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Beamr Validates ML-Safe Compression for dSPACE Data Logging

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Globe Newswire
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Pixazo API Now Supports Seedance 2.0 & GPT Image 2 — Bringing Next-Generation AI Video and Image Creation to Developers

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Beamr delivered 31% file size reduction compared to baseline encodes on footage from dSPACE RTMaps. Results to be demonstrated at dSPACE User Conference, April 21-22, Novi, Michigan

Beamr Imaging Ltd. (NASDAQ: BMR), a leader in video optimization technology and solutions, and dSPACE, a leading provider of solutions for the development of connected, autonomous, and electrically powered vehicles, today announced a joint demonstration validating, for the first time, compression for autonomous vehicle (AV) video data in the dSPACE RTMaps ecosystem while preserving machine learning (ML) model accuracy. The demonstration will be presented at dSPACE user conference, held from April 21-22 in Novi, Michigan.

AV fleets generate massive volumes of multi-camera video data during test drives. A single run produces terabytes of footage, choking storage, slowing data transfer, and extending development iteration cycles. Applying compression at the data logging stage reduces the volume of video data entering downstream storage and processing pipelines, where infrastructure costs accumulate at scale. Yet many AV teams hesitate to compress, lacking confidence that file size reduction can be achieved without compromising ML model accuracy.

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Testing on real-world sequences processed through dSPACE RTMaps showed Beamr Content-Adaptive Bitrate compression (CABR) delivered 31% file size reduction compared to baseline encodes, and 97% reduction for uncompressed data – while preserving ML model accuracy. RTMaps is a multisensor software framework for data logging and replay, software development, and real-time execution.

In previous benchmarks, CABR demonstrated ML-safe video data compression with up to 50% file size reduction for real-world and synthetic video data, across the AV pipeline. For object detection tasks, CABR showed <2% difference in mean Average Precision, well within the model’s expected variance. Testing with world foundation models showed no measurable impact on AV captioning, evaluated using two embedding models. Beamr and dSPACE plan to extend ML-safe compression testing to additional stages, including video data simulation and hardware-in-the-loop (HIL) testing.

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“ML-safe compression is essential for any team running AV pipelines at scale,” said Dani Megrelishvili, Beamr Chief Product Officer. “Validating Beamr’s technology inside RTMaps brings that assurance into the dSPACE ecosystem, so teams already running these workflows can reduce their data volumes without rebuilding their pipeline.”

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Synthflow AI and 8×8 Enter Strategic Partnership to Deliver Next-Generation Agentic AI

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Business Wire
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Synthflow AI and 8x8 Enter Strategic Partnership to Deliver Next-Generation Agentic AI

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Synthflow AI, an enterprise AI agent platform that automates customer conversations, has formed a strategic partnership with 8×8, Inc. , a leading global business communications platform provider, to bring Synthflow next-generation AI agents to enterprise contact centers.

This collaboration integrates Synthflow into the 8×8 Contact Center, automating self-service while enhancing agent support across AI calls, chat, and digital channels. The new technology helps joint customers avoid missing calls, ultimately converting more leads, empowering customers to increase their CSAT scores, and reducing operational costs. Additionally, customers can set up Al answering assistants without developer support.

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The global voice AI market is expected to grow to $54 billion by 2033, and this partnership addresses the growing need for modern, enterprise-ready conversational AI. By replacing legacy point solutions, Synthflow enables joint customers to avoid long implementation cycles and complex setups. The platform delivers natural, human-like conversations with low latency, advanced interruption handling, memory capabilities, and support for over 30 languages. These features allow businesses to achieve faster resolution times and higher containment rates.

Hakob Astabatsyan, CEO of Synthflow, said: “Our partnership with 8×8 validates the strength of our agentic AI capabilities and the sophisticated framework we use. Having handled over 65 million voice interactions, we’ve seen firsthand the significant impact that transformative AI has on businesses in driving efficiency, satisfaction, and lowering costs.

“We give 8×8 and Synthflow customers an agile, innovation-focused alternative to legacy systems, making it easier than ever to transform customer interactions with intelligent automation at scale.”

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The integration provides a distinct competitive advantage in the cloud contact center market. The long-term strategic alignment also includes future roadmap initiatives, such as enabling 8×8 and its channel partners to resell Synthflow directly, alongside offering the platform to small and medium businesses through the 8×8 App Store.

Victor Belfor, Global Vice President, Business Development and Strategic Partnerships at 8×8, Inc., said: “As consumers become increasingly comfortable engaging with AI agents, it’s vital that our customers recognize this channel as a priority for seamless, effective customer engagement. By partnering with Synthflow, we’re providing joint customers with the modern capabilities they need to help improve their satisfaction scores and quickly implement advanced voice automation.”

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Trust3 AI Announces Native Integration with Google Cloud’s Agentic AI Stack to Deliver Data and AI Governance for Agentic Applications

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PRNewswire
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Trust3 AI Announces Native Integration with Google Cloud's Agentic AI Stack to Deliver Data and AI Governance for Agentic Applications

Trust3 AI, the unified data and AI governance platform, announced a new integration with Google Cloud’s agentic AI stack, including the Agent Development Kit (ADK) and Vertex AI Agent Builder. The combined solution helps enterprises design, deploy, and scale Gemini‑powered and multi‑model AI agents with built in guardrails, continuous policy enforcement, and full lifecycle observability across data and AI.

As enterprises move from single‑prompt chatbots to complex agentic systems, they face three compounding risks: uncontrolled agent sprawl, opaque decision‑making, and fragmented governance across data, models, and tools. Google’s ADK and Vertex AI Agent Builder provide a powerful foundation to build multi‑agent applications with Gemini and other models, connect agents to 100+ systems via connectors and MCP, and orchestrate autonomous workflows at scale.

However, without a unified trust layer, enterprises still struggle to ensure that every agent action respects data policies, regulatory obligations, and business logic across clouds and applications.

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What Trust3 AI adds

Trust3 AI delivers a unified platform that governs both data and AI, powered by automated “Trust Agents” that continuously monitor and control how agents access data, call tools, and take actions. Trust3 AI already provides agentic governance for modern data platforms such as Snowflake, Databricks, and Starburst with features like a unified catalog, intent‑based PBAC, semantic enrichment, and end‑to‑end auditability.

“Agentic systems are only as valuable as they are trustworthy,” said Christophe Hassaine, VP of Alliance at Trust3 AI. “By integrating natively with Google’s agentic AI stack, we make it possible for enterprises to go from POC to production with Gemini and multi‑agent applications – without sacrificing governance, compliance, or control.”

With this new integration, Trust3 AI becomes a native trust layer for agentic applications built on Google Cloud – wrapping Gemini‑based agents, ADK workflows, and Vertex AI Agent Builder experiences with policy‑aware controls, observability, and compliance.

Policy-Aware Agents for Smarter AI Governance

Trust3 AI integrates seamlessly with ADK-based agents and Vertex AI Agent Builder workloads, acting as a critical policy decision and enforcement point. By evaluating every agent request against natural-language policies, intent-based PBAC (Policy-Based Access Control) rules, and regulatory frameworks like GDPR, HIPAA, and the EU AI Act, Trust3 AI ensures secure and compliant execution of actions.

Unified Governance Across the AI Ecosystem

With its unified catalog, Trust3 AI bridges the gap between raw data sources, governed datasets, and AI applications. This transparency allows enterprises to trace agent activity, while identifying which data was accessed, under what policies, and for what business purposes. Leveraging Google’s MCP support and pre-built connectors, Trust3 AI extends governance from data platforms into downstream SaaS applications and custom tools used by ADK or Vertex agents.

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Trust Agents: Enhancing Agentic AI Reliability

To govern multi-agent topologies, Trust3 AI deploys specialized Trust Agents that monitor how agents delegate tasks, share session states, and orchestrate actions across Google’s agentic architecture. These Trust Agents proactively detect risky behaviors, hallucination-prone patterns, and policy violations in real time. They can intervene automatically, reroute tasks to safer agents, or escalate for human approval, ensuring trust and reliability in agentic AI systems.

Building Trust Across Agent Ecosystems

Google’s Agent2Agent (A2A) protocol enables interoperability between agents built on different frameworks and vendors. Trust3 AI enhances this capability by adding a consistent trust and audit layer to cross-vendor interactions. Enterprises can securely connect internal ADK agents with third-party or partner agents while maintaining end-to-end visibility, robust guardrails, and tamper-proof audit trails.

Lifecycle Governance and Observability for AI Workloads

Trust3 AI captures rich telemetry from agent prompts, tool calls, decisions, and outcomes, providing architecture and risk teams with a unified view of Gemini-based and multi-model agentic workloads on Google Cloud. This comprehensive observability allows teams to experiment, refine policies, and continuously optimize agents while meeting audit and reporting requirements – all without slowing down innovation.

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8×8 Launches Retail Nationwide in the UK to Close the Communication Gap Costing Stores Sales

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Business Wire
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8x8 Launches Retail Nationwide in the UK to Close the Communication Gap Costing Stores Sales

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Mobile-First UC Offering Designed for Shared Devices, Shift-Based Teams, and Multi-Location Retail Operations Launches for the UK at Retail Technology Show 2026

Solving the problem of communication tools being designed for desk-based workers, not mobile retail workers, 8×8, Inc., a leading global business communications platform provider, is using its presence at the Retail Technology Show 2026 to make its UK debut of Retail Nationwide — a unified communications offering built specifically for how store teams actually work.

Retail Nationwide addresses a structural mismatch that costs UK retailers daily. Most enterprise communication tools were designed for office staff with assigned phones and fixed desks. Retail doesn’t work that way. When a call comes in, the nearest available person should be able to answer it – but most current setups aren’t configured for that. The result is missed calls, inconsistent responsiveness, and IT teams managing the fallout across dozens or hundreds of locations.

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Retail Nationwide is built around how stores actually operate. Calls ring across all connected devices, whoever is available answers. Configuration is standardised across locations, reducing provisioning time when new stores open.

Each licence works with a desk phone plus up to five shared mobile or tablet devices, so the store environment is covered without requiring individual licences for every staff member.

“UK retailers are managing more complexity with leaner teams than ever with staff helping customers, dealing with online orders, trying to answer queries across multiple channels, and so much more,” said Michelle Kelly, Retail Expert at 8×8, Inc. “The communication infrastructure many stores are running on wasn’t built for that. It was built for a world where everyone has a desk and phone and has been shoehorned into retail, resulting in a poor employee and customer experience. Retail Nationwide changes all that and has a pricing model that reflects the retail reality.”

8×8 will be attending Retail Technology Show 2026 alongside channel partner Global Telecom Networks (GTN).

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“What we hear consistently from UK retailers is that their frontline teams are difficult to reach and expensive to equip,” said Vipool Umaria, Chief Operations Officer at Global Telecom Networks. “The licensing model alone creates friction — staff turnover, licences go unused, IT has to keep pace with store changes. Retail Nationwide cuts through all of that. It’s a model built around how retail actually staffs and operates and that attention to detail in the industry is why we are working with 8×8.”

Retail-specific solutions designed to drive measurable outcomes

In addition to Retail Nationwide, 8×8 will showcase retail-focused solutions that help businesses increase conversion, improve post-purchase experiences, and build lasting customer relationships, including:

  • 8×8 Aftersale Assist helps retailers resolve issues faster after purchase by using AI-powered self-service and one-way video support, improving customer satisfaction while reducing avoidable returns and support costs.
  • 8×8 Sales Assist helps sales teams engage customers more effectively with AI-driven insights and guided conversations, improving efficiency, increasing personalization, and driving repeat purchases and loyalty.

8×8 will also demonstrate its core retail communication capabilities, including MDM integration for large-scale device management, support for shared handheld devices with simplified store-associate onboarding, centralized remote configuration for consistent multi-site communication, and a dedicated managed version of the 8×8 Work app optimized for MDM-based deployments.

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Particular Audience Launches PA DiscoveryOS on Shopify

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MTS Staff Writer
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Particular Audience Launches PA DiscoveryOS on Shopify

Getting Started | Particular Audience Docs

The move brings enterprise AI search, retail media and agentic commerce to millions of merchants


Particular Audience announced the official launch of the PA DiscoveryOS app on the Shopify App Store. The launch marks a major milestone for the ecommerce industry, taking complex, enterprise-grade AI capabilities—historically reserved for retail giants with massive engineering budgets—and making them instantly accessible to Shopify Plus merchants via a seamless, zero-code integration.

Previously, integrating enterprise AI search, personalization, and retail media engines required complex headless architecture and custom APIs, costing tens of thousands of dollars and taking three to six months to deploy. PA DiscoveryOS slashes this integration time by over 99%, taking the implementation time from months to minutes.

“With PA DiscoveryOS, we are eliminating the technical barriers that have kept mid-market and enterprise Shopify merchants from unlocking their full revenue potential,” said James Taylor, CEO & Founder at Particular Audience. “Merchants can now deploy a state-of-the-art AI infrastructure overnight, instantly driving higher average order values and unlocking entirely new, high-margin revenue streams.”

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The PA DiscoveryOS Shopify app introduces a comprehensive suite of advanced commerce features, including:

  • Next-Generation “Hybrid” AI Search: Powered by Adaptive Transformer Search, the platform combines vector search (understanding natural language and semantic context) with traditional keyword technology. Supported by live A/B testing, it effortlessly handles complex shopper queries and eliminates frustrating “0 results” pages.
  • Automated Bundling Technology: Moving beyond static, manual cross-sells, machine learning generates highly relevant, dynamic product bundles at the exact point of decision, driving immediate increases in Units Per Transaction (UPT) by 30-60%.
  • Onsite Retail Media Networks: Merchants can now monetize their own website traffic. PA DiscoveryOS provides the infrastructure to serve targeted, AI-driven sponsored products, turning a store into a highly profitable ad network.
  • Dynamic Shelves & Contextual Discovery: Brands can deploy intelligent, algorithmic product carousels across any page that adapt to user intent in real-time, mimicking the intuitive discovery feeds of social media platforms.
  • Native Video & Rich Media: The app bridges the gap between content and commerce by integrating shoppable videos and dynamic lifestyle assets directly into search results and personalized shelves, driving higher engagement.
  • Real-Time “Anonymous” Personalization: Through session-based intent modeling, the platform delivers 1-to-1 personalization for anonymous visitors based on live behavior, predicting needs before a user ever logs in or creates an account.
  • Advanced SEO & Merchandising Automation: The app introduces semantic merchandising to effortlessly organize massive catalogs, while automatically generating static SEO pages for unique attribute combinations (e.g., “blue running shoes for flat feet”) to capture niche, long-tail Google traffic.

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Crucially, the launch of PA DiscoveryOS on Shopify does more than optimize the traditional storefront; it prepares merchants for the future of AI-driven shopping. By standardizing catalog and intent data, the app lays the foundation for retailers to connect with Retail-MCP.com, Particular Audience’s open-source framework utilizing the Model Context Protocol (MCP). This integration unlocks conversational AI platforms as direct sales channels. Merchants can deploy “Functional Ad Units” within AI apps, allowing customers to discover products, check real-time inventory, and complete checkout natively inside conversational interfaces—ensuring Shopify merchants are fully equipped to monetize API payloads in the era of agentic commerce.

Particular Audience is the leading AI-native retail media and personalisation platform, powering both organic and sponsored personalised product discovery through its DiscoveryOS platform. With operations across the US, UK, Canada, and Australia, Particular Audience partners with the world’s most ambitious retailers including Target, The Good Guys, Petbarn, Hamleys and Hotel Chocolat to boost conversion, increase ad revenue and lift shopper satisfaction, without compromising user experience. Particular Audience supports global enterprise retailers, while advancing open-source standards like the Model Context Protocol (MCP) that enable agentic commerce. The company’s mission is to show every shopper exactly what they want – before they know they want it – while driving profitable growth for the merchants who serve them.

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Bearingpoint Launches Genaiq to Turn Generative AI Into Enterprise-Scale Automation

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Business Wire
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BlueConic Launches Agentic Growth Plays, Ending the Era of Customer Data That Goes Nowhere

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GenAIQ helps organizations scale generative AI from isolated pilots to secure, enterprise-wide automation across their business functions.

BearingPoint announced the launch of GenAIQ, its proprietary agentic AI platform designed to help organizations move beyond fragmented AI pilots and into real operational impact. Built for enterprise environments, GenAIQ automates knowledge-intensive tasks and business processes while enabling transparency, governance, and seamless integration with existing IT landscapes.

GenAIQ provides a scalable, integrated platform that transforms agentic AI into a reliable foundation for business automation.

Why it matters now

While many organizations are exploring generative AI, few succeed in scaling it into daily operations. Fragmented data, document-heavy workflows, and increasing demands for transparency, compliance, and control continue to slow adoption. GenAIQ addresses these challenges by combining agentic AI, domain-specific intelligence, and deep enterprise integration in a single, modular platform – turning experimentation into scalable execution.

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Business value and adoption

GenAIQ supports organizations at every stage of their AI journey – from task-level assistance to fully automated, end-to-end processes. Powered by 60+ industry-specific agents and proven workflows available through its agent store, the platform reduces manual effort in knowledge-intensive work, improves output quality, and accelerates time to value.

BearingPoint supports clients end-to-end, from identifying high-impact use cases to implementation, enablement, and long-term scaling.

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“Many organizations are experimenting with generative AI but struggle to scale beyond isolated use cases,” says Tomas Chroust, Partner and Head of CoE Data Analytics & AI at BearingPoint. “GenAIQ provides a scalable, integrated platform that transforms agentic AI into a reliable foundation for business automation.”

“GenAIQ was built to evolve with our clients’ ambitions,” adds Tessen Fritzsche, Product Manager GenAIQ at BearingPoint. “Whether starting with task-level support or moving toward end-to-end automation, the platform delivers flexibility, transparency, and enterprise-grade control.”

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Relynta Expands Its Inbox-First AI CRM Into an End-to-End Client Workflow Platform for Service Businesses

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MTS Staff Writer
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Relynta Expands Its Inbox-First AI CRM Into an End-to-End Client Workflow Platform for Service Businesses

Relynta helps service businesses move from website inquiry to AI reply, proposal, e-signature, scheduling, invoicing, and payment in one workspace

Relynta, the inbox-first AI CRM built for small businesses, announced its expanded end-to-end workflow for service businesses, bringing lead capture, customer communication, proposals, e-signatures, appointments, invoicing, payments, and follow-up into a single connected platform.

While many small and midsize service businesses still rely on a patchwork of inbox tools, spreadsheets, calendars, e-signature platforms, invoicing systems, and disconnected CRMs, Relynta is designed to bring the full customer lifecycle into one workspace centered around the conversation.

Relynta’s expanded service-business workflow helps teams handle the full path from first contact to closed deal and paid invoice. Businesses can capture website inquiries, respond faster with AI-assisted drafts grounded in their own business knowledge, create customer records automatically, manage opportunities in pipeline, send proposals, collect signatures, schedule appointments, issue invoices, accept online payments, and continue follow-up through email, SMS, and campaigns.

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“Small service businesses do not need more software tabs. They need one practical system that helps them respond faster, stay organized, and get paid,” said a Relynta spokesperson. “Relynta was built to reduce the friction between customer inquiry, follow-up, quoting, signing, scheduling, and billing — so teams can run the business from one place instead of stitching together five to eight tools.”

The platform is designed for service-oriented businesses such as agencies, consultants, real estate professionals, insurance teams, home-service operators, and other growing SMBs that depend on fast response times and consistent follow-up to win revenue.

Key capabilities now highlighted in Relynta’s service-business workflow include:

AI-powered shared inbox with business-aware draft replies
Automatic contact creation and customer timeline
Pipeline and deal tracking tied to real conversations
Proposal builder with professional templates and AI-generated content
Built-in e-signature workflow for agreements and documents
Appointment booking and reminders
Estimates, invoicing, and online payments
Two-way SMS and follow-up campaigns
Client portal for approvals, payments, appointments, and documents
Inbound form capture from website and third-party forms

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For many service businesses, the problem is not a lack of customer demand, but a lack of operational continuity between tools. Leads can sit in email too long, quotes may be delayed, contracts live elsewhere, and payment follow-up becomes manual. Relynta’s approach is to keep everything connected to the customer record and the underlying conversation, giving teams more visibility and less administrative overhead.

“With Relynta, the inbox is no longer isolated from the rest of the business,” the spokesperson added. “The same workflow that starts with an inquiry can continue through proposal, signature, appointment, invoice, payment, and long-term follow-up. That is the experience many service businesses have been missing.”

Relynta offers plans for solo operators and growing teams, with features spanning AI inbox, CRM, pipelines, proposals, e-signatures, inbound forms, estimates, invoicing, campaigns, appointments, and client portal functionality.

Businesses interested in learning more can visit Relynta online to explore product capabilities, pricing, and request a personalized demo. Relynta also offers a 14-day free trial, giving service businesses a chance to explore its AI-powered inbox, CRM, proposals, e-signatures, scheduling, invoicing, payments, and follow-up workflows before subscribing.

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Bless Web Designs Guarantees Dallas Businesses Appear in AI Search Results

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Bless Web Designs Guarantees Dallas Businesses Appear in AI Search Results

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First Dallas agency guarantees businesses appear in ChatGPT and AI search results within 90 days—addressing invisibility crisis as 67% of searches use AI.

Bless Web Designs, the #1-ranked Dallas web design agency by Clutch and GoodFirms, announced the industry’s first AI Search Visibility Guarantee™—a groundbreaking commitment ensuring Dallas businesses appear in ChatGPT, Google AI Overviews, and Perplexity search results within 90 days when implementing the agency’s comprehensive AI-optimized website packages. This unprecedented guarantee directly addresses the emerging crisis of AI search invisibility affecting an estimated 60-70% of Dallas small businesses as artificial intelligence fundamentally reshapes how consumers discover and evaluate local service providers.

We analyzed 100 Dallas businesses and found only 23% appear in AI search results. This invisibility crisis will cost billions in lost revenue. Our guarantee ensures this never happens to our clients.”

— Nibin Varghese, Creative Director, Bless Web Designs

The AI Search Revolution Creates Unprecedented Visibility Crisis
The landscape of business discovery has undergone a seismic shift in the past 18 months. According to recent search behavior data compiled by leading analytics firms, 67% of all searches now generate AI-powered answers through platforms like ChatGPT, Google’s AI Overviews, Perplexity, and other large language model interfaces. This percentage is projected to reach 85% by early 2027, fundamentally changing how consumers discover local businesses. Traditional search engine optimization alone no longer guarantees visibility when potential customers ask AI assistants for recommendations, creating what industry experts are calling the AI invisibility crisis.

When Dallas residents ask ChatGPT for plumber recommendations, query Perplexity for restaurant suggestions, or rely on Google AI Overviews for service provider comparisons, businesses optimized only for Google’s traditional search results remain completely invisible. These businesses lose opportunities to the small percentage of competitors whose websites are structured for AI comprehension and citation, creating a growing competitive disadvantage that most business owners don’t even realize exists.

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“We conducted an extensive analysis of 100 Dallas small businesses across ten different industries including home services, healthcare, legal, restaurants, retail, and professional services,” said Nibin Varghese, Creative Director and Co-Founder of Bless Web Designs. “The results were alarming. Only 23% of these businesses appeared when we asked leading AI platforms for local recommendations in their categories. These businesses have strong Google rankings, excellent reputations, positive reviews, and quality websites, yet they’re completely invisible in AI search results. This invisibility crisis will cost Dallas businesses billions in lost revenue over the next five years if left unaddressed.”

Industry-First Guarantee Sets New Standard for Accountability
The AI Search Visibility Guarantee™ represents the first verifiable commitment by any Dallas web design agency to ensure clients achieve measurable AI search presence through comprehensive AI-optimized website packages. While other agencies discuss AI optimization in vague terms or offer it as an expensive add-on service, Bless Web Designs has integrated advanced AI optimization into its professional website packages specifically designed to achieve visibility across both traditional and AI-powered search platforms.

Under the guarantee terms, Bless Web Designs commits to implementing comprehensive AI optimization strategies across multiple technical and content dimensions, then verifies client visibility through documented AI search queries across ChatGPT, Google AI Overviews, Perplexity, and other major AI platforms. The guarantee applies to relevant industry and location-specific queries that potential customers would realistically use when seeking services.

The guarantee is included with Bless Web Designs’ professional AI-optimized website packages, which incorporate the technical architecture, content depth, and structural elements required for effective AI search visibility. These packages include five core components that work synergistically to achieve AI citation.

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Five Core Components of AI Search Visibility
Entity Optimization and Authority Building: Establishing clear business entity signals that AI systems recognize and trust represents the foundation of AI visibility. This includes comprehensive structured data markup implementing Schema.org vocabularies for LocalBusiness, Service, Organization, and relevant industry-specific schemas. The process includes authoritative directory presence across 40 plus high-trust platforms that AI systems reference for verification, consistent NAP information across the web, claimed and optimized knowledge panel information, and authoritative backlink profiles from recognized industry sources.

AI systems don’t simply crawl websites randomly. They verify entity claims against multiple authoritative sources, much like a journalist fact-checking a story. A business claiming to be Dallas’s leading plumber must have that claim validated through consistent presence in trusted business directories, industry associations, review platforms, and local chamber memberships. Bless Web Designs ensures every client achieves this authoritative entity foundation through its comprehensive AI-optimized packages.

AI-Readable Architecture and Semantic Structure: Traditional SEO optimizes for keyword matching and backlink authority. AI optimization requires fundamentally different technical architecture that enables large language models to comprehend, extract, and confidently cite business information. This includes implementation of llms.txt files that provide AI systems with explicit, structured business information in a format designed specifically for machine comprehension rather than human reading.

The architecture includes natural language business descriptions that explain services, specialties, and value propositions in conversational terms AI systems can parse and paraphrase. Semantic HTML structure using proper heading hierarchies, descriptive lists, and meaningful markup helps AI systems understand content relationships and context. FAQ schemas with question-answer pairs provide clear, citation-friendly content that AI systems frequently reference when constructing responses. Clean, crawlable site architecture ensures AI crawlers can efficiently access and index all relevant content without encountering technical barriers.

“The websites that appear in AI search results aren’t necessarily the ones with the highest Google rankings,” Varghese noted. “They’re the websites that AI systems can read, understand, and confidently cite. We’ve reverse-engineered what makes websites citation-worthy and built that into our professional AI-optimized website packages.”

Citation-Worthy Content Development: AI systems cite sources they perceive as authoritative, accurate, and helpful. Creating citation-worthy content requires understanding how AI platforms evaluate source quality and structure content accordingly. This includes expertise-demonstrating content that showcases specific knowledge, methodologies, and industry insights rather than generic marketing copy. Specific, verifiable claims with concrete numbers, timeframes, and measurable outcomes that AI systems can extract and cite with confidence replace vague promises and superlatives.

Location-specific content addressing Dallas neighborhoods, local business contexts, and regional considerations helps AI systems understand geographic relevance when responding to location-based queries. Problem-solution frameworks that clearly articulate customer pain points and systematic solutions provide the narrative structure AI systems prefer when constructing comprehensive answers. Original research, case studies, and data create unique, citation-worthy information that positions the business as an industry authority rather than just another service provider.
The depth and breadth of content required for AI visibility demands comprehensive website packages with sufficient pages, service descriptions, and supporting content to establish topical authority that AI systems recognize and cite.

Verification, Monitoring, and Continuous Optimization: Unlike traditional SEO where rankings can be checked through simple position tracking, AI visibility requires active querying and monitoring across multiple platforms. Bless Web Designs provides monthly AI visibility reports documenting exact queries tested, platforms evaluated, and citation frequency achieved. These reports include screenshots of actual AI responses showing how the business is mentioned and positioned relative to competitors.

90-Day Performance Commitment with Continued Optimization: If the business does not appear in AI search results for relevant industry and location queries within 90 days of launch, Bless Web Designs continues implementing advanced AI optimization strategies at zero additional cost until visibility is achieved. This ongoing commitment includes enhanced entity optimization, expanded citation-worthy content, additional structured data implementation, and technical architecture improvements based on platform-specific requirements observed during the initial optimization period.

“The guarantee isn’t just a promise, it’s our commitment to your success,” Varghese emphasized. “If our initial comprehensive optimization doesn’t achieve the visibility results you need, we continue refining and enhancing the strategies at no extra cost. Our reputation depends on our clients’ success in this new search landscape, and we’ve structured our professional packages to deliver measurable AI visibility.”

Proven Methodology Behind the Guarantee
Bless Web Designs’ confidence in offering this unprecedented guarantee stems from documented success with its proprietary Neuro-Responsive Framework, which has successfully positioned Dallas businesses for AI visibility across multiple search platforms while simultaneously improving traditional search rankings and conversion rates.

The framework represents 15 years of web design evolution and has been specifically enhanced for AI search optimization over the past 18 months. Recent client results demonstrate the framework’s effectiveness across diverse industries and business models.

TX Whiskey, a Dallas entertainment venue and whiskey bar with a fully-optimized professional website package, receives citations in AI-generated Dallas entertainment recommendations and activity suggestions for both locals and tourists. This AI visibility has contributed to a 375 percent increase in event signups and 220 percent increase in website visitors. When travelers ask ChatGPT or Perplexity for Dallas nightlife recommendations or whiskey tasting experiences, TX Whiskey appears prominently in the results.

Prestige Business Brokers, serving Dallas business owners looking to buy or sell companies through a comprehensive business-focused website with AI optimization, appears in Perplexity results for business broker searches and receives ChatGPT citations for business valuation and sale process questions. The firm reports improved lead quality and client intake as AI-referred leads arrive with higher intent and better understanding of the services provided.
Dallas Mobile Pet Spa achieved a 1400 percent increase in weekly leads with the booking rate multiplied by five times after implementing a comprehensive service business website package with full AI optimization. The mobile pet grooming service now appears when Dallas pet owners ask AI platforms for convenient, at-home pet care solutions.

The Neuro-Responsive Framework: Three Scientific Principles
The framework combines three scientifically-validated principles that work synergistically to deliver results for both human visitors and AI systems.

Cognitive-First Design applies psychological principles from behavioral economics, decision science, and conversion optimization research. The design guides human visitor attention through strategic visual hierarchy, removes friction from decision-making processes through simplified navigation and clear calls-to-action, and builds trust through social proof, credentials, and transparent communication. Simultaneously, these design principles create content patterns AI systems recognize as authoritative and citation-worthy. Clear problem-solution frameworks, logical information architecture, and explicit expertise demonstrations signal to both human visitors and AI systems that the business is a reliable information source.

AI-Ready Architecture implements technical structures enabling both traditional search engines and AI agents to instantly comprehend business offerings, service areas, expertise credentials, and unique value propositions. This includes structured data vocabularies, semantic HTML markup, natural language descriptions, and explicit entity relationships. The architecture follows best practices from both traditional SEO and emerging AI optimization research, ensuring websites perform well across all discovery channels rather than optimizing for one at the expense of others.

Comprehensive AI-Optimized Website Packages
The AI Search Visibility Guarantee is included with Bless Web Designs’ professional website packages specifically designed to achieve visibility across both traditional and AI-powered search platforms. These comprehensive packages include all technical, content, and structural elements required for effective AI optimization.

Professional AI-optimized packages include custom website design tailored to the business rather than generic templates, with sufficient page depth and content breadth to establish topical authority. Natural language business descriptions explain services in conversational terms AI systems can easily parse and paraphrase. Comprehensive structured data implementation covers LocalBusiness, Service, Organization, Product, FAQ, and industry-specific schemas that AI systems reference for verification.

Bless Web’s strategies provide AI systems with explicit, structured business information in their preferred format. Citation-worthy content development demonstrates subject matter expertise through case studies, methodology explanations, problem-solving frameworks, and industry insights across multiple pages and content types. Google Business Profile optimization ensures local AI search queries capture the business when people ask about services in specific Dallas neighborhoods or ZIP codes.

Mobile-first responsive design ensures perfect functionality across all devices, as 60 percent of search traffic now originates from mobile devices. Security implementation includes SSL certificates, regular backups, malware scanning, and security best practices that protect both the business and customer data. Analytics tracking covers both traditional search traffic and AI referral traffic, providing comprehensive visibility into all discovery channels.

Professional AI-optimized website packages start at $2,490 and include zero monthly fees with 100 percent code ownership, meaning businesses own their websites outright rather than renting them. Three months of post-launch support addresses any questions or minor updates needed as the business familiarizes itself with the new platform. All packages include the industry’s only 100 percent money-back satisfaction guarantee, demonstrating Bless Web Designs’ confidence in delivering quality and results.

“AI optimization isn’t a simple add-on or quick fix,” Varghese explained. “It requires comprehensive website architecture, sufficient content depth, proper technical implementation, and ongoing refinement. That’s why we’ve built it into our professional packages from the ground up rather than offering it as an afterthought. Businesses investing in AI-optimized websites are positioning themselves for the future of search, not just addressing today’s needs.”

Industry Recognition Validates Expertise
Bless Web Designs’ AI optimization expertise and overall web design methodology has earned recognition from leading industry authorities. The agency maintains the number one ranking for Web Design Agency in Dallas by Clutch based on verified client reviews and project outcomes. UpCity has designated Bless Web Designs as a Top Web Designer in Dallas. DesignRush ranks Bless Web Designs as the number one Rated Web Design Agency. Expertise.com selected Bless Web Designs as Best Web Designer in Dallas. Tech Behemoths nominated Bless Web Designs for the 2025 Best Web Design Company award. Three Best Rated has chosen Bless Web Designs as one of the 3 Best Web Designers in Dallas. GoodFirms ranks Bless Web Designs as the number one Top Web Design Company in Dallas. The Better Business Bureau has awarded Bless Web Designs an A-plus Accredited Business rating, the highest possible score for trustworthiness and transparency.

Serving Dallas Businesses Across All Industries
Based in Uptown Dallas and Garland, Bless Web Designs serves businesses across the entire DFW Metroplex including Dallas, Plano, Frisco, McKinney, Allen, Richardson, Garland, Mesquite, Rowlett, Rockwall, Fort Worth, Arlington, Grand Prairie, Irving, Carrollton, Lewisville, Denton, Grapevine, Southlake, and surrounding communities.

The agency has developed industry-specific expertise serving home services contractors including plumbers, electricians, HVAC companies, roofers, landscapers, painters, and general contractors. Healthcare practices including doctors, dentists, chiropractors, therapists, and medical spas benefit from HIPAA-compliant solutions. Legal professionals including law firms and attorneys receive attorney-specific optimization. Restaurants, cafes, bars, and food service businesses get menu integration and online ordering.

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Synup Launches MCP Server to Power AI-Driven Workflows for Marketing Agencies

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Synup Launches MCP Server to Power AI-Driven Workflows for Marketing Agencies

Synup Listing & Reputation Management Software

Agencies can now build their own AI agents on top of Synup’s local marketing platform, automating everything from review responses to listings management through the open Model Context Protocol standard.

Synup, a leader in agency-focused marketing technology, today announced the launch of Synup MCP, a Model Context Protocol server that lets marketing agencies and reseller partners connect AI agents directly to Synup’s full suite of local marketing tools. With Synup MCP, agencies can build AI-powered workflows that manage listings, respond to reviews, publish social content, and analyze local search performance, all through a single, standardized protocol.

The Model Context Protocol (MCP) is an open standard that has quickly become the go-to way for AI models to talk to external tools and data sources. It’s already supported by Claude, ChatGPT, Gemini, Microsoft Copilot, and thousands of developer tools. By launching a native MCP server, Synup becomes one of the first local marketing platforms to give agencies a way to plug their own AI agents into a production-grade marketing stack, no custom API work required.

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“Agencies have always been early adopters of technology that helps them do more with less, and AI agents represent the biggest unlock we’ve seen in a decade,” said Ashwin Ramesh, Founder and CEO of Synup. “With Synup MCP, we’re not handing agencies another dashboard to log into. We’re giving them the infrastructure to build their own intelligent systems on top of our platform. An agency can now have an AI agent that monitors every client’s reviews, drafts responses in the brand’s voice, flags reputation risks, and updates listings across hundreds of locations, all running on its own. That’s the future of agency operations, and we want our partners building it on Synup.”

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Why This Matters for Agencies

The marketing agency industry is valued at $18 billion annually, with over 50,000 agencies serving small businesses across the country. Many of these agencies have adopted AI tools for simple tasks like writing content or scheduling social media posts or tracking rankings. But the ability to connect those tasks into intelligent, multi-step workflows that run without constant human oversight has been out of reach for all but the most technical teams.

Synup MCP changes that. It exposes the full Synup platform as a set of tools that any MCP-compatible AI agent can discover, connect to, and act on. It doesn’t matter whether an agency builds agents using Claude, GPT, Gemini, or open-source models. Synup MCP works with all of them.

What Agencies Can Do With Synup MCP

  • Manage listings at scale with AI agents. Build agents to manage listings across the major publishers for you. They’ll push updates when something changes, and flag the listings that have drifted out of sync. No one has to babysit a spreadsheet.
  • Automate review monitoring and response. Build agents that can watch for incoming reviews, draft on-brand responses, escalate negative sentiment, and help agencies maintain response SLAs across every client.
  • Orchestrate social content. The AI workflows can write the posts, queue them up, and publish them for you. Works across the usual platforms. If you’re juggling a lot of client accounts, it’s the difference between posting regularly and meaning to post regularly.
  • Pull local SEO insights without the manual digging. Agents can pull grid ranking data and share of voice metrics to flag opportunities and trigger optimization workflows without waiting for a human to spot the trend.
  • Turn account management into a growth engine. Connected to Synup OS, you can tap into client health data, churn risk indicators, and upsell signals, helping agencies get ahead of problems instead of reacting to them.
  • Keep everything white-labeled. All MCP-powered workflows run within Synup’s white-label framework, so agencies can offer AI-driven services under their own brand.

“We designed Synup MCP with a simple principle: agencies shouldn’t need a dev team to take advantage of AI,” said Roshan Agarkar, VP of Product at Synup. “The MCP standard takes the integration headache off the table. Bring your own AI tool. Connect it to Synup. Start automating the same day. You don’t need a developer sitting next to you.. For agencies that do have technical teams, the possibilities open up even further. We’re talking about custom reputation management bots, fully autonomous local SEO pipelines, and workflows we haven’t even imagined yet. We built the rails. Our agency partners get to decide where they go.”

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Candid Appoints Andrew Shaw as Chief Product & Technology Officer to Accelerate Platform Growth

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Candid Appoints Andrew Shaw as Chief Product & Technology Officer to Accelerate Platform Growth

Seasoned product leader joins from OLX to scale Candid’s Live Marketing™ AI infrastructure across the UK and beyond

Candid, the platform-based advertising, marketing and communications group operating across the Netherlands and the United Kingdom, has appointed Andrew Shaw as Chief Product & Technology Officer (CPTO), effective immediately.

Working at group level, Shaw assumes responsibility for Candid’s product strategy, technology infrastructure and the scaling of its agency brands and capabilities. His appointment comes at a pivotal moment for the group, with strong and growing market demand for Candid’s proprietary Live Marketing™ platform — an integrated, AI-powered infrastructure spanning strategy, campaigns, media and creative. Shaw’s immediate mandate is to accelerate its development and bring it to enterprise scale.

Shaw joins with a strong international pedigree in product leadership and technology innovation. He was most recently Director of Product at OLX in Amsterdam, and prior to that held a comparable senior product role at adidas in Germany. Originally from South Africa, Shaw spent over five years in Germany before relocating to the Netherlands four years ago, where he has built deep expertise working within complex, international technology organisations.

In his new role, Shaw will work across Candid’s group of agencies and brands — building the product and technology foundations that underpin the group’s client proposition and ensuring the Candid platform maintains its competitive edge in a fast-evolving market.

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Andrew Shaw, Chief Product & Technology Officer, Candid:

“My remit is clear: to take Candid’s Live Marketing™ infrastructure from proven technology to a truly differentiated, enterprise-grade and scalable platform — one that holds its competitive advantage in a market that is moving fast.”

Gerard Ghazarian, Founder & President, Candid:

“Andrew brings exactly the depth of product and technology leadership that this moment calls for. He will be instrumental in shaping our product strategy and in building the technology organisation we need to realise our ambitions — in the UK, the Netherlands, and beyond.”

Shaw’s appointment represents a significant step in Candid’s continued investment in its technology capabilities and leadership team. As the group scales across its agency brands and geographies, this appointment signals an unambiguous commitment to building a robust, future-proof platform that delivers tangible, measurable value for clients and brand partners across the portfolio.

Marketing Technology News: The ‘Demand Gen’ Delusion (And What To Do About It)

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Efficiency in First-Price Auctions Starts at the Bid

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Anthony Juda
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Efficiency in First-Price Auctions Starts at the Bid

Today’s programmatic buyers are operating under tighter budgets and greater pressure to prove results than ever before. In response, most optimization efforts have gone toward refining who to reach and how success is measured. Yet, in a first-price auction environment, efficiency is shaped not only by audience strategy and measurement, but by how accurately advertisers price each impression at bid time.

Win-price optimization addresses this problem directly. Instead of bidding high to avoid missing impressions, win-price algorithms estimate what an impression is likely to clear for and bid just above that level. The shift is subtle but meaningful – efficiency is no longer just about impacting bidding power, but about improving pricing accuracy.

Why does this distinction matter? Because in a first-price auction, the bid is the price. When a bidding model overestimates an impression’s value, even slightly, the buyer pays the difference. Across thousands of auctions a day, that overpayment compounds –campaigns may appear healthy on the surface while efficiency steadily erodes underneath, with no obvious signal that anything is wrong.

Consider a buyer planning a broad video campaign with a $10 target CPM, for instance. Under conventional bidding logic, the model may routinely bid near that ceiling to secure wins, even when similar impressions frequently clear for far less. In a first-price auction, those inflated bids become the final price. Over time, the campaign wins roughly the same volume of impressions it would have otherwise, but consistently pays more than the market requires.

Marketing Technology News: MarTech Interview With Fredrik Skantze, CEO and Co-founder of Funnel

With win-price optimization in place, this logic changes. The bidding model looks at how comparable impressions have cleared historically, how competitive the current supply path is and how urgently the campaign needs to spend. If those signals suggest an impression typically clears closer to $4 or $5, the bid reflects that reality and still wins. The audience doesn’t change, nor does the inventory. The alignment between the bid and the true clearing price, however, is transformed for the better, surfacing savings as incremental reach, longer flight time or additional flexibility.

Gaps like these are more common than many buyers realize, though they’re rarely the result of poor planning. More often, they stem from incomplete information. When a demand-side platform, or DSP, operates with a more limited set of signals, it compensates by bidding defensively. Without the appropriate context, the safest assumption is that an impression is valuable and worth paying a premium.

Models with broader visibility behave differently. When supply path dynamics, historical clearing prices, competition intensity and real-time pacing are taken into consideration, the bidding model develops a clearer sense of when aggressive bidding is warranted and when it isn’t. Two DSPs can bid on the same impression and arrive at very different prices, not because one values quality more, but because one has a more complete understanding of price.

There’s also a practical effect. Many buyers still spend time monitoring pacing, reconciling reports and making manual bid adjustments to keep campaigns aligned. As pricing becomes more accurate, much of that reactive work falls away – the bidding model recalibrates continuously, allowing buyers to focus more on strategy and less on maintenance.

Programmatic teams have spent years optimizing who they reach and how outcomes are measured. Pricing – despite shaping the cost and effectiveness of every impression – has received far less scrutiny. Win-price optimization brings that missing dimension back into focus.

For many advertisers, the inputs required to bid more accurately already exist; the opportunity now is to use them deliberately. Because in first-price auctions, overpaying isn’t a rounding error – it’s a strategy flaw. The next phase of programmatic efficiency won’t be defined by who can target more precisely, but by who can price most intelligently.

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Semrush Unveils Brand Visibility Framework at Adobe Summit

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Business Wire
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Semrush Unveils Brand Visibility Framework at Adobe Summit

Semrush Unveils Brand Visibility Framework at Adobe Summit

New research report series provides CMOs with a strategic framework and practical tools to orchestrate brand visibility across search and AI environments

Semrush , the leading brand visibility platform, unveiled a new strategic operating model for “Brand Visibility” during the Adobe Summit. The launch includes a two-part research report series: Brand Visibility Orchestration: How to execute on the Brand Visibility Operating model and Brand Visibility in the AI search era: A strategic framework for CMOs, designed to help marketing leaders transition from fragmented channel execution to a coordinated system of brand discovery.

This framework establishes Brand Visibility as the degree to which a brand is discoverable, authoritatively represented, and commercially actionable across both human- and machine-mediated discovery surfaces. A core component of the model is Agentic Search Optimization (ASO)—a new operational layer required to ensure a brand is selected, interpreted, and surfaced by autonomous AI agents as they increasingly evaluate brand relevance and authority.

Marketing Technology News: MarTech Interview With Fredrik Skantze, CEO and Co-founder of Funnel

The move to a formal operating model is a direct response to a fundamental shift in search behavior. With Gartner predicting a 25% drop in traditional search volume by 2026, brands are no longer discovered solely through users typing keywords in search bars, but through a complex ecosystem of AI-generated answers, chatbots, and agents.

“Most marketing organizations don’t struggle with defining strategy; they struggle with making it work in a world where discovery is now shaped by interconnected AI systems,” said Andrew Warden, Chief Marketing Officer at Semrush. “Visibility is no longer something you achieve through isolated tactics—it must be engineered through a repeatable operating model. This research provides the playbook for moving from managing channels to orchestrating outcomes.”

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The Shift to Brand Orchestration

The model responds to this tectonic shift in discovery by identifying a critical “Alignment Gap” in current marketing execution. Semrush research identified:

  • The Measurability Gap: 55.5% of teams fully aligned on search and AI optimization find their performance measurable and actionable, compared to only 15.5% of “somewhat aligned” teams and a further 18% who are siloed and disconnected.
  • The Process Gap: Only 22.6% of organizations have a truly unified process for topics, briefs, and goals across traditional search and AI-generated answers.
  • The Ownership Gap: A majority of enterprise teams (57.3%) describe themselves as either “somewhat aligned”, “siloed” or “completely disconnected” on brand visibility, meaning ownership is often unclear, and coordination depends on individuals rather than structure.

A Strategic Framework for the AI Era

The new research introduces the People and Process Maturity Matrix, a practical tool for CMOs to assess organizational readiness for AI-driven discovery. The matrix identifies four stages of maturity, helping leaders move from “Fragmented Operators” to “Brand Visibility Orchestrators”.

Key components of the Brand Visibility Operating Model include:

  • The Brand Orchestration Lifecycle: A repeatable four-stage system consisting of Foundation (narrative definition), Content (multi-format assets), Distribution (cross-surface activation), and Feedback (visibility signals).
  • The Brand Visibility Orchestrator: A newly defined organizational role focused on acting as the connective layer between strategy and execution, ensuring narratives remain consistent across all surfaces.
  • Unified Content Supply Chain: A process where topics and briefs are defined once and carried across search and AI environments to reinforce brand authority.

Proven Impact of Orchestration

Data from the reports highlight the performance gap between siloed and orchestrated teams. More than 55% of teams fully aligned on search and AI optimization say brand visibility is clearly measurable and actionable, compared to just 15.5% of partially aligned teams, while siloed and disconnected teams reported AI visibility very difficult to measure (23%) and not at all measurable (24.6%). In a recent internal application of these principles, Semrush nearly tripled its own AI share of voice from 13% to 32% within a single month.

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Fruition Achieves monday.com Advanced Delivery Partner Badge with monday Service and CRM Specialist Partner Recognition

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Fruition Achieves monday.com Advanced Delivery Partner Badge with monday Service and CRM Specialist Partner Recognition

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Fruition earns the monday Advanced Delivery Partner Badge and dual Specialist accreditations, cementing their position as a leading monday.com & AI consulting firm.

Fruition, a certified monday.com Platinum Partner based in Sydney, Australia, just picked up the Advanced Delivery Partner Badge. On top of that, they’ve been named Specialist Partners for both monday CRM and monday Service.

Fruition awarded monday.com Advanced Delivery Partner status with specialisations in monday CRM and monday Service implementation services across APJ

This official monday ADP Status isn’t easy to get. Only a handful of elite consulting firms make the cut with a strong track record. For example, these partners should offer tailored training for implementations, automations, and integrations.

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This latest recognition reflects how Fruition keeps expanding, not just across the Asia-Pacific, but also supporting AI and monday.com deployments in the United Kingdom and the United States. They have now locked their spot as one of the world’s most accomplished monday.com consultants.

To earn the monday.com Advanced Delivery Partner Badge, partners must surpass rigorous thresholds. That’d be across CSAT scores and completed project volume.

Fruition exceeded these benchmarks. They recorded 500+ finished projects and 300% Year-on-Year growth. With a flawless 5.0 CSAT score, the team completed over 9,000 billable hours in 2025.

The firm’s dedicated team of 35+ monday.com experts paved the way for the monday ADP Badge. They’ve served 700 clients globally across industries such as manufacturing, government, professional services, construction, and more.

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As an Advanced Delivery Partner and Specialist, Fruition gains access to priority enterprise leads and a dedicated partner manager. Other benefits include elevated commission tiers, exclusive marketing development funds, and a listing within the AI Matchmaker tool.

Alongside this, Fruition earned Specialist Partner designations for two fast-growing product lines:

  • monday CRM: AI workflows, end-to-end CRM configurations, and agentic sales pipeline.
  • monday Service: Employee self-service solutions, IT helpdesk, customer support portals, and HR service desk.

Fruition noted in a LinkedIn Post, “We’re loving what monday CRM is evolving into with its latest integrated AI workflows and agentic sales solutions.” The team was also proud to share their monday Service Specialist certification.

Josh Jebathilak, Fruition’s founder, reflected on the firm’s client philosophy, “We wanted to bring great customer experiences to software by guiding and advising our clients every step of the way. None of our clients is ever left uninformed or out of the loop.”

The hand-picked monday.com experts at Fruition can now offer exclusive monday.com consultation services like:

  • Enterprise-grade implementations with complex automations and custom integrations.
  • Full HR, service helpdesk, and customer support portal deployment built on monday Service.
  • AI-powered sales pipelines with agentic workflows and end-to-end CRM configurations tailored to your business.
  • First-preference lead-matching via AI Matchmaker, connecting clients to the right monday specialist.
  • Delivery across data migration, training, third-party integrations, managed services, and implementation.

On top of all that, Fruition got the APJ Rising Star 2025 Award at the monday.com Partner Summit 2026 in Prague. They were among 19 global partners recognised for outstanding client delivery and exceptional growth.

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Siteimprove Launches Advanced AEO Insights for AI Visibility to Help Enterprises Win in Answer Engines and Generative Search

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Siteimprove Launches Advanced AEO Insights for AI Visibility to Help Enterprises Win in Answer Engines and Generative Search

New AEO capabilities within the Siteimprove.ai Search solution enable enterprises to track AI citations, prompts, share of voice, and sentiment across answer engines in a single, unified platform

Siteimprove, a leader in agentic content intelligence, announced a major advancement in Answer Engine Optimization (AEO) with the launch of deeper AEO insights within Siteimprove.ai Search solution for AI Visibility. This new capability enables enterprise teams to measure, understand, and optimize how their brand appears across answer engines and generative search experiences.

As AI fundamentally reshapes the digital landscape, traditional search is no longer the sole gateway to discovery. According to IDC Research, 79% of buyers will use AI tools to navigate complex purchasing decisions, make informed decisions, and rely less on salespeople by 2028*. In this new environment, visibility is defined not by rankings alone, but by presence within AI-generated answers.

The Siteimprove.ai Search solution addresses this shift by ensuring enterprise content is structured, accurate, trustworthy, and accessible—the essential foundation for discoverability and performance across both traditional and AI-driven search.

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The new AEO capabilities provide customers with a comprehensive understanding of how their content performs across AI-driven platforms, including Google’s AI experiences and emerging answer engines. With this intelligence, organizations can improve visibility, increase engagement, enhance customer experiences, and drive measurable business outcomes.

“Answer engines are rapidly becoming the first point of engagement for buyers, and visibility in these AI channels is no longer optional,” said Nayaki Nayyar, CEO of Siteimprove. “With deeper AEO capabilities embedded into our Siteimprove.ai platform, we’re giving customers the clarity and control to shape how they are discovered, trusted, and chosen—across both AI-driven and traditional search environments.”

Within the AI Visibility dashboard, customers can now track and analyze key AEO performance metrics across answer engines, including:

  • AI citations and frequency of citations
  • Share of answers (share of voice)
  • Brand sentiment within AI-generated responses
  • Competitive positioning and insights
  • Revenue attribution tied to AI visibility
  • Content performance across AI-driven channels

Marketing Technology News: Programmatic Ad Platforms With Unique AdTech Features

The Siteimprove.ai Search solution now gives teams a holistic view of traditional SEO and AEO under a single enterprise experience for brand visibility in a dynamic search landscape.

Siteimprove is a recognized Representative Vendor in the 2026 Gartner® Market Guide for Answer Engine Optimization. According to Gartner, “Organizations need new approaches to measure visibility, including presence in AI-generated answers, citations, and conversational interfaces.”

This launch builds on the recent expansion of Siteimprove.ai, a unified agentic content intelligence platform with new conversational analytics agent and keyword intelligence agent, advancing the company’s broader vision to optimize the entire digital content lifecycle. From accessibility and search to content strategy and analytics, Siteimprove.ai delivers a single, agentic platform designed for enterprise scale.

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TwelveLabs Unveils the Next Era of Video Intelligence at NAB Show 2026

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TwelveLabs Unveils the Next Era of Video Intelligence at NAB Show 2026

TwelveLabs Unveils the Next Era of Video Intelligence at NAB Show 2026

From breakthrough models to creator tools and enterprise integrations, company brings AI-powered video understanding directly into production workflows

TwelveLabs, the video understanding company, today announced a series of product and ecosystem advancements at the NAB Show 2026. The releases showcase TwelveLabs’ evolution from a model and infrastructure provider to a full-stack platform, delivering end-to-end video intelligence.

With new capabilities and partnerships, TwelveLabs continues to drive the shift in how video is understood, accessed, and used at scale. Video now represents 90% of the world’s data, and TwelveLabs lets organizations and creators leverage this data, moving from raw footage to insight, and action faster than ever.

Introducing Pegasus 1.5: The Newest Breakthrough in Video Understanding

TwelveLabs is known for developing some of the most advanced video foundation models in the world, and the launch of its Pegasus 1.5 model represents a new category of video intelligence. It introduces Time-Based Metadata Extraction, becoming the first model ever that discovers temporal boundaries in video and extracts structured metadata to match a customer-defined schema. No re-indexing or manual annotation, and just a single API call. Users simply define what matters, and the model finds every instance with timestamps and structured outputs.

This means Pegasus 1.5 interprets video with a level of contextual understanding similar to how editors review footage, recognizing context, transitions, and key moments like when a brand appears or a key moment occurs.

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For media companies, decades of archival footage become instantly searchable, structured assets. For sports broadcasters, every play and event can be immediately identified. And for enterprises, Pegasus 1.5 replaces manual video-tagging workflows that previously required thousands of hours of review per year– all with unrivaled performance. In early testing, Pegasus 1.5 outperformed Gemini 2.5 Pro by 30% on aggregate segmentation quality benchmarks, and it is already in production with a major broadcast network.

Rodeo Brings AI Agents Directly into Video Production

TwelveLabs also introduced Rodeo, the company’s first application-layer product designed for creators . Rodeo acts as an AI-powered creative co-pilot, enabling them to find, edit, and assemble footage using natural language. It removes labor-intensive, technically demanding processes and constraints to free users to do what they do best: create.

Rodeo introduces AI agents directly into the workflow with no technical integration. These agents surface relevant clips, suggest edits, help assemble sequences and more, as directed by the user. This empowers creatives to move from raw footage to finished stories in minutes vs. hours or days.

Embedded in Industry Tools: AutoDesk Flow Capture

In addition to its own product innovation, TwelveLabs also adds its video intelligence capabilities into the tools professionals already use. TwelveLabs has partnered with Autodesk to enhance their digital dailies and review software, Autodesk Flow Capture, powered by PIX. From Hollywood blockbusters to indie breakouts, Flow Capture (formerly Moxion and PIX) is a secure, cloud-based tool that connects production and postproduction teams and workflows. By combining fragmented workflows with a single, connected solution, Flow Capture helps production teams move faster, stay aligned, and deliver high-quality content on time and on budget.

With the addition of TwelveLabs-powered Smart Search and Smart Actions, Flow Capture unlocks an entirely new level of efficiency. Teams can search video the way they think, instantly jumping to exact moments using natural language and surfacing the right content in seconds. At the same time, automated workflows tag, organize, and route media from the moment it’s uploaded, eliminating manual effort and streamlining collaboration at scale. The result: faster discovery, smarter workflows, and more time to focus on the creative.

“Creative teams shouldn’t have to hunt for their footage,” said Hugh Calveley, Sr. Director of Product Management at Autodesk. “With TwelveLabs powering Flow Capture’s Smart Search and Smart Actions, teams can search video the way they think and stay focused on what matters most: the story.”

“For years video has been the most valuable and least accessible form of data. TwelveLabs is changing this at every level,” said Jae Lee, CEO and co-founder of TwelveLabs. “With Pegasus 1.5, Rodeo, and our integrations with industry leaders, we’re transitioning from understanding video to operationalizing it at scale. This will transform how we use and experience what has become the most prolific medium on the planet.”

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TwelveLabs Launches Pegasus 1.5, Turning Raw Video Into Structured, Queryable Data at Scale

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TwelveLabs Launches Pegasus 1.5, Turning Raw Video Into Structured, Queryable Data at Scale

TwelveLabs Unveils the Next Era of Video Intelligence at NAB Show 2026

New video reasoning model extracts timestamped, structured metadata from up to two hours of video in a single API call – no indexing, no preprocessing – with superior segmentation quality over leading general-purpose models

TwelveLabs, the video intelligence company, today announced the general availability of Pegasus 1.5, its latest video reasoning model. Pegasus 1.5 introduces Time Based Metadata Extraction (TBM), a capability that lets users define a custom JSON schema and receive timestamped, structured metadata from video content up to two hours long – with no ingestion pipeline, no preprocessing, and no indexing step.

The release marks a shift in how organizations work with video data. Rather than relying on manual tagging, transcription, or frame-level analysis, Pegasus 1.5 reasons across entire videos to produce structured outputs that map directly to production workflows. Media companies, sports broadcasters, and content platforms can now convert raw footage into query-ready metadata in a single API call – transforming video from a storage cost into a queryable, monetizable data asset.

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What Pegasus 1.5 Delivers

Pegasus 1.5 processes video as a multidimensional volume – not a sequence of frames. Its Time Based Metadata Extraction capability accepts a user-defined JSON schema and returns structured, timestamped results across the full duration of a video, up to two hours.

Key capabilities include:

  • Time Based Metadata Extraction (TBM): Define a JSON schema describing the data you need – editorial segments, sports plays, brand appearances, speaker changes, shot types. Pegasus 1.5 returns timestamped, structured metadata that maps to your schema, discovering every instance across your entire video. No indexing, no preprocessing, no manual tagging.
  • On-the-fly processing: Point the model at any video – a URL, an uploaded file, or a base64 string – and get results. No ingestion pipeline. No waiting for an index to build. A developer can go from zero to structured video metadata in a single API call within minutes of getting an API key.
  • Multimodal Prompting: Provide a reference image of any entity – a person, product, or logo – and define what you are looking for. Pegasus 1.5 finds every moment that entity appears on screen, timestamped and structured. A sports broadcaster can locate every dunk from a specific player across a full season; a brand can measure product screen time across thousands of hours of content.
  • Long-form video support: Process videos up to two hours in a single pass, maintaining context and continuity across the full duration. Feature-length films, full-length sports broadcasts, multi-hour archive tapes, and conference recordings – analyzed in a single request.
  • Production-grade structured output: Deliver reliable, schema-compliant JSON at scale. In internal benchmarks on news content, leading general-purpose models exhibited high structured JSON failure rates. Pegasus 1.5 maintained consistent output fidelity across complex, multi-definition schemas.
  • Superior segmentation quality: Produce more accurate temporal boundaries and segment-level metadata. On aggregate segmentation quality benchmarks, Pegasus 1.5 outperforms Gemini 3 Pro by 13.1%, with boundary accuracy within approximately 350 milliseconds.

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Performance and Benchmarks

In head-to-head evaluations against leading general-purpose models, Pegasus 1.5 demonstrates measurable advantages in the two dimensions that matter most for production video workflows: segmentation quality and structured output reliability.

On aggregate segmentation quality – the accuracy of temporal boundaries and segment-level metadata – Pegasus 1.5 outperforms Gemini 3.1 Pro on aggregated segmentation by 13.1%. On structured JSON output reliability, particularly on complex content types like news programming, general-purpose models showed significantly higher failure rates in producing valid, schema-conformant JSON. Pegasus 1.5 was purpose-built for this workload and delivers consistent results where general-purpose models break down.

“Most AI models treat video as a sequence of images with audio attached. That approach works for demos, but it falls apart in production,” said Jae Lee, CEO and co-founder of TwelveLabs. “Pegasus 1.5 treats video as what it actually is – a rich, multidimensional data source. TBM gives enterprises a way to define exactly what they need from their video and get it back as structured, time-coded data. No preprocessing. No manual steps. No waiting for an index to build. That is the difference between a research prototype and production infrastructure. And once video data is structured, it becomes a first-class input for any AI agent or automated system – as easy to parse as text.”

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Conductor Launches Enterprise AgentStack to Power the Next Era of AI Visibility

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Business Wire
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Conductor Launches Enterprise AgentStack to Power the Next Era of AI Visibility

Conductor Logo

AI-native apps, developer experiences, and turnkey AEO agents powered by Conductor’s unified data engine enable enterprises and partners to build the next generation of agentic marketing systems

Conductor, the only end-to-end enterprise AEO platform, announced AgentStack, a new enterprise suite of native LLM apps, developer infrastructure, and turnkey agents, designed to help brands build, manage, and scale their visibility across AI-driven search experiences.

Brands are rapidly reallocating budget toward AEO to secure visibility. Those who fail to invest risk becoming invisible. Conductor’s AgentStack is everything brands need to deploy agentic workflows for AEO, at enterprise scale.

The way humans discover and evaluate products has fundamentally changed. People no longer need to evaluate content and make their own decision—AI does it for you, and people trust it. What used to require multiple searches, pages, and touchpoints now increasingly happens in a single interaction on LLM platforms like ChatGPT and Claude.

The shift to AI search has created a new discipline for brands: Answer Engine Optimization (AEO), the practice of ensuring your company is present, cited, and trusted in AI-generated answers. Brands are rapidly reallocating budget and resources toward AEO to secure visibility. Those who fail to invest risk becoming invisible.

AI is also reinventing how marketing technology is built and delivered. A new model is emerging: AI-powered agents that can be customized and deployed on demand. Instead of adapting workflows to pre-built software, teams and partners can build agentic systems and custom applications tailored to their exact needs.

That’s where Conductor’s AgentStack comes in—it’s everything brands need to deploy agentic workflows for AEO, at enterprise scale. Through Conductor’s APIs, MCP server, and LLM apps in ChatGPT, Claude, and Copilot, enterprises and partners can power agents and applications.

“Once you connect Conductor’s MCP to your AI platform or deploy our native connectors, you can build a custom version of our application in a day,” said Seth Besmertnik, Co-Founder and CEO of Conductor. “Reduce reporting time by 90% while improving output. 100x your ability to produce AI search-optimized content across emails, blog posts, and product pages.

“You’re only limited by your imagination. And even there, we help with use case libraries and skills guides.”

Teams can generate automated board-ready presentations grounded in real AI visibility data, track brand sentiment across AI platforms in real time, and identify which topics competitors are winning in AI-driven answers. From there, they can generate optimized content to close those gaps in minutes. Technical teams can monitor whether AI crawlers can access key pages to ensure discoverability and resolve issues before performance is impacted.

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In addition to enterprise brands, leading agencies and technology providers, including Optimizely, Razorfish, Havas, and IBM, are already building on AgentStack for their clients.

“As AI agents become central to how enterprise marketing gets done, access to reliable, unified intelligence becomes essential,” said Alexis Zamkow, Global Offering Lead, Marketing Transformation at IBM. “Conductor’s agent infrastructure provides the data foundation needed to build systems that adapt in real time across AI-driven experiences.”

Conductor has spent the last four years building the foundation for this new reality. Its unified data engine brings together the intent, content, and technical signals that determine discoverability across both AI systems and traditional search, all fully connected within a single software stack.

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“Agents are only as powerful as the intelligence behind them,” said Wei Zheng, Chief Product Officer at Conductor. “Conductor brings together the signals that determine discoverability across AI systems and search engines. That intelligence is what enables agents to automate meaningful marketing work.”

AgentStack also introduces Conductor’s first turnkey agents that combine proprietary AI search and content intelligence with a zero-configuration workflow, taking content teams from insight to published, optimized content in under three minutes, no prompt engineering or technical expertise required. Unlike other agent tools that force teams into complex interfaces, Conductor’s agents are the only turnkey solution built exclusively for AEO and content teams, delivered through a guided, point-and-click experience that makes enterprise AEO automation accessible from day one.

“We’re moving from a world where marketers optimize pages to one where systems optimize presence across AI experiences,” said Besmertnik. “Companies need an intelligence layer to power those systems. That’s the role Conductor is stepping into.”

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Infor and AWS Bring Agentic AI to Manufacturing at Enterprise Scale

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PRNewswire
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Infor and AWS Bring Agentic AI to Manufacturing at Enterprise Scale

New agents saving time and creating measurable value for early adopters

Infor, the Industry Cloud Complete company, and Amazon Web Services, Inc. (AWS) announced new and enhanced industry-specific AI agents built natively on AWS, enabling manufacturing and distribution enterprises to deploy industry-specific AI agents that reason, plan, and act across complex business workflows. The collaboration addresses discrete and process manufacturing’s AI scaling challenge by combining enterprise-grade infrastructure with industry-specific capabilities, enabling companies to rapidly develop and deploy AI agents that drive measurable improvements in efficiency, cost, and customer service.

“The conversation has changed from ‘where do we start with AI’ to ‘how fast can we scale it,” said Ozgur Tohumcu, General Manager of Automotive and Manufacturing at AWS. “Through our collaboration with Infor, manufacturers are moving from pilot to production faster than ever — deploying industry-specific agents that deliver operational advantages at enterprise scale.”

“Generic AI doesn’t work in manufacturing — you need agents that understand manufacturing-specific operational processes, bill of materials, supply chains, and shop floor realities,” said Rick Rider, Senior Vice President, Product Management, Infor. “AWS provides the enterprise infrastructure and AI horsepower, while we bring the deep industry-specific intelligence and context. The result is AI and agents built specifically for manufacturing industries that our customers can trust to run critical operations and deliver measurable financial impact.”

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Xpress Boats: Reducing Expedited Shipping Costs by 50%

Xpress Boats, a leading American manufacturer of all-aluminum fishing and pontoon boats based in Hot Springs, Arkansas, has achieved significant operational improvements following the implementation of Infor Velocity Suite. Facing mounting pressure to maintain its reputation for on-time delivery, Xpress Boats turned to Infor to identify and eliminate inefficiencies across its manufacturing and supply chain processes.

Using Infor Process Mining, the company uncovered critical bottlenecks in less than a week.  The areas they looked at first were Procure to Pay, Order to Cash and Demand to Build. Combined with automation tools for returns processing and vendor pricing, as well as Infor GenAI for intelligent document handling, Xpress Boats rapidly transformed key operations.

The results were immediate and measurable: a 98% improvement in process issue diagnosis speed, a 95% reduction in returns processing time, and a 50% reduction in expedited shipping costs. The results were immediate and measurable: a 98% improvement in process issue diagnosis speed, a 95% reduction in returns processing time, and a 50% reduction in expedited shipping costs.

Similar to the car industry, Xpress Boats changes models annually, at the same time in which vendors provide new product pricing. Infor agents apply pricing updates throughout the various levels of their bill of materials structure. This results in more accurate RPOs, which serve as the foundation of the retail pricing.

“Infor’s Industry AI Agents and GenAI Assistant have the potential to redefine how we operate. By streamlining processes, reducing manual effort, and delivering instant access to real-time insights, they can empower every level of our organization, from the shop floor to leadership, pushing us to work smarter,” said Jennifer Terry, Information Systems Manager for Xpress Boats. “What excites us most is not just the efficiency these tools unlock today, but the way they’re helping us think bigger and reimagine the future of our operations.”

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Among Infor’s complete collection of AI agents are those designed specifically to address the complexities of manufacturing operations. Built on AWS infrastructure designed for mission-critical workloads, Infor deploys agents across manufacturing’s most critical workflows with compliance controls and seamless scaling from pilot to production:

  • Profitable Project Management — Agents continuously compare baseline plans to real-time financials and performance metrics to protect margins, forecast revenue, and surface cost or schedule variances before they impact profitability.
  • On-Time Project Delivery Management — Agents monitor project risks, milestones, dependencies, and cross-project performance to detect delays early and coordinate interventions that keep delivery on schedule.
  • Process Mining & Operational Intelligence — Agents use process-mining-derived insights to automatically discover end-to-end workflows from event logs, surface bottlenecks and variant behaviors, and prioritize the highest-impact interventions so agents can close the loop with targeted remediation and continuous optimization.
  • Inventory Flow Management — Agents track warehouse activity, stock movements, and inbound and outbound orders to maintain real-time inventory visibility and ensure materials move efficiently through the supply chain.
  • Financial Operations Management — Agents connect contracts, billing, supplier invoices, and general ledger activity to automate financial oversight, streamline processes, and provide a unified view of financial performance.
  • Quality Management — Agents monitor inspections, non-conformances, and material disposition across orders and projects to quickly identify deviations and maintain consistent product and operational quality.

Customers can also build and deploy their own custom agents through Infor Agent Factory and in conjunction with Infor AI agents through orchestration, using Amazon Bedrock AgentCore Amazon Bedrock, and Amazon SageMaker, tailoring agents to their unique manufacturing needs.

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Knak Makes Enterprise Marketing Production Callable by AI Agents

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PRNewswire
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Knak Makes Enterprise Marketing Production Callable by AI Agents

New support for Model Context Protocol enables AI agents and orchestration layers to reach Knak directly, generating launch-ready campaign assets

Knak, the marketing production platform for enterprise teams, announces support for the Model Context Protocol (MCP), giving marketers access to marketing assets and campaigns within the AI workflows they already use and without the manual handoffs and bespoke development that can slow teams down.

The Knak MCP marks a significant expansion of how enterprise marketing teams can deploy marketing campaigns. Teams previously used Knak directly to build emails, landing pages and digital assets. Now, the production platform is accessible to AI assistants and works whether a human marketer or an AI agent is calling it, allowing AI outputs to reflect brand guidelines and assets that live within Knak. Enterprises such as OpenAI, Meta and Google are building AI-driven workflows that use Knak as the production layer in the middle.

Knak and OpenAI will present a session at Adobe Summit 2026 to demonstrate how enterprise marketing teams are already building AI-native production workflows with Knak. Knak Co-Founder and Chief Evangelist Brendan Farnand will join Jeff Canada, head of B2B Marketing Operations at OpenAI, for the Tuesday, April 21 session, “Inside OpenAI’s Marketing Stack: Applying AI to Scale Smarter.”

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The session will cover the real-world architecture OpenAI’s marketing operations team has built — connecting intake, orchestration and execution — and how Knak sits at the center of that production stack.

“The way enterprise marketing teams produce content is changing fast. AI is already a big part of production workflows, but enterprises need to consider if their production infrastructure can keep up with the increased demand,” said Pierce Ujjainwalla, Co-founder & CEO, Knak. “Knak’s MCP server is built to fix the pain points enterprise teams are facing by allowing orchestration layers to call Knak, and the production system takes it from there.”

The Production Layer in AI Marketing Workflows

Knak has long served as the production layer between brief and MAP, the system where on-brand emails, landing pages and digital assets get built, reviewed and made launch-ready. With MCP support, that same production infrastructure becomes accessible to any AI orchestration layer, enabling structured content inputs to be passed into Knak and marketing assets to be returned, ready for review and launch.

For teams already building AI-driven marketing workflows, this MCP announcement formalizes the architecture that enhances marketers’ bandwidth but doesn’t replace them.

Marketing Operations teams can architect how AI gets deployed inside Knak by setting the brand guardrails, access controls and governance rules that ensure every asset that comes out is ready to ship.

“We’re using AI to triage requests, reduce friction, and move faster — but AI alone doesn’t get you to launch-ready,” said Jeff Canada, Marketing Operations Lead, OpenAI. “You still need a production layer that takes what the AI hands off and turns it into something that can actually ship. That’s where Knak sits in our stack, and it’s what makes the whole workflow actually close.”

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Current and future availability

MCP support is available to Knak customers in Alpha. Current capabilities include email generation through AI agents using Knak’s existing template library.

AI agents including ChatGPT and Claude can now connect to Knak through the MCP server to generate emails programmatically using existing templates. Brand compliance guardrails and expanded platform functionality are planned for upcoming releases.

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BigBlueBam Public Beta Brings AI-Native Architecture to Open-Source Project Management, CRM, and Knowledge Work

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MTS Staff Writer
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BigBlueBam Public Beta Brings AI-Native Architecture to Open-Source Project Management, CRM, and Knowledge Work

Exposes 340 MCP tools across 20 applications, a surface comparable to Azure MCP Server, aimed at the daily work of knowledge workers, released under MIT license

When Anthropic released the Model Context Protocol in late 2024, the cloud platforms responded at scale. Microsoft’s Azure MCP Server now exposes 276 tools for managing Azure infrastructure. AWS has shipped a sprawling suite for cloud operations. Eddie Offermann, the solo developer behind the BigBlueBam open-source work operating system, did something different: he took the protocol as seriously as Microsoft did, and pointed it at the work itself.

The thing that actually matters about MCP is not that it lets your chatbot call tools. It is that it provides a unified execution substrate for agents.”

— Eddie Offermann

BigBlueBam, entering public beta this month, ships with an MCP server exposing 340 tools spanning all 20 applications in the suite. Every project-management action in Bam, every message operation in Banter, every knowledge-base query in Beacon, every invoice action in Bill, every CRM update in Bond, and every automation in Bolt is addressable through the MCP surface. It is the largest MCP-native work suite shipped to date, at Microsoft-comparable scale, built by a single developer rather than a corporate engineering org, and MIT-licensed rather than tied to a commercial cloud.

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“MCP is the interesting standards story in AI infrastructure right now, and most vendors outside the cloud platforms are treating it as a novelty,” Offermann said. “The thing that actually matters about MCP is not that it lets your chatbot call tools. It is that it provides a unified execution substrate for agents. If you take that seriously, it changes how you architect everything downstream.”

A Different Category of Deployment

The large first-party MCP servers that exist today, including Azure MCP, AWS’s MCP suite, Google Cloud’s, and GitHub’s, are management planes. They let developers and SREs provision resources, query metrics, run diagnostics, and deploy services. Their user is an operator managing infrastructure.

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BigBlueBam’s MCP server operates a layer above, on the applications knowledge workers use for their actual jobs. Creating a task in Bam is not managing a task service; it is the work. Writing in Beacon is not configuring a knowledge base; it is the knowledge. Sending a message in Banter is not operating a messaging service; it is the communication. The user is a human doing their daily job, and MCP is what lets an agent act alongside them inside the work, not through a dashboard behind it.

The Substrate Argument

BigBlueBam’s MCP server is not a thin wrapper over the product’s existing REST API. It is the product’s primary agent surface. Permissions are enforced through the same role-based access-control system that governs human users. Every MCP tool call generates an audit log entry. Every tool result is scoped to the authenticated agent’s visibility.

That design has a second, less obvious consequence: it unifies human-authored automation with agent action.

Bolt, BigBlueBam’s workflow automation engine, compiles visual rules (“when a Bam ticket is assigned to priority-high, notify the #incidents channel in Banter and create a Beacon incident document”) down to chained MCP calls. A human-authored automation and an AI agent’s action therefore run through the same execution path, under the same permission system, producing the same audit trail.

“Once MCP is the execution layer, the distinction between ‘the AI did it’ and ‘the automation did it’ and ‘a person clicked a button’ collapses into a single record of what happened, who caused it, and whether they were authorized,” Offermann said. “That is what compliance actually looks like when it has been designed in from the start.”

Scale of the Deployment

BigBlueBam’s 340-tool MCP registry breaks down approximately as follows (counts approximate, growing):

– Project and task management tools (Bam): ~45
– Team communication tools (Banter): ~35
– Knowledge base and document retrieval tools (Beacon, Brief): ~45
– Automation and workflow tools (Bolt): ~25
– CRM and contact management tools (Bond, Blast): ~35
– Billing, invoicing, and time tracking tools (Bill, Bank): ~25
– Scheduling, availability, and HR tools (Book, Balance, Belong): ~35
– Dashboard, reporting, and analytics tools (Bench, Bridge): ~20
– File, asset, and canvas tools (Bin, Board, Badge): ~25
– Forms, surveys, OKRs, and cross-cutting tools (Blank, Bearing): ~20
– Helpdesk and other suite tools: ~30

Every tool is documented with JSON Schema for both inputs and outputs. Every tool’s permissions are declared in the same RBAC table that governs human role grants.

Why the Architecture Is Hard to Copy

The unified MCP surface is only possible because BigBlueBam is built on a single PostgreSQL schema shared across all 20 applications. Most enterprise SaaS vendors grew through acquisition and hold customer data in separate databases per product. Retrofitting an MCP-style unified tool surface across those databases would require either invasive schema migrations (breaking paying customers) or a translation layer that would defeat the atomic-transaction guarantees that make the architecture defensible.

“Incumbent vendors can ship an MCP demo,” Offermann said. “What they cannot ship is an MCP substrate, because they don’t have a unified data model underneath it. That is the competitive dynamic that matters for the next five years.”

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

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