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LivePerson Announces Event-driven Orchestration Partnership with Coral Active

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LivePerson Announces Event-driven Orchestration Partnership with Coral Active

LivePerson, a leading provider of predictable conversational AI, announced the launch of LivePerson Sync in partnership with Coral Active, a leader in enterprise contact center integrations. LivePerson Sync enables seamless integration with systems like Salesforce, Microsoft, and ServiceNow, bringing CRM data and workflows directly into the live agent workspace.

“LivePerson Sync is the answer brands have been looking for to improve agent productivity and experience by providing agents with the customer information they need in a single view,” said John Sabino, LivePerson CEO. “By further connecting our agent workspace with critical information from across systems, we’re removing the friction of disconnected systems.”

LivePerson Sync is partnering with Coral Active, a company founded in 2011 to improve live agent experiences by simplifying agent workspaces through integrations with contact centers, CRMs, and legacy applications.

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Bridging the Tech Stack Divide

As brands grapple with increasingly complex technology stacks, live agents often lose critical time toggling between disconnected systems. LivePerson Sync addresses this challenge by providing a true single pane of glass experience. It allows brands to synchronize LivePerson Conversational Cloud with CRM, CCaaS, or browser-based applications in real-time.

Key Capabilities of LivePerson Sync

LivePerson Sync treats every interaction as a real-time event that can trigger automated workflows across multiple platforms. It offers four primary deployment models:

  • CRM in LivePerson: Secure bidirectional customer profile data sync and lead/ticket management directly within the LivePerson workspace.
  • LivePerson in CRM: A native chat capability embedded directly inside the enterprise’s preferred CRM desktop, providing a seamless upgrade for legacy connectors.
  • Context Synchronization: Context-aware synchronization that automatically triggers CRM records on secondary monitors as agents switch between conversations.
  • AI Enrichment & Automation: AI-driven actions that automatically ingest transcripts, generate summaries, and update customer records upon conversation completion.

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Enterprise-Grade Flexibility and Scale

Unlike vendor-locked alternatives, LivePerson Conversational Cloud is an open conversational AI platform that connects channels, systems, and the AI model of choice for true agility and business value across conversations. LivePerson Sync advances this vision through event-driven orchestration that bridges the gap between disconnected tech stacks, empowering brands to unify their data and agent workflows into a single, cohesive ecosystem.

LivePerson Sync is available immediately for brands looking to modernize their agent experience and reduce handle times through intelligent automation.

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8×8 Expands General Availability of 8×8 Engage

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8x8 Expands General Availability of 8x8 Engage

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Now Available to All Channel Partners and Customers Globally; Strong Adoption Momentum Validates Demand for Empowering Frontline and Expert Teams Across the Organization

As customer experience continues to expand beyond traditional service departments, organizations need a scalable way to empower every customer-facing team by giving them the flexibility and autonomy to engage on their terms, without sacrificing visibility or accountability. In response, 8×8, Inc. , a leading global business communications platform provider, announced the general availability of 8×8 Engage, now available globally across all of 8×8’s channels.

Customer conversations no longer happen in one place. They happen in retail stores, on service floors, in healthcare facilities, and across distributed teams. Each of these interactions is an opportunity to build loyalty, resolve issues faster, and drive better outcomes.

“The way organizations deliver customer experience has fundamentally changed,” said Hunter Middleton, Chief Product Officer at 8×8, Inc. “They need every customer-facing team to engage with consistency, intelligence, and accountability. To do this, we’re bringing advanced customer engagement tools out of the contact center and making them available and easily accessible to front line teams across the organization. With 8×8 Engage now generally available globally – including through our channel partners – we’re making that possible at enterprise scale, on the same unified platform our customers already rely on.”

Strong adoption momentum

Growth since launch tells a clear story:

  • The number of customers adopting Engage has exceeded 150% growth, compared to same period last year
  • Daily active new customers have increased nearly 5X year over year
  • Daily active users have grown more than 4X year-over-year

This momentum reflects a clear enterprise need: as customer experience expands beyond service departments, organizations require a scalable way to bring visibility and accountability to every customer-facing interaction, wherever it happens.

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“We chose 8×8 Engage to give our teams greater flexibility across sites, and it’s changed how we manage customer interactions,” said Jake Blowers, Head of Projects and Innovation at Motus Commercials. “Our colleagues can now take calls wherever they are – whether at their desk, in the workshop, or on the move – which has significantly reduced missed opportunities. The result is a more responsive customer experience and greater operational agility across our business.”

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Built for distributed, mobile, and expert teams

Built natively on the 8×8 Platform for CX, 8×8 Engage delivers:

  • Mobile-ready engagement for teams working across dynamic environments
  • CRM-integrated customer context for more informed, lower-friction interactions
  • AI-generated summaries and sentiment analysis to improve context, accelerate resolution, and support stronger CSAT outcomes
  • Intelligent routing and queue management with real-time workload visibility
  • Unified governance and analytics, including end-to-end visibility into customer journeys across all customer-facing teams

“Customer engagement is increasingly happening across all parts of the enterprise,” said Zeus Kerravala, Founder and Principal Analyst at ZK Research. “Enterprises are looking for flexible engagement models that give frontline and expert teams visibility and control without adding unnecessary complexity. This shift reflects a broader evolution in how organizations operationalize customer experience.”

8×8 Engage is now generally available globally and ready to deploy across the organization. Channel partners can immediately offer 8×8 Engage as part of the 8×8 Platform for CX to help customers eliminate communication silos and move faster with less complexity.

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Beyond Dubbing: Vozo AI Launches Visual Translate for Complete Video Localization

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Beyond Dubbing: Vozo AI Launches Visual Translate for Complete Video Localization

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Translate on-screen text in videos without recreating the original visuals—
bringing fully localized video experiences to global audiences.

Vozo AI, an AI-powered video localization platform, announced the beta launch of Visual Translate, a generative AI capability that automatically localizes on‑screen text while maintaining the original design, layout and animation. This release addresses a long-standing gap in AI video translation: while subtitles and dubbing translate what viewers hear, most tools still fail to translate the text viewers see within the video itself.

Vozo Visual Translate localizes on-screen text in videos, without recreating visuals.

In many videos—such as training materials, product demos, and explainer content—key information appears directly within visuals, including slide text, labels, callouts, diagrams, and charts. When that content remains in the original language, international viewers may understand the narration but still miss critical context.

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Visual Translate closes this gap by automatically:

• Working directly from the video itself—no original project files required

• Detecting and translating on-screen text within videos

• Preserving the original layout, style, and animations

• Allowing text, fonts, colors, and positions to be edited and customized

The result is a fully localized video where both narration and visuals are translated coherently, giving international audiences the same clarity as native viewers.

During the alpha phase, a multinational manufacturing company used Visual Translate to localize slide-based training videos for global teams and distributor networks. By translating visual content directly within the video into nine languages, rather than manually editing, the company reduced localization time by over 96%—turning a two-day process into just 30 minutes.

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By automating what was once a highly manual process, Visual Translate marks a shift in AI video translation—moving beyond basic dubbing and subtitles toward truly complete, scalable localization that preserves how meaning is conveyed visually. The capability is particularly valuable for education, corporate training, and marketing, where critical information often appears in step-by-step instructions, labels, and other visual elements rather than narration alone.

“Most video translation tools focus on speech,” said Dr. CY Zhou, Founder and CEO of Vozo AI. “But in many videos, meaning is conveyed visually—through slides, diagrams, and on-screen text. Visual Translate fills that missing layer, enabling truly complete video localization and allowing ideas and knowledge to move across languages with far greater clarity and impact.”

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Kamelia Ayrafar Joins Integral Ad Science (IAS) Board of Directors

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Kamelia Ayrafar Joins Integral Ad Science (IAS) Board of Directors

Netflix Head of AI, Members and former Google AI and engineering leader brings deep experience scaling AI to IAS

Optable and PubMatic Partner to Advance Agentic Audience Discovery and Real-Time Activation Across PubMatic AgenticOS

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Optable and PubMatic Partner to Advance Agentic Audience Discovery and Real-Time Activation Across PubMatic AgenticOS

Integration enables buyers to discover, build, and activate privacy-safe audience signals across premium publishers using agentic AI

Optable, the Agentic Audience Platform, announced a partnership with PubMatic , the leading AI-powered ad tech company delivering digital advertising performance, to bring privacy-safe, publisher-controlled first party audience data directly into end-to-end agentic media buying workflows. Through the partnership, Optable’s Audience Agent is integrated into AgenticOS, enabling buyers to autonomously discover, build, and activate high-value audience signals sourced from premium publishers and data owners in a privacy-safe way.

The integration gives buyers using PubMatic AgenticOS direct access to Optable’s agent-driven audience planning capabilities, allowing them to tap into rich first-party data without exposing or transferring underlying data. Advertisers can analyze publisher first-party data signals, including identity, contextual, and audience, and activate custom data targeted campaigns more efficiently across multiple publishers.

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“This partnership ensures that publisher first-party data doesn’t just inform planning — it creates a layer of audience intelligence that directly powers activation and programmatic buying decisions,” said Vlad Stesin, CEO of Optable. “By integrating our Audience Agent into PubMatic AgenticOS, we are enabling buyers and sellers to collaborate securely, uncover new audience value, and activate it faster without compromising privacy, data or control.”

“As agentic workflows continue to evolve, interoperability and trust are critical,” said Kyle Dozeman, Chief Revenue Officer, Americas at PubMatic. “AgenticOS was built to connect intelligence to execution. Integrating Optable’s audience capabilities allows AI agents to discover high-value, custom audiences and then move seamlessly to RTB activation across premium supply.”

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Optable’s Agentic Audience Platform enables publishers and data owners to harness, enrich, and activate their first-party data while maintaining full control. Sellers working with Optable can use the Audience Agent to seamlessly surface high-value audiences to buyers on PubMatic and tap into growing agentic demand from advertisers. Activation executes directly through PubMatic Activate, a direct-to-supply media bidder, meaning publishers and partners benefit from agentic audience workflows without needing to adopt new protocols or modify existing infrastructure.

By simplifying audience collaboration and activation, the partnership helps publishers increase addressability, improve yield, and respond to demand faster without adding operational complexity. For advertisers, it provides more direct access to premium audience signals across PubMatic’s marketplace, enabling more precise audience analysis, faster campaign execution, and improved outcomes.

By integrating PubMatic AgenticOS with Optable’s identity-first, privacy-safe AI, buyers gain better signals and more efficient activation while complementing AgenticOS’s execution capabilities with specialized audience intelligence. The partnership also represents an early example of the Advertising Context Protocol (AdCP) in action, demonstrating how agent-to-agent workflows can enable secure, interoperable collaboration across the advertising ecosystem, and how privacy-safe audience intelligence can directly power real-time programmatic execution on the open web, without relying on closed platforms or centralized data systems.

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Digi International Unveils AI-Powered One Digi AI Discovery Engine to Transform B2B Solution Search

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Digi International Unveils AI-Powered One Digi AI Discovery Engine to Transform B2B Solution Search

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New interface uses natural language AI for cross-platform search to surface the best Digi, Opengear, Particle, and SmartSense solutions

WhatsDash Rebrands as StatNexa, Launching a Unified Marketing Analytics Platform for Agencies

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WhatsDash Rebrands as StatNexa, Launching a Unified Marketing Analytics Platform for Agencies

WhatsDash officially rebranded to StatNexa, introducing enhanced marketing analytics, advanced reporting dashboards, integrations, and client reporting tools.

WhatsDash, a marketing analytics and reporting platform used by digital marketers and agencies to monitor campaign performance, has officially announced its rebranding to StatNexa. The rebrand represents the company’s next stage of growth as it expands its capabilities to help organizations better manage and analyze marketing data.

The launch of StatNexa represents our commitment to building a more powerful and scalable marketing analytics platform for agencies and data-driven teams.”

— StatNexa Team

The platform will now operate under the new name StatNexa, reflecting a stronger focus on advanced marketing analytics, automated reporting, and centralized performance tracking. The company confirmed that existing users will continue to have uninterrupted access to the platform as the brand transition takes place.

The transition from WhatsDash to StatNexa marks a strategic step toward building a more comprehensive marketing intelligence platform designed for modern businesses, marketing teams, and digital agencies. As marketing channels continue to expand, many organizations face challenges managing data from multiple platforms. StatNexa aims to address this challenge by providing a unified dashboard where users can collect, visualize, and analyze marketing data from different sources.

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StatNexa enables users to transform complex marketing data into simplified dashboards and automated reports, allowing teams to better understand campaign performance and make informed decisions.

The platform offers several features designed to support marketing analytics and reporting workflows, including:

• Advanced marketing reporting dashboards
• Integration with more than 90 marketing and analytics platforms
• Automated report generation and performance scorecards
• Customizable client-specific dashboards
• Template-based reports for faster reporting workflows
• Marketing performance tracking and OKR monitoring
• Real-time data visualization across campaigns

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These features help marketing professionals centralize their reporting process and reduce the time required to manually compile marketing data from different tools.

According to the company, the rebranding reflects a broader vision to expand the platform’s capabilities and strengthen its position as a marketing analytics solution for agencies and businesses managing multi-channel campaigns.

The company also confirmed that the transition to the StatNexa brand does not affect current platform functionality, user accounts, or stored data. Existing customers can continue using the platform without disruption while benefiting from ongoing improvements and updates.

With the growing demand for data-driven marketing decisions, platforms that provide centralized analytics and reporting capabilities are becoming increasingly important for marketing teams worldwide. StatNexa aims to support this need by providing tools that simplify performance monitoring and reporting processes.

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The Impact of Visual Media on Brand Authenticity in Digital Marketing Strategy by Actual SEO Media, Inc.

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High-quality visual media serves as the primary driver of brand credibility, shaping consumer perceptions of professionalism and reliability.

First impressions in the digital marketplace are often formed within seconds. Consumers frequently encounter brands through websites, advertisements, or social media posts before any direct interaction occurs. Visual media, therefore, become a powerful factor in shaping perception. Design quality, imagery, layout, and consistency can strongly influence whether an audience considers a brand trustworthy or questionable. Well-structured visual content signals professionalism, while poorly designed graphics can immediately weaken consumer confidence. In an increasingly competitive online environment, such as Actual SEO Media, Inc., visual presentation plays a central role in establishing credibility.
Marketing research consistently shows that audiences rely heavily on visual cues when evaluating unfamiliar brands. Colors, typography, and layout can influence emotional responses and help determine whether viewers continue exploring a website or leave quickly. As a result, businesses that prioritize visual quality often make a stronger impression and maintain higher engagement. Visual media is therefore not simply decorative—it functions as a key communication tool that shapes how consumers interpret a brand’s reliability and expertise.

The Role of Visual Design in Establishing First Impressions
Website design is often the first point of contact between a brand and its audience. Visitors quickly evaluate whether the site appears organized, modern, and trustworthy. Clean layouts, clear navigation, and consistent visual identity communicate professionalism. When these elements work together effectively, they help visitors feel confident that the company behind the site is credible and attentive to detail.
Visual consistency across digital platforms reinforces this credibility. When logos, colors, and graphic styles remain uniform on websites, advertisements, and social media pages, consumers recognize a cohesive brand identity. This consistency signals stability and reliability, which can encourage potential customers to spend more time engaging with content or exploring products and services.
High-quality photography, professional graphics, and carefully chosen typography also contribute to a polished appearance. When images are clear and relevant to the message, they help audiences quickly understand what a company represents. Effective visual design, therefore, serves as a silent introduction, allowing consumers to interpret the brand’s values and professionalism without reading extensive text.
In contrast, outdated designs, cluttered layouts, or inconsistent visuals can leave a negative impression. Even if the products or services offered are high quality, poor presentation may cause viewers to question the brand’s legitimacy. For many online users, the visual environment strongly influences whether they perceive a company as credible enough to consider further.

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How Visual Media Strengthens Brand Identity and Trust
Beyond the first impression, visual media continues to shape consumer perception throughout the customer journey. Branding elements such as color schemes, icons, and graphic styles create visual associations that help audiences recognize and remember a company. When these elements appear consistently across marketing channels, they reinforce familiarity and trust.
Visual storytelling also plays an important role in communicating brand values. Images, videos, and design elements can illustrate a company’s mission, expertise, and industry focus. For example, professional visuals that highlight automotive services or dealership marketing strategies can help audiences understand a brand’s specialization without lengthy explanations.
Consistent visual branding helps companies maintain credibility across different marketing platforms. Social media graphics, website banners, and advertising visuals all contribute to a unified message. When audiences repeatedly encounter the same visual identity, they develop a stronger sense of reliability and brand recognition.
Organizations that manage digital marketing strategies often rely on coordinated visual media to support brand identity. For instance, Actual SEO Media, Inc. provides web design and development, search engine optimization, pay-per-click advertising, brand management, article writing, local SEO strategies, and automotive dealership SEO while offering free consultations and maintaining a full in-house team to support integrated digital campaigns. Visual consistency across these services helps reinforce brand credibility and supports long-term recognition in competitive markets.

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The Impact of Poor Visuals on Brand Credibility
Poorly executed graphics can rapidly damage a brand’s reputation. Low-resolution images and cluttered layouts suggest a lack of professionalism, leading first-time consumers to doubt a company’s reliability.
Consistency is equally vital. When logos, colors, and styles fluctuate across platforms, it confuses the audience and weakens brand recognition. A fragmented visual identity prevents the development of long-term consumer trust.
Furthermore, outdated website designs act as a red flag. Modern users equate current design trends with business relevance and technological competence; a neglected site often results in high bounce rates. Finally, visual clutter—such as excessive animations or crowded layouts—hinders information processing.
In digital marketing, clean and purposeful design is not just an aesthetic choice; it is a fundamental requirement for maintaining organizational clarity and professional authority.

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Over The Top SEO Launches the Industry’s First Full-Scale Generative Engine Optimization Division

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Over The Top SEO Launches the Industry's First Full-Scale Generative Engine Optimization Division

The decade-long SEO leader deploys a fully operational GEO infrastructure — with 450+ optimized pages already indexed — while competitors are still in the announcement phase

Over The Top SEO (OTT), the award-winning digital marketing agency led by CEO and Founder Guy Sheetrit, announced the launch of its dedicated Generative Engine Optimization (GEO) division. The division is the first full-scale GEO operation deployed by a major SEO agency, arriving at a moment when the search industry is undergoing its most significant transformation since the introduction of Google PageRank.

GEO is the practice of ensuring that brands are cited, recommended, and accurately represented when artificial intelligence systems generate answers for users. Unlike traditional SEO, which focuses on ranking web pages in a list of search results, GEO addresses a fundamentally different challenge: getting named inside the AI-generated answer itself.

The shift is already massive. ChatGPT now holds approximately 60 percent of the AI search market and processes more than 2.5 billion prompts every day. Google’s AI Overviews reach 1.5 billion users monthly. Perplexity, Claude, and Microsoft Copilot are growing rapidly behind them. Roughly a third of ChatGPT’s daily prompts are commercial queries — people asking which products to buy, which companies to hire, and which solutions to trust.

When AI generates those answers, it doesn’t present a list of websites. It names specific brands. If a company isn’t being cited in those responses, it is invisible to a growing — and soon dominant — segment of its market.

“The companies that will dominate the next decade aren’t just ranking on Google. They’re training AI to recommend them. We’ve been the number one SEO company for over a decade. Now we’re making sure our clients are number one in the AI search era too. We didn’t write a blog post about GEO — we built an entire division and deployed it before anyone else caught up.”

— Guy Sheetrit, CEO & Founder, Over The Top SEO

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What OTT Has Built — and Already Deployed

While several agencies have recently announced GEO as an offering — in some cases rebranding existing content marketing services — OTT’s approach is different in a critical respect: it is already operational. The division has been building and deploying since late 2025, and its infrastructure is live and producing measurable results.

The GEO division is organized around six core capabilities:

AI Citation Architecture. Content structured so AI models cite and recommend brands by name, with citation pattern analysis across ChatGPT, Perplexity, Google AI Overviews, Claude, and emerging platforms.

Full Schema Markup Deployment. Seven types of structured data — Article, FAQ, Organization, LocalBusiness, Breadcrumb, WebSite, and Person — implemented site-wide across every client property.

llms.txt Protocol Adoption. Among the first agencies to implement the llms.txt standard, a machine-readable file enabling large language models to discover and accurately index brand information. Fewer than one percent of websites have adopted this protocol.

AI-Native Content Pipeline. A proprietary production system creating assets engineered from the ground up for AI visibility — including AI-generated video, featured imagery, FAQ schema, deep internal linking, and full E-E-A-T optimization.

Topical Authority Clusters. Structured clusters of 50 to 100 interconnected, deeply researched assets per client vertical, covering the full range of questions an AI model might field about their industry.

AI Crawler Optimization. Every client property configured to welcome GPTBot, Google-Extended, ClaudeBot, and PerplexityBot — ensuring content enters the training and retrieval data that shapes AI-generated responses.

To date, OTT’s GEO division has deployed more than 450 AI-optimized pages, all indexed by Google and structured for AI citation. The division monitors brand mentions in real time across all major AI platforms.

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Gradial Launches GEO Agent With Built-In Execution to Help Brands Win in AI Search

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Gradial Launches GEO Agent With Built-In Execution to Help Brands Win in AI Search

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New capability identifies visibility gaps in AI search and automatically implements fixes across website content

Gradial, the system of work for enterprise marketing, announced the launch of Gradial GEO, a new capability that helps marketing teams improve visibility in AI search engines. Gradial GEO identifies gaps in how a brand appears in generative search results and executes the changes needed to improve visibility automatically.

The Problem: GEO Without Execution Is Just a Report

As AI-powered search tools like ChatGPT, Gemini, and Perplexity increasingly shape how buyers discover products and services, Generative Engine Optimization (GEO), the practice of ensuring brands appear in AI-generated answers and recommendations, has become a top priority for CMOs in 2026.

However, most GEO tools today are visibility tools: they show you where you stand but leave your marketing team responsible for acting on the recommendations. Those recommendations feed backlogs. Backlogs slow execution. And because AI models re-crawl constantly and evolve on a weekly basis, brands cannot afford to treat GEO as a quarterly audit.

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GEO is a continuous operation. It requires continuous execution.

The Solution: Gradial Closes the Execution Loop

Gradial GEO analyzes how a brand appears across leading AI search engines, identifies visibility gaps across website content, and executes the recommended fixes automatically, directly in the CMS, without creating new backlog for marketing teams.

Because Gradial already executes marketing work across enterprise web stacks, those fixes don’t sit in a report. They get implemented immediately. And because AI models evolve constantly, Gradial agents continuously update pages and content so brands can maintain and improve their AI search visibility in real time.

With Gradial GEO, marketing teams can:

  • Analyze how their brand appears across AI search engines including ChatGPT, Gemini, and Perplexity
  • Identify where competitors are cited and recommended instead
  • Detect content gaps on their website that reduce AI visibility
  • Execute fixes automatically (new pages, content updates, and structural improvements) directly in the CMS
  • Simulate how content will be presented by LLMs before it goes live, so teams can optimize ahead of publish, not after

The result is an always-on GEO optimization loop where insights and execution run continuously as AI models evolve, with brand governance and QA built into every change.

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What This Means

“AI search is fundamentally changing how buyers discover brands. Marketing teams need more than insights about where they’re missing visibility. They need a system that can constantly execute the changes required to improve it. Gradial GEO closes that execution loop.”

— Anish Chadalavada, Co-founder and Chief Growth Officer, Gradial

Gradial’s belief: your website is the source of truth that AI models reference. Brands that build a tight execution loop for both human and machine audiences will win the next decade of discovery. Brands that treat GEO as a reporting exercise will get left behind.

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ExpertFile Expands Its Platform to Help Marketing Teams Strengthen Expert Visibility in AI-Driven Search

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ExpertFile Expands Its Platform to Help Marketing Teams Strengthen Expert Visibility in AI-Driven Search

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Latest advancements now deliver the most advanced system for publishing trusted expert research and thought leadership content

With the launch of ExpertFile Studio™, ExpertFile Search™, and ExpertFile SignalsAI™, the company gives marketing teams a more complete system for publishing trusted expert content, improving discoverability, and strengthening AI visibility

As AI systems like ChatGPT, Google AI Overviews, and Claude increasingly shape how audiences evaluate sources and decide what information to trust, organizations need more than static directories, scattered bios, and unstructured web pages. They need expert content that is structured, governed, and legible enough to be surfaced, cited, and recommended in AI-mediated environments. ExpertFile announced the launch of ExpertFile Studio™, while expanding its broader platform to help organizations create, govern, distribute, and optimize expert content in ways that make their expertise more recommendable, more citable, and more ready for selection across search, media, and AI-driven discovery.

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The ExpertFile platform now brings together three core capabilities designed to help knowledge-based organizations strengthen the signals that increasingly determine who gets surfaced, trusted, and selected in the AI era:

ExpertFile Studio™ for creating and governing expert-led content experiences—including profiles, topic hubs, speaker bureaus, research showcases, and expert answers—using no-code tools that improve structured clarity and decision-enabling content while helping communications teams move faster with quality, consistency, accessibility, and oversight.

ExpertFile Search™ for extending authority, ecosystem presence, and third-party discovery through ExpertFile’s global expert search engine and mobile apps, helping journalists, producers, and event organizers find credible sources across more than 50,000 topics and expanding client reach well beyond their own websites.

ExpertFile SignalsAI™ for surfacing emerging opportunities, tracking expert visibility across media, search, and AI-driven environments, and providing the reporting and analysis organizations need to strengthen positioning, guide editorial priorities, and respond faster to developing trends.

“Organizations do not want competitors and algorithms defining how their expertise is represented in AI search. ExpertFile gives communications teams the tools to structure, govern, and activate expertise that makes them the obvious and trusted choice.”

— Robert Carter, VP Product & Co-Founder, ExpertFile

The launch comes at a time when communications and marketing leaders are under growing pressure not just to improve visibility, but to ensure their organizations are represented as credible, low-risk, decision-ready sources in environments where AI-generated answers often shape first impressions. In this new landscape, success depends on publishing expertise in structured, attributed, and consistently governed formats that help both people and machines assess authority, reduce uncertainty, and confidently recommend the right expert or institution.

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What’s New Across the ExpertFile Platform

ExpertFile Studio™

• No-code publishing for expert profiles, topic pages, speaker bureaus, research showcases, and expert answers

• Governance controls and workflow support that help organizations maintain quality, consistency, and reputational safeguards at scale

• Structured content experiences designed to improve discoverability across search engines and generative AI platforms

ExpertFile Search™

• A global expert search engine used by journalists, producers, and event organizers to find credible sources

• Mobile apps for iOS and Android that extend expert discovery beyond the institution’s own website

• Distribution reach across more than 50,000 topics, giving organizations additional exposure where media professionals actively look for expertise

ExpertFile SignalsAI™

• Performance analytics to support smarter editorial planning and optimization of expert content programs

• Tools that help organizations identify emerging opportunities and relevant topics for expert commentary

• Visibility into how expert content aligns with evolving search, media, and AI discovery patterns

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AgentMail Raises $6M led by General Catalyst to Build the First Email Provider for AI Agents

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AgentMail Raises $6M led by General Catalyst to Build the First Email Provider for AI Agents

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Seed round led by General Catalyst, with participation from Y Combinator, Phosphor Capital, Paul Graham, Taro Fukuyama, Dharmesh Shah, Paul Copplestone, and Karim Atiyeh

AgentMail, the first email provider built for AI agents, announced it has raised $6M in seed funding led by General Catalyst, with participation from Y Combinator, Phosphor Capital, and notable angel investors including Paul Graham, Taro Fukuyama, Dharmesh Shah (CTO of HubSpot), Paul Copplestone (CEO of Supabase), and Karim Atiyeh (CTO of Ramp). The platform is also launching its onboarding API for agents to get email addresses without human assistance.

As AI agents evolve from chatbots into virtual employees capable of managing complex workflows, they require digital infrastructure for identity, communication, and context. The prevailing solution already exists: email. More than 90% of U.S. internet users use email (source) and the market for agents is exploding. But traditional providers were designed for human users, leaving developers to hack around rate-limited inboxes and send-only APIs for agents that can’t scale operations.

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AgentMail solves this by providing dedicated email inboxes for AI agents, in the same way Gmail does for humans. Unlike transactional email APIs, AgentMail inboxes support two-way conversations with built-in parsing, threading, labeling, searching, and replying. With the addition of an integrated intelligence layer, AgentMail gives agents the same capabilities as human employees. Thousands of developers already use AgentMail to power hundreds of thousands of agents across procurement, logistics, finance, and more.

“The next billion users of the internet will be AI agents,” said Haakam Aujla, co-founder of AgentMail. “We’re building infrastructure that treats agents as first-class citizens, starting with email. The demand is so intense that the agents themselves are finding us and signing up.”

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The company was founded by Haakam Aujla, Michael (Hyun) Kim, and Adi Singh – University of Michigan grads from Optiver, Nvidia, and Accel with backgrounds in quant, AI, and venture. The funding will be used to expand the engineering team and the AgentMail platform, as well as to accelerate developer and agent adoption.

“AI agents are already starting to function as virtual employees across industries,” said Yuri Sagalov, Partner at General Catalyst. “These agents need their own identity and e-mail is the heart of identity on the Internet. Traditional identity services were not built with agentic use cases in mind, and AgentMail is building that part of the stack, starting with email. The team’s clarity of vision and speed of execution stood out to us immediately, and we’re proud to back Haakam, Michael, and Adi as they build the foundation for the agent economy.” Garret Scott, CEO of DoAnything.com said, “AgentMail took email from the thing I worried about most to something I barely think about. Now thousands of DoAnything agents operate autonomously with their own email identities.”

Today, AgentMail is also launching its onboarding API, giving AI agents direct access to the platform. Now an agent can sign up and create an email inbox entirely on its own, with proper security and abuse safeguards. The inbox can then be used to access virtually any service and communicate with virtually any human – or agent. Developers and agents can get started for free at agentmail.to.

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CTV Transparency Gap Undermines Performance: Study

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CTV Transparency Gap Undermines Performance: Study

Peer39 logo

New research from Peer39 shows signal poverty, not scale, is the core issue holding CTV back

The rapid growth of connected TV has outpaced the signals required to support effective optimization, accountability, and performance. So CTV scale will hit a ceiling unless buyers adopt reliable program-level signals. That’s the main conclusion from the data in the new industry report Peer39 released today, “How CTV Transparency Is Dragging Down Performance.”

CTV’s troubles came about because automation ramped up before anyone knew what was actually onscreen. When content is invisible or mislabeled, performance signals collapse.”

— Peer39 CEO Mario Diez

As CTV budgets accelerated away from linear television, automation moved in before the ecosystem had established consistent, program-level visibility. In the absence of reliable content signals, buyers leaned on proxies such as app names, Deal IDs, and completion rates, creating an illusion of control that masked growing structural risk.

“CTV’s troubles don’t stem from bad tools or bad actors,” said Peer39 CEO Mario Diez. “They came about because automation ramped up before anyone knew what was actually onscreen. When content is invisible or mislabeled, performance signals collapse.”

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Peer39’s analysis shows that approximately 60% of CTV bid requests contain no usable program-level data. More than 25% of open-exchange CTV supply is “Fake CTV”: inventory that is sold as CTV content, but appears on mobile, wallpaper, screensavers, or utility apps for televisions.

The report details how:
* App-level buying and curated deals hide content variability and risk
* Completion rate is a misleading proxy for quality and attention
* Fake CTV thrives in signal-poor environments, often delivering ‘perfect’ completion amid little to no engagement

Program-level authentication dramatically reduces risk and improves performance outcomes

Using Peer39’s industrywide benchmarks and campaign data, the report demonstrates that authenticated CTV environments closely resemble traditional television, in that they are dominated by professionally produced drama, news, comedy, and reality programming. Unauthenticated supply, on the other hand, drives spending on filler content, mobile-app leakage, and misclassified inventory.

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Crucially, the findings challenge the assumption that quality requires higher cost. The report heart5highlights how buyers using program-level pre-bid signals increase scale, reduce effective CPMs, and outperform curated private marketplace strategies by removing opaque layers.

“How CTV Transparency Is Dragging Down Performance” offers practical remedies for buyers and publishers, including transparency audits, rethinking publisher deal structures, adopting “no tech, no buy” standards for open-exchange CTV, and redefining success metrics around authenticated reach rather than completion rate alone.

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Credera Releases New Insight Excerpt on How AI Is Transforming the Content Supply Chain

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Credera Releases New Insight Excerpt on How AI Is Transforming the Content Supply Chain

Credera achieves AWS Generative AI Competency

Credera, a global consulting firm focused on strategy, data, and technology, has released an excerpt exploring how artificial intelligence is reshaping modern marketing operations. The excerpt is from Credera’s recent e-book “AI is turning content operations into a strategic growth engine, and paid media is the first place it’s breaking through,” which includes research on the evolution of the content supply chain.

It highlights how advances in AI are transforming the systems organizations use to plan, produce, manage, and optimize marketing content. Traditionally viewed as a back-office operational process, the content supply chain is rapidly becoming a strategic capability as brands attempt to scale personalized experiences across an increasingly fragmented media landscape.

The excerpt also outlines how rising content demand across paid, owned, and earned channels has exposed inefficiencies in legacy workflows and marketing operations. As formats multiply and performance expectations increase, many organizations struggle to produce and adapt content quickly enough to meet modern marketing requirements.

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Credera’s analysis explains how AI is changing the economics and structure of content operations by enabling organizations to generate creative assets more rapidly, automate complex workflows, and adapt content dynamically across audiences, channels, and formats.

The piece also explores why paid media is emerging as the first major proving ground for AI-powered content supply chains. In performance-driven environments where optimization cycles move quickly, the ability to generate and test creative variations at scale is becoming a competitive advantage.

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The excerpt further examines how AI-driven content systems are shifting from linear workflows toward more adaptive models that connect content creation, media activation, and performance data into a continuous feedback loop. In this model, insights from campaign performance can inform future content creation and optimization in near real time.

Credera’s broader e-book from which the excerpt is taken expands on these ideas, outlining how organizations can evolve their content supply chains into strategic, AI-enabled operating models capable of supporting scalable personalization and dynamic creative optimization.

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Bluente Launches Open-Source MCP Server, Bringing Format-Preserving Document Translation Directly Into AI Workflows

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Bluente Launches Open-Source MCP Server, Bringing Format-Preserving Document Translation Directly Into AI Workflows

Bluente - Venturra

New integration lets AI agents translate documents across 120+ languages without leaving the tools developers and professionals already use

Bluente, the AI-powered document translation platform used by over 40,000 professionals worldwide, announced the release of its open-source MCP (Model Context Protocol) server. The integration enables AI agents in Claude Desktop, Cursor, and other MCP-compatible environments to translate documents with full format preservation, directly from within the user’s existing workflow.

We built the MCP server because translation shouldn’t require context-switching,”

— Daphne Tay, CEO & Founder

The Bluente Translate MCP Server is available now on GitHub under the MIT license.

The Problem: Translation Breaks Workflow Context
Professionals working across languages face a consistent friction point. Translating a contract, financial report, or investor deck means leaving the current work environment, uploading to a separate tool, waiting for output, and then manually rebuilding formatting that was destroyed in the process. Tables break. Legal numbering disappears. Tracked changes are lost.

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The MCP server eliminates that detour entirely. A developer working in Cursor can translate a client’s PDF without switching tabs. A legal analyst using Claude Desktop can process a scanned Arabic contract and receive the formatted translation back in the same conversation.

How It Works
The MCP server exposes six tools that handle the full translation lifecycle:
• Language discovery — query supported languages and translation pairs across 120+ languages
• File upload — send documents (PDF, DOCX, XLSX, PPTX, images, and more) to Bluente’s translation engine
• Translation execution — trigger translation with automatic format preservation and integrated OCR for scanned documents
• Status tracking — monitor translation progress for large documents
• File download — retrieve the completed translation with original formatting intact
• End-to-end workflow — a single command that handles upload, translation, and download in one step

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The server runs on Node.js (v20+) and communicates with AI clients over stdio while connecting to Bluente’s APIs over HTTPS. Enterprise security standards apply: zero data retention, end-to-end encryption, and automatic deletion after processing.

Why MCP Matters for Document Translation
The Model Context Protocol is an open standard that allows AI assistants to interact with external tools and services. By publishing an MCP server, Bluente makes its translation capabilities available as a native action inside any compatible AI environment.

For engineering teams, this replaces fragile multi-vendor pipelines. Instead of stitching together separate OCR, translation, and formatting services, a single MCP tool call handles the entire process. For professionals in legal, finance, and life sciences, it means translated documents arrive formatted and ready to use, without the hours of manual rework that follow traditional translation workflows.

Built for the Community
The server is fully open source under the MIT license. Developers can inspect the code, contribute improvements, and adapt the integration for their own use cases.

“We built the MCP server because translation shouldn’t require context-switching,” said Daphne Tay, CEO & Founder at Bluente. “Professionals already work inside AI-powered environments. They shouldn’t have to leave those environments, upload a file somewhere else, wait, download the result, and then spend an hour fixing broken formatting. The MCP server brings Bluente’s translation engine directly into the tools people already use, with the same format preservation and security standards our 30,000+ users rely on.”

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IPcook Launches Low-Cost Proxy Infrastructure to Reduce AI Data Collection Costs

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IPcook Launches Low-Cost Proxy Infrastructure to Reduce AI Data Collection Costs

IPcook Logo

Generative AI has grown rapidly in recent years, driving an increasing need for large-scale AI training data. Companies often rely on the internet for data collection for AI, but gathering information at scale requires robust proxy infrastructure, which can be costly. To help enterprises and developers overcome this challenge, IPcook provides a low-cost proxy. This approach allows organizations to access the data they need while keeping operational costs manageable and supporting scalable model training.

The Rising Demand for AI Training Data
The demand for AI training data continues to grow as generative AI models advance in complexity. Effective model training requires a continuous stream of diverse and high-quality datasets, yet publicly available sources are often already heavily used.

To address this, many companies increasingly rely on web data collection to supplement their training resources. Large-scale data gathering depends on stable proxy networks to maintain uninterrupted access and prevent IP restrictions. Reliable proxy infrastructure has thus become a critical component of AI workflows, enabling organizations to scale their data collection efficiently while supporting ongoing model development and innovation.

The Cost Challenge Behind Large-Scale Data Collection
Large-scale AI data collection requires reliable proxy infrastructure. For organizations developing generative AI training data pipelines, proxy services often become a major operational obstacle.

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First, extensive web crawling depends on rotating proxies to maintain consistent access and avoid IP restrictions. Without sufficient IP rotation, requests can be blocked, causing interruptions in data collection and potentially delaying model training.

Second, high-quality proxy services often come at a substantial price, which can increase the overall cost of ongoing AI training projects and make budget planning more challenging for organizations of all sizes.

Third, startups and smaller AI teams may find these costs restrictive, limiting the volume of data they can gather and affecting the diversity and quality of their AI training datasets.

IPcook Introduces Low-Cost Proxy Infrastructure for AI Data Collection
AI models require increasingly large and diverse datasets, which makes reliable and affordable data collection infrastructure essential for many organizations. To address this need, IPcook provides a low-cost proxy solution designed to support large-scale AI data workflows. The infrastructure helps organizations manage data collection tasks without significantly increasing operational costs.

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For large-scale crawling activities, the company has the cheapest rotating proxies that distribute requests across multiple IP addresses. This approach helps maintain stable access during extended data collection tasks. With a more affordable proxy infrastructure, developers and AI teams can expand their data collection capacity and support ongoing model training.

Key Advantages of IPcook’s Rotating Proxies
– Cost-Effective Infrastructure. IPcook’s proxy services start at $0.50 per GB, allowing AI teams to maintain large-scale data collection without significantly increasing operational costs. By reducing infrastructure expenses, organizations can sustain continuous data gathering for months without exceeding budget constraints.

– Support for Scalable Data Collection. The network can handle up to 100,000 simultaneous requests, making it suitable for enterprises collecting large datasets for AI training. Organizations can scale their operations without needing to invest in additional proxy resources.

– Flexible Rotating Proxy Network. IP rotation can be configured to change with each request or at fixed intervals, such as every minute. This approach reduces the risk of blocks and allows data collection tasks to continue without interruption.

– Stable and Consistent Performance. IPcook maintains a 99.99% network uptime, ensuring continuous access to web resources. This level of reliability allows AI teams to keep data pipelines active and supports uninterrupted model development.

According to Raymond, Head of the R&D Department at IPcook, as concerns about AI training data exhaustion continue to grow, access to diverse and continuously updated datasets is becoming more critical for model development.
“AI innovation is closely tied to sustainable data collection,” Raymond noted. “Infrastructure costs should not become a barrier for researchers and developers. By providing stable and cheap rotating proxies, IPcook aims to help organizations maintain long-term data collection and support the next generation of AI technologies.”

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SiteCapture Launches SiteCaptureAI to Power a New Era of Field Service Efficiency

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SiteCapture Launches SiteCaptureAI to Power a New Era of Field Service Efficiency

Context-aware AI agent instantly analyzes jobsite documentation to automate field service workflows and slash operational costs.

SiteCapture announced SiteCaptureAI, a new product that brings AI-powered automation and intelligence to field operations. Built for organizations that install, inspect, and maintain assets, SiteCaptureAI helps field service teams sharply reduce operational costs and complete high quality work in a fraction of the time.

Field service teams capture enormous volumes of photos, videos, and documentation to verify work and maintain quality standards. However, reviewing this information still relies heavily on manual processes, making it difficult to identify and resolve issues in real time. Issues are often discovered only after crews have left the site, resulting in costly repeat visits, project delays, and operational inefficiencies.

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SiteCapture has helped reduce operational costs for thousands of companies since the launch of its SaaS platform for inspections, quality control, reporting, and work management. Now, with SiteCaptureAI, customers can achieve a new level of efficiency and profitability with AI-powered automations that include:

  • Photo & Video Intelligence that provides critical data and insights, detects and tags objects and their condition, extracts key text, generates summaries, and transcribes video narrations
  • Field Reporting Verification that ensures required photos, videos, and data are captured thoroughly and accurately
  • Automated Quality Control that instantly verifies whether quality, safety, and compliance requirements have been met and flags priority issues
  • Real-Time Field Alerts immediately notify field teams of issues and provide guidance to resolve them while the team is still on site
  • Custom Workflows that allow operations teams to create their own AI automations tailored to their unique business needs

“Field service organizations are under enormous pressure to perform high quality work with fewer resources,” said Kamal Shah, Founder and CEO of SiteCapture. “SiteCaptureAI makes that possible by automating some of the most time-consuming and error-prone aspects of field operations. By reducing manual work and automatically identifying and resolving issues in real time, we anticipate organizations can reduce the cost of quality control by up to 50 percent, maintain high standards, and complete projects faster than ever.”

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SiteCapture’s customers in the home energy, property management, construction and other field service sectors are already seeing the benefits of SiteCaptureAI.

“SiteCaptureAI allows our QA/QC team to catch photo documentation issues before installation crews leave the jobsite,” said Graham Horne, Installation QA/QC Manager at Powur, a leading solar installation company. “Ensuring all our quality control and finance partner documentation requirements are met the first time will drive significant efficiency gains for our team, reduced truck rolls, less rework, and improved first-time financing approval rates.”

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Seedtag Launches Liz Agent, the Agentic AI Platform for Faster, Smarter Media Strategy

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Seedtag Launches Liz Agent, the Agentic AI Platform for Faster, Smarter Media Strategy

New conversational interface transforms planning, decision-making and campaign activation rooted in Seedtag’s proprietary Neuro-Contextual intelligence

Seedtag, the global Neuro-Contextual advertising company, announced the launch of Liz Agent, an agentic AI Platform designed to optimize media planning and campaign activation for brands and agencies. By leveraging Seedtag’s Neuro-Contextual data, the Liz Agent acts as an end-to-end consultant, giving campaigns greater depth and personalization by uncovering real-time insights, sophisticated audience mapping, and deep competitive analysis. Liz Agent allows Seedtag’s clients to move efficiently from brief to action, streamlining every stage of the media planning phase and ensuring that  strategies can easily be activated across Seedtag’s global inventory.

As the creator of Neuro-Contextual Advertising, Seedtag decodes real-time interest, emotion, and intent to make context the foundation of planning and activation. Powered by Seedtag’s proprietary Neuro-Contextual intelligence engine, Liz Agent now acts as a strategic conversational interface for Seedtag clients, combining research, analysis, and execution into a single, connected experience. Rather than simply retrieving information. Liz Agent maximizes all elements of the campaign, including targeting, creative, and message-angle recommendations, to deliver context-rich insights aligned with specific campaign goals, closing the loop between planning and action.

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“Liz Agent represents a major step forward in how our clients can interact with Seedtag’s intelligence and use it to think through and strategize their campaigns,” said Kartal Goksel, CTO of Seedtag. “AI has always been part of our DNA. By leveraging agentic AI, we are allowing clients to plan and activate campaigns via natural conversation with Liz, empowering better media planning and faster execution. The Liz agent ensures that every strategic recommendation we make is backed by the most relevant Neuro-Contextual data available.”

Liz Agent is built on a sophisticated multi-agent orchestration engine that harmonizes state-of-the-art Large Language Models (LLMs) with Seedtag’s exclusive data, tools, and deep domain expertise. This architecture transforms Liz Agent into a specialized strategic partner through four core pillars:

  • Direct Integration with Seedtag’s Proprietary Data: This ensures all recommendations are grounded in exclusive Neuro-Contextual intelligence rather than generic AI knowledge, delivering recommendations based on verified Seedtag data.
  • Proactive Intelligence: Liz doesn’t wait for a brief. She uses network-level analysis to monitor the open web and Seedtag’s knowledge base to uncover proactive opportunities, cultural pulses and competitive insights, turning intelligence into action.
  • Conversational Interface: Its conversational layer redefines campaign activation, allowing brands to move from intelligence to execution through a simple, natural conversation.
  • From Insight to Activation: Liz Agent closes the loop between planning and execution. Strategies developed through conversation can be instantly activated across Seedtag’s global inventory.

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“We are entering a new era where agents are the primary interface to intelligence,” Brian Gleason, CEO of Seedtag said. “Liz Agent is how we put Seedtag’s AI directly into the hands of our clients, enabling them to interact with Liz through a natural conversation. It’s a major step forward in our mission to bring Liz to the world, empowering brands and agencies to build advertising rooted in human understanding, not surveillance.”

Seedtag clients can already benefit from the Liz Agent, gaining access to deeper insights and driving more effective campaign planning and execution from day one.

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Databricks Launches Genie Code: Bringing Agentic Engineering to Data Work

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Databricks Launches Genie Code: Bringing Agentic Engineering to Data Work

Genie Code turns data engineering, data science and analytics ideas into autonomous production systems

Databricks, the Data and AI company, launched Genie Code, an autonomous AI agent that fundamentally changes how data work gets done. Genie Code can carry out complex tasks such as building pipelines, debugging failures, shipping dashboards, and maintaining production systems. On real-world data science tasks, Databricks found Genie Code more than doubled the success rate of leading coding agents. Just as agentic coding tools have transformed software engineering, moving developers from autocomplete-style assistance to agent-driven development, Genie Code brings the same paradigm shift to data engineering, data science, and analytics.

Genie Code is a new addition to Genie, which lets any knowledge worker chat with their data and get trusted answers instantly using the context and semantics captured by Unity Catalog. Genie Code extends this approach to data professionals, handling the complex engineering required to go from idea to production across all enterprise data. Additionally, today Databricks announced the acquisition of Quotient AI, an innovator in evaluation and reinforcement learning for AI agents, to embed continuous evaluation directly into Genie and Genie Code.

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Rise of Agentic Data Work
Today’s data tools treat AI as a helper — writing code, running local tests, iterating on it. This leaves data teams doing the hard work of planning, orchestrating, operating, validating and maintaining. Genie Code inverts this approach. It reasons through problems, plans multi-step approaches, writes and validates production-grade code, and maintains the result — all while keeping humans in control of the decisions that matter.

“Software development has shifted from code-assistance to full agentic engineering in the past six months,” said Ali Ghodsi, Co-founder and CEO of Databricks. “Genie Code brings this revolution to data teams. We’re moving from a world where data professionals are assisted by AI to one where AI agents do the work, guided by humans. We are calling this Agentic Data Work. It will fundamentally change how enterprises make decisions.”

What Genie Code Does
Existing agentic coding tools have trouble accomplishing data tasks because they lack access to critical context like lineage, usage patterns and business semantics. Genie Code helps teams bridge the context gap to ensure the high levels of accuracy and governance required for production environments. Genie Code:

  • Acts as an expert machine learning engineer: Genie Code handles full ML workflows end-to-end. It reasons through complex problems to plan, write, and deploy models, while logging experiments to MLflow and fine-tuning serving endpoints for peak performance.
  • Embeds deep data engineering expertise: While a novice engineer might write a script that works on test data, Genie Code designs like a senior architect. It accounts for the differences between staging versus production environments, builds workflows for change data capture and applies data quality expectations.
  • Proactively maintains and optimizes: Genie Code monitors Lakeflow pipelines and AI models in the background to triage failures and investigate anomalies. It autonomously analyzes agent traces to fix hallucinations and tunes resource allocation before a human intervenes.
  • Understands enterprise context: Integrated with Unity Catalog, Genie Code enforces existing governance policies and access controls. It understands business semantics and audit requirements and federates enterprise data, including data from external platforms.
  • Improves over time: Genie Code grows smarter the more teams use it. Through persistent memory, it automatically updates internal instructions based on past interactions and coding preferences. On real-world data science tasks, Databricks found Genie Code more than doubled the success rate of leading coding agents (from 32.1% to 77.1%).

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“At SiriusXM, Genie Code supports everything from authoring notebooks and complex SQL to reasoning through table relationships and debugging pipelines,” said Bernie Graham, VP of Data Engineering, SiriusXM. “It acts as a hands-on development partner that helps our data teams deliver high-quality work in less time.”

“Genie Code changes how our data teams operate,” said Emilio Martín Gallardo, Principal Data Scientist, Data Management & Analytics at Repsol. “Instead of stitching together notebooks, pipelines, and models manually, we can hand off complex workflows to an AI partner that understands our data, governance, business context, and internal libraries such as Repsol Artificial Intelligence Products. It accelerates everything from time series forecasting to production deployment, without sacrificing rigor or control.”

Acquisition of Quotient AI Strengthens Continuous Evaluation
To close the loop on production quality, Databricks has acquired Quotient AI. Quotient automatically monitors agent performance — measuring answer quality, catching regressions early, and pinpointing failures — feeding a reinforcement learning loop that keeps agents improving over time. Quotient’s founders bring deep expertise in evaluating AI coding systems, having previously led quality improvement for GitHub Copilot. By embedding these capabilities into Genie Code, Databricks ensures data and AI systems don’t just run in production, they continuously improve.

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Atento Advances Impact Sourcing and AI-Augmented CX Through Strategic Collaboration with Sanas and Thrivin

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Atento Advances Impact Sourcing and AI-Augmented CX Through Strategic Collaboration with Sanas and Thrivin

Atento, a global leader in customer experience (CX) and business transformation outsourcing (BTO), announced a strategic collaboration with Sanas, a leading provider of real-time speech understanding technology, and Thrivin, a quality-first impact sourcing platform in Kenya.

Together, they are advancing a differentiated model for Impact Sourcing at scale and AI-augmented customer experience, enabling enterprises to expand globally while maintaining enterprise-grade governance, CX performance, and operational resilience.

This collaboration reflects Atento’s core belief that the future of CX must be Augmented by AI. Driven by People.

A Unified BTO Operating Model: Governance, AI, and Quality Talent

This initiative integrates:

  • Atento’s global BTO governance, transformation expertise, and enterprise-grade delivery framework
  • Sanas’ real-time speech understanding technology, deployed as an AI enablement layer for non-U.S. and non-Puerto Rico voice operations
  • Thrivin’s highly educated, English-proficient, performance-driven African talent model, integrated into Atento’s global operating standards

Atento remains the orchestrator of the end-to-end model, ensuring that security, compliance, performance management, and transformation frameworks meet the expectations of global enterprise clients.

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Operationalizing Impact Sourcing at Enterprise Scale

Through this collaboration:

  • Impact Sourcing at Scale is delivered through Thrivin’s quality-first talent pipeline, integrated into Atento’s enterprise governance model and performance frameworks.
  • AI-Augmented CX is enabled through Sanas’ real-time speech understanding technology, reducing communication friction while enhancing agent confidence and customer clarity.
  • Total Experience (TX) serves as the organizing principle, aligning customer experience, employee experience, and operational efficiency through a delivery model intentionally human at its core and enhanced by AI.

Expanding Global Delivery with Discipline and Impact

Africa represents a growing frontier for CX and business services, with a young, digitally fluent, English-speaking workforce eager to participate in global markets. By combining Thrivin’s skilled talent base with Atento’s transformation methodologies and operational governance, enterprises gain access to a new delivery geography without compromising quality or brand integrity.

Meanwhile, Sanas’ AI technology addresses a key challenge in global voice operations, enabling international expansion while preserving customer experience consistency.

This collaboration reflects a key industry shift, the future of outsourcing lies in integrating AI, governance, and workforce development into a unified model, moving beyond geography as the driver of transformation.

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“This collaboration brings together complementary strengths, Atento’s global transformation solutions and BTO delivery model, Sanas’ real-time speech understanding technology, and Thrivin’s exceptional talent network in Africa. Together, we’re creating new opportunities to deliver AI-augmented customer experience at scale while helping enterprises expand into new markets with the governance, performance, and quality they expect from Atento. It also creates a strong platform for all three organizations to grow together as we support the next generation of delivering innovative global solutions for our customers”, said Brent Bush, EVP Sales & Business Development at Atento.

“From a U.S. operations perspective, this collaboration strengthens our ability to scale responsibly without compromising enterprise standards,” said Chris Condon, President & GM US Nearshore at Atento. “By integrating AI-enabled voice technology with a disciplined, governed impact sourcing delivery model, we’re demonstrating that global expansion, operational rigor, and workforce development can coexist within a high-performance BTO framework.”

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