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Capital One Software Announces New Observability and AI-Powered Optimization Capabilities for Slingshot to Drive System-Wide Data Efficiency

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Capital One Software Announces New Observability and AI-Powered Optimization Capabilities for Slingshot to Drive System-Wide Data Efficiency

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Context-Driven Insights Improve Snowflake Performance, Detect and Resolve Data Infrastructure Issues

Capital One Software, the enterprise B2B software business of Capital One, announced intelligent optimization features for Capital One Slingshot, designed to improve performance and quickly detect and resolve data infrastructure issues. By utilizing context across a user’s environment, Slingshot will identify opportunities to improve workload performance in Snowflake that go beyond basic SQL syntax and storage costs.

These features reflect a fundamental shift in how enterprises can approach data efficiency: not just tuning individual resources in isolation, but understanding and optimizing the entire system, including code, pipelines, infrastructure and the teams running them.

Marketing Technology News: MarTech Interview with Theresa Pham, Head of Product @ Wayvia

“Enterprise data infrastructure is a complex web of inter-dependencies that requires a context-first approach for optimization at scale,” said Jeff Chou, VP, Slingshot Product Management, Capital One Software. “Slingshot’s intelligent optimization capabilities can help businesses understand what their queries are actually doing, what their tables are built for, and where their teams are unknowingly duplicating work. That’s how we help enterprises get efficient at the system level.”

Marketing Technology News: Idle data is as good as no data

Upcoming Slingshot features include:

  • Context-Aware AI Query Optimization: Enterprise Snowflake environments generate staggering query volumes that no team can manually evaluate at scale. Slingshot will automatically identify top queries by cost, runtime, and frequency in Snowflake environments. It will generate AI-powered optimization recommendations that surface clear, actionable steps and project cost and runtime improvements for both Snowflake admins and data engineers.
  • Context-Aware AI Table Optimization: Query inefficiency often doesn’t stem from the query itself, but from poorly configured tables. Slingshot’s Table Optimization capability will analyze the top 50 tables by query impact and surface multi-dimensional infrastructure fixes. Slingshot will also validate that proposed table changes will not negatively impact the top queries already running against that table, before surfacing the recommendation.
  • Duplicate Pipeline Detection: Large enterprises have full pipelines that are unknowingly redundant. Slingshot’s AI-powered duplicate pipeline detection will identify these redundancies by looking at common patterns of data usage to find potential overlap. Slingshot uses AI to compare many potentially-similar workloads to evaluate functional equivalence.
  • Data Explorer: This interactive, drill-down analytics interface will allow data teams to investigate root causes. Users can interactively slice Snowflake costs across various dimensions (accounts, users, query hashes, Slingshot tags, service types) with synchronized filtering. Drill-downs offer rich object detail pages for individual warehouses, databases, and queries, collapsing the gap between cost visibility and actionable change. Data rich before-and-after impact analysis pages provide historical context for any changes made to a Warehouse.

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SymphonyAI Brings AI-Powered Assortment and Space Platform to Global CPGs, Compressing Category Review Cycles from Weeks to Days

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InnerGroup Appoints Neha Bubna to Accelerate AI-driven Content Production at InnerStudio

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CINDE Assortment and Space closes the loop between assortment, planogram, and in-store execution, proven across 500-plus global CPG deployments

Planogram compliance failures, undetected out-of-stocks, and the lag between headquarters planning and store-level execution cost grocers measurably in comp sales, shrink, and associate labor hours. The tools built for category planning have never been designed to close that execution gap. In response, SymphonyAI, a global leader in Vertical AI, announced the availability of CINDE Assortment and Space for CPGs, an AI platform that closes the loop between assortment strategy, planogram execution, and in-store compliance, compressing the category review cycle from four to six weeks to a matter of days.

80% of CPG headquarters lack the analytics needed to support assortment and shelf decisions — still running quarterly reviews on stale spreadsheets while category performance erodes between resets.

The platform is underpinned by SymphonyAI’s Transferable Demand AI, a model trained across 25 years of retail data and validated in production across more than 500 global CPG deployments, including PepsiCo, Southern Co-op, and every one of the top 25 global CPG companies. CINDE Assortment and Space is available as a standalone Assortment-as-a-Service offering and as part of the full CINDE CPG Enterprise Suite.

Marketing Technology News: MarTech Interview with Theresa Pham, Head of Product @ Wayvia

Five Use Cases

Each addresses a specific, recurring failure point in how CPGs manage category decisions today, identified across decades of production deployments:

  • Store Intelligence — Photo-to-Planogram Loop: A merchandiser takes a mobile photo of the shelf. Computer vision identifies every SKU, facing, and out-of-stock condition and routes a corrective task to the right associate, with no manual audit, no separate compliance tool, and no lag between the store walk and the action. The output feeds directly into the next assortment cycle, closing the planogram compliance gap that compounds between resets and drives on-shelf availability loss.
  • Assortment Optimization — Transferable Demand: SKU-level rationalization driven by incrementality scoring, need-state analysis, and cannibalization modeling. Southern Co-op achieved a 5.2 percent category sales uplift using this capability, a comp sales outcome driven by getting the right SKUs on the right shelves. The Transferable Demand AI model carries across retailers without retraining, meaning work validated at one JBP extends to the next without rebuilding from scratch.
  • Intelligent Store-Based Clustering: Store clustering derived from store-level transaction and sales patterns, enabling highly accurate, scalable models tailored to localized demand, shopper behavior, and operational dynamics. This capability is particularly valuable across wholesale environments and markets with limited customer-level data, including many Asia-Pacific and emerging markets where retailer adoption depends on practical, store-centric intelligence.
  • Space-Aware Assortment — Category Captain Workflow: Integrated assortment and planogram planning from a shared data model, producing shelf-ready outputs that store teams can act on directly. These are not analytical recommendations requiring manual translation before execution. PepsiCo deployed this capability for category captain planning across major UK grocery retailers, compressing range review cycles and generating retailer-ready deliverables within the platform.
  • Planogram Automation — Multi-Banner Scale: Store-specific planograms generated and maintained at scale across banners, countries, languages, and regulatory contexts, eliminating the manual rebuild cycle that consumes field and category team capacity between resets. A global retailer based in Europe runs CINDE planogram automation across 32 countries and 32 banners, the largest multi-banner deployment of its kind.

Marketing Technology News: Idle data is as good as no data

Market Context

According to the POI 2024 State of the Industry Report, 80 percent of CPG headquarters lack the capabilities needed to support pricing, trade, and go-to-market decisions. The category has historically been served by disconnected point solutions: clustering, planogram, and compliance tools that operate in isolation, each requiring manual handoffs that introduce lag and execution failures at store level. No vendor has previously integrated all four disciplines into a single platform with a shared data model.

The convergence of three factors has made this integration both technically feasible and commercially urgent: the acceleration of range review frequency as retailers demand more responsive joint business planning; the availability of computer vision at scale for in-store compliance verification; and the maturation of large-scale demand models capable of transferring across retail contexts without retraining.

“CPGs have spent years making assortment and shelf decisions with disconnected tools that cannot share data across the planning cycle,” said Manish Choudhary, President of Retail, SymphonyAI. “CINDE Assortment and Space was built to close that loop entirely. When a demand model proven at one retailer transfers without retraining to every other JBP in the portfolio, and when in-store execution feeds directly back into planning, CPGs stop rebuilding work from scratch every quarter. That capability is available today, backed by 25 years of production deployment across more than 500 global CPGs.”

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Visionbay.ai Selects Netris as the Network Automation Foundation for the Largest GPU Cluster and AI Supercomputing Center in Taiwan

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Visionbay.ai Selects Netris as the Network Automation Foundation for the Largest GPU Cluster and AI Supercomputing Center in Taiwan

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Foxconn-backed Visionbay.ai standardizes on the Netris NAAM platform — Network Automation, Abstraction, and Multi-Tenancy — to accelerate deployment, deliver hard multi-tenancy (enforced in hardware), provision customers instantly, and empower network engineers to automate and streamline the operation of complex GPU networking.

Netris announced at GTC Taipei 2026 that Visionbay.ai (“Visionbay”), backed by Foxconn, has selected the Netris NAAM platform — Network Automation, Abstraction, and Multi-Tenancy — to operate the largest GPU cluster and AI supercomputing center in Taiwan. Visionbay has also standardized on Netris as the network automation foundation across its entire GPU cluster roadmap, which extends to future GPU generations.

“Netris NAAM is essential infrastructure for any GPU cluster at AI factory scale.” – Neo Yao, CEO of Visionbay.ai

Visionbay is Foxconn’s dedicated business unit for AI supercomputing and cloud operations, and an NVIDIA Cloud Partner (NCP). The company’s mission is to build a sustainable AI ecosystem that powers Asia’s intelligent future, delivered through an end-to-end AI Factory solution from AI infrastructure to application-layer integration services. Visionbay is one of the leading AI infrastructure platforms and GPU cloud providers across Asia.

Marketing Technology News: MarTech Interview with Theresa Pham, Head of Product @ Wayvia

Why Visionbay chose Netris

Visionbay conducted a rigorous technical and procurement evaluation before selecting Netris for its first cluster and standardizing on Netris as the network automation foundation across its entire GPU cluster roadmap. The selection came down to six factors:

  • Market leadership in NAAM. Netris is the market leader in the Network Automation, Abstraction, and Multi-Tenancy (NAAM) category, with more live deployments than all other network automation vendors combined — 25+ live deployments in the last 12 months across neoclouds, AI factories, and sovereign AI cloud providers worldwide.
  • Technology leadership across NAAM category.
    • Network Automation: Netris automates the configuration of every fabric layer (North-South Ethernet, East-West Ethernet or InfiniBand, NVL72, Edge, DPU, SuperNIC).
    • Network Abstraction: Netris’s algorithm turns cloud-like constructs (VPCs, peering, elastic IPs, load balancers, NAT rules) into precise and validated network configurations and surgically applies them throughout all networking fabrics.
    • Network Multi-Tenancy: Netris enforces hard multi-tenancy on networking hardware across switches, DPUs, and fabrics, delivering the hardware-level isolation that sovereign AI workloads require for data sovereignty and compliance.
  • Future-proof across GPU generations. Netris helps Visionbay future-proof its network automation across evolving GPU generations, supporting the hardware Visionbay needs to deploy today and eliminating the need to rebuild the network automation model for each new infrastructure generation.
  • Ecosystem alignment. Netris is the most widely deployed network automation platform for AI infrastructure, with native integrations across NVIDIA DSX Air, NVL72, BlueField DPU orchestration, and East-West networking across Ethernet or InfiniBand.
  • Local team and language support. Netris has local teams in Asia that support local language and in-person engagement.
  • Operational scalability. Netris supports the operational scalability Visionbay requires as it expands its AI cloud infrastructure and future GPU deployments.

“Netris NAAM is essential infrastructure for any GPU cluster at AI factory scale,” said Neo Yao, CEO of Visionbay.ai. “Our collaboration with Netris supports the operational scalability and flexibility required for next-generation AI Factory infrastructure.”

Marketing Technology News: Idle data is as good as no data

Why traditional approaches didn’t work

Visionbay’s architecture team understood from the start that networking for GPU clusters is fundamentally more complex than traditional data center networking. Every GPU server connects across multiple fabric layers — North-South Ethernet, East-West networking, NVL72, edge, host, and DPU — that must reconfigure in concert on every tenant change, GPU reassignment, and resize.

Manual networking was eliminated immediately: hand-configuring hundreds to thousands of switches on every change cannot scale, and small misconfigurations introduce downtime, tenant data leakage, and weeks of delay that leave GPUs idle. In-house automation was not considered either — every NVIDIA reference architecture update, GPU generation, and workload type breaks homegrown tools, and building in-house means becoming a network automation company before becoming an AI cloud.

What Netris NAAM delivers

The Netris NAAM platform helps AI cloud operators accelerate initial deployment and time to first token, provision new customers instantly with cloud-provider-like networking, dynamically scale GPU capacity across tenants without downtime, maximize GPU utilization across tenants, deliver hard multi-tenancy across every fabric, and empower network engineers to automate and streamline the operation of complex GPU networking. Netris eliminates manual configuration errors and the unplanned outages they cause.

“Asia is leading the sovereign AI buildout, and Visionbay is at the center of it with Taiwan’s largest GPU cluster and AI supercomputing center,” said Alex Saroyan, CEO and Co-Founder, Netris. “Visionbay is helping define what next-generation AI infrastructure looks like in the region, and we are honored that the Netris NAAM platform is the network automation foundation behind their AI cloud.”

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ZoomInfo Launches GTM.AI, the Headless GTM Context Layer, to Ground Every AI Agent in Verified GTM Data

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ZoomInfo Launches GTM.AI, the Headless GTM Context Layer, to Ground Every AI Agent in Verified GTM Data

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ZoomInfo has made GTM.AI generally available as the verified data foundation that grounds AI agents across the go-to-market ecosystem, from Claude, ChatGPT, Microsoft Copilot to Salesforce Agentforce, HubSpot Breeze, and dozens more, in continuously verified B2B intelligence.

ZoomInfo , the all-in-one AI GTM platform, has confirmed the general availability of GTM.AI, the headless GTM context layer and the API and Model Context Protocol home that makes the company’s verified intelligence natively accessible to AI agents across the tools go-to-market teams already use. Through one connection, that verified intelligence now reaches dozens of surfaces including:

GTM.AI is ZoomInfo’s headless GTM context layer, the verified data foundation for AI agents.

  • Frontier AI assistants: Claude, ChatGPT, Microsoft Copilot
  • Agentic CRM and orchestration platforms: Salesforce Agentforce, HubSpot Breeze, Microsoft Copilot Studio, and IBM watsonx Orchestrate.
  • Sales execution and engagement tools: Outreach AI, Nooks AI, Gong, and LeanData.
  • Data and agent platforms: Google ADK, Dust, Glean, Databricks, and Google’s Agent Development Kit.

Any connected agent can ground its work in the same continuously verified data that powers the world’s largest revenue organizations, without rebuilding pipelines, without scraping, and without compromising on compliance.

Go-to-market is being rebuilt in real time. The teams pulling ahead are not the ones with the most tools, they are the ones whose AI is grounded in the cleanest, most verified data, wired into every workflow they run.

Marketing Technology News: MarTech Interview with Theresa Pham, Head of Product @ Wayvia

The depth and breadth AI agents in GTM actually need. Frontier models are exceptional at reasoning, but they are constrained by what they can access. The ceiling on agentic go-to-market is not model intelligence. It is the quality, freshness, and structure of the data the model can call. The GTM Context Graph behind GTM.AI resolves 100 million companies, 500 million contacts, billions of buying signals, and identity-resolved IP-to-organization pairings into one connected graph, so every record resolves to every other record. When an agent asks for VP-level marketing leaders at fast-growing fintechs that moved their data warehouse to Snowflake and have a champion who just changed jobs, the system returns a verified, contactable, signal-ranked list in a single call.

One GTM context layer, available everywhere work happens. The Model Context Protocol, the open standard for connecting AI systems to external data and tools, has become the connective tissue of the agentic era. ZoomInfo’s MCP implementation positions GTM.AI as the headless context layer beneath every connected agent, exposing company search, contact discovery, real-time enrichment, intent retrieval, and AI-powered recommendation, each governed by the customer’s existing data entitlements and permissions. Inside Claude, an analyst can build a target account list, enrich it with verified contacts, and produce a buying-committee map in one conversation. Inside ChatGPT, a seller can prep a discovery call by pulling org structure, news, intent signals, and direct dials without leaving the chat. Inside Salesforce Agentforce or HubSpot Breeze, an autonomous agent can prospect against verified accounts instead of stale CRM records. Same verified intelligence, same GTM Context Graph, whichever surface the work happens on.

Marketing Technology News: Idle data is as good as no data

B2B data decays fast. By widely cited industry estimates, roughly 70 percent of contact data goes stale every year, and that decay is fatal to agentic workflows. An agent acting on stale data does not just produce a bad outcome. It produces bad outcomes at machine speed and scale. ZoomInfo’s verification methodology, built on proprietary collection technology, machine learning, public-source signal processing, and a contributory network, is what allows agents to act with confidence. Forrester has named ZoomInfo a Leader in Intent Data Providers, citing the largest research and development investment of any provider. Enterprise compliance is built in across ISO 27701, ISO 27001, SOC 2 Type II, and TRUSTe GDPR.

For the go-to-market operator, the implication is direct. The AI tools your teams already use, whether that is Claude or ChatGPT for research, Microsoft Copilot for execution, Salesforce Agentforce or HubSpot Breeze for autonomous prospecting, or Outreach AI and Nooks AI for engagement, can now operate against the same source of truth. You do not need a new workflow. You need a better version of the one you already have. GTM.AI, ZoomInfo’s headless GTM context layer, is generally available to ZoomInfo customers, with setup guides and full developer documentation for the MCP server and APIs available at gtm.ai.

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DXC Launches One of Its Most Powerful Growth Engines: DXC Engineering

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DXC Launches One of Its Most Powerful Growth Engines: DXC Engineering

DXC formally elevates its engineering division as a distinct service offering within its Consulting & Engineering Services (CES) organization combining deep domain-specific solutions, a powerful ecosystem of strategic technology partners, and AI-enabled solutions

  • 11,000+ engineers across 29 countries within CES, DXC’s broader 40,000-strong Consulting & Engineering Services organization

  • A rapidly growing engineering market where DXC’s combination of domain depth, proprietary platforms, and curated partner ecosystem creates a structurally differentiated value proposition

  • Software powering 50M+ vehicles worldwide, trusted by 17 of the world’s top 20 banks, and mission-critical infrastructure — evidence of an engineering practice that already operates at global scale

DXC Technology, a leading enterprise technology and innovation partner, announced DXC Engineering, a distinct service offering and a foundational pillar of its Consulting & Engineering Services (CES) business. DXC Engineering is built on the 20-year digital engineering heritage of Luxoft—which DXC acquired in 2019—and consists of more than 11,000 highly specialized engineers delivering mission-critical solutions across Financial Services, Automotive, Manufacturing, Telecommunications, Energy and other industries.

The new entity brings together three distinct capabilities: deep domain expertise, an industry-specific/AI partnership ecosystem, and Physical AI-enabled smart product design. DXC Engineering does not separate industry knowledge from technical execution, giving customers a single partner for the challenges that matter most. DXC builds solutions for customers that include a trading risk engine that can navigate real market volatility, an autonomous driving stack that meets functional safety standards, and a real-time telecom network platform that scales. DXC Engineering builds on these with focused investments to harness the potential triggered by AI.

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“With DXC Engineering, we are making a deliberate bet and doubling down on DXC’s unique engineering DNA. We are in the early stages of the software-defined era, and the time is now for customers to turn R&D into software-defined intelligent systems that will help them win in the marketplace. DXC Engineering is a signal to the market and to our customers that we are elevating the importance of our IP — both human and digital. Our customers look to DXC to design, build, and operate intelligent systems at scale, especially in environments where failure is not an option, and DXC Engineering will accelerate that capability just at the moment it’s needed most in the marketplace.”

— Ramnath Venkataraman, President, Consulting & Engineering Services, DXC Technology

CAPABILITIES DXC ENGINEERING BRINGS TO MARKET
Domain-specific Solutions:
DXC Engineering operates at both ends of the engineering spectrum: integrating the industry-specific software packages customers depend on, while simultaneously building the proprietary systems — trading engines, risk platforms, digital banking infrastructure — that set them apart. In Financial Services, DXC Engineering supports trading, risk, treasury, payments, digital banking, and regulatory platforms used by leading global institutions. In automotive, this dual model powers AMBER, DXC’s proprietary software framework, which reduces vehicle software development cycles by up to 50% and infotainment costs by up to 30%. In other industries, DXC Engineering delivers telecom network modernization, AI-enabled operational platforms, Smart Manufacturing, and industrial engineering solutions supporting critical processes and infrastructure. The combination of deep integration expertise and bespoke engineering enables DXC to execute complex, large-scale transformations with speed, precision, and confidence.

A Robust Partner Ecosystem
DXC Engineering has deliberately built a partner ecosystem spanning the full breadth of what customers need — from silicon and AI compute leaders who unlock hardware-software convergence, to industry platform specialists including Murex, Temenos, and others who define how financial markets, trading operations, and core banking systems run, to a growing cohort of domain-specific technology startups bringing frontier capability into production environments. Across every layer, DXC Engineering adds its own bespoke engineering and enterprise-grade integration that goes further than any single-capability partner working alone.

Physical AI and AI-enabled Intelligent Systems
DXC Engineering applies AI across both enterprise and physical environments to improve automation, resilience, productivity, and operational intelligence. This includes banking and operations platforms, intelligent telecom and infrastructure systems, and advanced operational analytics across industries.

In a physical environment at the core of DXC Engineering’s smart product capability is Physical AI — the discipline of engineering intelligent systems where software, hardware, and AI converge in real-world environments

From making autonomous vehicles road-ready to enhancing production line productivity at  unprecedented speed, DXC works with silicon and AI compute leaders, such as NVIDIA to integrate embedded computing power solutions that can make Physical AI come to life for clients in ways that redefine what’s possible.

Marketing Technology News: Disrupt or Be Disrupted: The AI Wake-Up Call for B2B Marketers

AT SCALE TODAY

  • Financial services: 17 of the world’s top 20 banks served; 350+ banking and capital markets clients across 70 countries; world’s largest Murex implementation practice
  • Automotive: software in 50M+ vehicles; active programs with leading European and global OEMs and Tier-1 suppliers via AMBER platform
  • Other focus industries covered by 150+ clients and more than 3000 projects delivered

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impact.com to Power Minecraft’s First-Ever Affiliate Program

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impact.com to Power Minecraft’s First-Ever Affiliate Program

Impact.com Affiliate Program – SaaS Affiliate – Affiliate Programs & Partner Programs

New partnership reflects the industry’s shift toward creator-led marketing and supports the development of a robust affiliate program for gaming creators 

impact.com, a global infrastructure for partnership-driven commerce, announced that it will power Minecraft’s first-ever affiliate program, making it easier for creators to earn from the Minecraft content they already share with their communities.

The program will be powered by impact.com’s Performance and Creator partnership solutions, enabling Minecraft to manage creator relationships, track affiliate performance, and reward partners globally through a single platform.

The launch signals the arrival of the sandbox game – officially the best-selling video game of all time with over 300 million copies sold – as a leading brand in the growing creator and affiliate economy.

Marketing Technology News: MarTech Interview with Theresa Pham, Head of Product @ Wayvia

The Minecraft affiliate program rewards the community for what they already do – create, share, and recommend Minecraft experiences. By combining creator partnerships with performance-based affiliate solutions, the program helps creators monetize their influence in a way that feels natural, authentic, and community‑driven.

“Minecraft has one of the most passionate creator communities in the world, and this program gives those creators a way to turn their influence into real business results,” said David A. Yovanno, CEO at impact.com. “With impact.com‘s Creator and Performance solutions running together, Minecraft can build a global partnership ecosystem that pays creators for real outcomes without compromising the authenticity that makes this community what it is.”

Using impact.com’s Creator solution, Minecraft can discover, recruit, and manage creator partnerships at scale, while the Performance solution provides the tracking, attribution, and payout capabilities needed to turn those partnerships into a measurable growth channel.

Marketing Technology News: Idle data is as good as no data

Together, these solutions enable Minecraft to support multiple partner types—including creators, publishers, educators, and Minecraft Marketplace partners—while providing clear tracking, transparent reporting, and real-time performance dashboards that allow partners to understand what content resonates most with their audiences.

The program is designed to scale globally and is expected to become one of the largest affiliate ecosystems in gaming.

The launch reflects a broader industry shift from paid advertising to creator‑led, partnership‑driven growth, where trusted recommendations drive measurable business results. As influencer and affiliate models converge, leading brands are formalizing creator monetization through performance‑based programs with clear attribution, governance, and ROI. Minecraft is positioning creators as a scalable, accountable growth engine, not  a one‑off marketing channel.

impact.com is the world’s leading global infrastructure for partnership-driven commerce, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products – Performance (affiliate), Creator (influencer), and Advocate (customer referral) – unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,900 global brands – including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics -rely on impact.com to power more than 2 million partnerships, collectively generating over $110 billion in annual gross merchandise value (GMV).

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OtterlyAI Launches a Public API, a Claude Skill, and a Marketplace of 101+ Marketing Workflows for AI Search

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Full-Stack Marketing Sets the New Growth Benchmark for 2026

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Brand visibility data now runs wherever marketing teams work, including Claude, n8n, and other tools, with a community marketplace where users can submit their own agent workflows

OtterlyAI, the AI Search Optimization Platform, released three product updates that move brand visibility data out of the dashboard and into the tools marketing teams already use: a Public API, a Claude Skill, and the OtterlyAI Marketplace.

Until now, a brand’s data on how it appears across ChatGPT, Google AI Overviews, Google AI Mode, Perplexity, Gemini, and Microsoft Copilot lived inside the OtterlyAI platform. The Public API changes that. Teams can pull brand reports, search prompts, citations, and recommendation data programmatically and route it into reporting stacks, internal tools, and automation workflows.

Marketing Technology News: MarTech Interview with Theresa Pham, Head of Product @ Wayvia

The Claude Skill brings the same data into Anthropic’s Claude. A user can ask Claude to pull brand and domain performance, surface recommendations, and turn the results into an executive-ready summary, without leaving the chat. One example workflow builds a content brief that targets the search prompts where a brand is currently missing from AI answers.

The OtterlyAI Marketplace launches alongside both, with 100+ workflows for AI Search visibility. It includes prompts, agents, tools, and resources spanning brand visibility checks, share of voice comparisons, citation gap analysis, GEO audits, and prompt research. Many connect directly to Claude, n8n, and other platforms. Each workflow has been tested in production, submitted OtterlyAI and by its customers.

Marketing Technology News: Idle data is as good as no data

Community members can submit their own workflows to the Marketplace. OtterlyAI plans to review and publish submissions so the library grows with real use cases from the GEO community rather than from a single team.

“AI Search is already a major channel for many brands” said Thomas Peham, CEO and co-founder of OtterlyAI. “The API and the Claude Skill let people build with their visibility data directly. The Marketplace gives them a head start with workflows that already work.”

The releases reflect a shift in how marketing teams measure search. As AI Search answers replace traditional links for a growing share of queries, teams need to know whether their brand is mentioned, which sources AI engines cite, and where competitors appear instead. OtterlyAI monitors tracked search prompts across the major AI Search experiences and reports on brand mentions, Share of Voice, brand coverage, citations, and the Brand Visibility Index.

An MCP (Model Context Protocol) server is planned for release in the coming weeks, which will let AI agents connect to OtterlyAI data through a standard protocol.

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Orbit Analytics Introduces Vega Engine to Modernize Enterprise Data Pipelines

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Orbit Analytics Introduces Vega Engine to Modernize Enterprise Data Pipelines

Orbit Analytics

New pipeline execution engine helps enterprises move, transform, validate, and monitor data across ERP systems, cloud applications, and modern data platforms.

Orbit Analytics announced Vega Engine, a new generation of its enterprise data pipeline technology designed to help organizations connect, process, and prepare business data for analytics, reporting, and AI-enabled decision-making.

Vega Engine is built for enterprises that depend on complex operational systems such as ERP, finance, procurement, supply chain, CRM, and other business applications, but need that data available in modern cloud data platforms with greater reliability, transparency, and control.

As organizations modernize their data infrastructure, many still face practical challenges, fragmented source systems, brittle integrations, long-running extracts, inconsistent transformation logic, limited lineage, and downstream reporting failures that are discovered too late.

Orbit DataJump (Vega Engine) addresses these challenges by providing a more governed and scalable foundation for enterprise data movement and transformation.

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Built for modern cloud data platforms

Orbit DataJump (Vega Engine) includes prebuilt connectors for leading enterprise data platforms, including Databricks, Snowflake, Oracle Lakehouse / ADW, Microsoft Fabric, and Amazon Redshift, along with connectors for various enterprise business applications such as Oracle Cloud Applications, Oracle E-Business Suite, Salesforce and many more.

Rather than treating every platform as a generic target, Vega Engine is designed to take advantage of each platform’s native processing capabilities where appropriate. This includes support for optimized data loading, transformation execution, and reduced unnecessary data movement across the pipeline lifecycle.

Vega Engine introduces centralized data pipelines that allow data engineers to define and manage pipeline logic through a zero-coding visual interface, while also allowing to extend pipelines with scripting and advanced transformation logic where needed. This greatly helps reduce pipeline management.

“Enterprises do not simply need faster data movement. They need reliable, governed, and observable data pipelines that can support critical reporting and analytics with confidence,” said Ravi Jasti, CTO at Orbit Analytics.

“Vega Engine was designed to modernize the foundation of our data pipeline technology by improving execution performance, platform integration, data quality controls, and operational transparency across complex enterprise environments.”

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Key capabilities of Vega Engine include:

  • Enterprise-grade data pipeline execution for cloud and hybrid environments.
  • Connectors for major cloud data platforms and enterprise business applications.
  • Visual pipeline authoring with advanced scripting support.
  • Push-down execution and platform-aware processing where supported.
  • Built-in data quality validation and operational alerting.
  • End-to-end lineage tracking from source to destination.
  • Improved reliability for analytics, reporting, and downstream data products.

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Hyland Launches Next Wave of AI Platform Innovations to Unlock the Content-Powered Agentic Enterprise

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Hyland Launches Next Wave of AI Platform Innovations to Unlock the Content-Powered Agentic Enterprise

Account: Hyland Software, Inc.

Company enables global organizations to scale agentic automation with new technology blueprint powered by the Content Innovation Cloud

Hyland, a global leader in enterprise content management (ECM) and the pioneer of the content-powered agentic enterprise, unveiled a bold new wave of platform innovations at CommunityLIVE 2026 designed to move AI from experimentation to enterprise-wide adoption. Powered by the Content Innovation Cloud™, these advancements transform governed enterprise content into trusted, actionable intelligence that accelerates business outcomes. To meet the demands of global organizations, Hyland announced the general availability of the Enterprise Context Engine and introduced industry-specific ontologies that enrich organizational context for more accurate, domain-aware AI performance. Additionally, the company delivered Enterprise Agent Mesh, enabling governed orchestration of AI agents at scale, and introduced Agent Lifecycle Management and Control Tower capabilities to deliver enterprise-grade control, observability, and operational oversight.

“AI is being used to accelerate business outcomes, but the winners will be the enterprises that can embed AI into their operations with governance and control,” said Jitesh S. Ghai, CEO at Hyland. “At Hyland, we see healthcare, insurance, banking, education, and government professionals spending significant amounts of time on manual work with documents, and we believe agents should automate the mundane so professionals can refocus on the joy of the job. Our latest innovations are designed to do just that, delivering the critical building blocks needed to operationalize the content-powered agentic enterprise at scale.”

“AI is reaching an inflection point in the enterprise, where success is no longer defined by pilots, but by the ability to operationalize across complex, distributed environments,” said Amy Machado, Senior Research Manager at IDC. “This means moving beyond isolated intelligence to systems that can interpret content, align with business processes, and operate within defined controls and obligations. This is where a strategic investment in modern content platforms like Hyland can drive measurable business outcomes.”

Delivering Industry Solutions for the Content‑Powered Agentic Enterprise

Hyland is pioneering the content‑powered agentic enterprise by delivering preconfigured, industry‑specific agentic solutions that automate enterprise execution across healthcare, banking, insurance, education, and government. Grounded in governed content, deep industry domain expertise, and purpose-built orchestration, Hyland enables organizations to transform fragmented, document driven processes into coordinated systems of action.

From intelligent medical records and clinical workflows in healthcare, to customer onboarding and loan operations in banking, to claims, compliance, and underwriting in insurance, these solutions demonstrate how AI can deliver value with the context, consistency, and control needed in high consequence environments. The result is a unified platform that connects content to action, enabling organizations to operationalize AI at scale to accelerate their business outcomes.

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Hyland is already modeling what agentic automation looks like when grounded in real operational context:

  • Agentic Hospital: coordinated set of clinical and administrative agents that unify fragmented patient content into decision ready intelligence, projected to enable up to 5x faster referral assembly, 60% more efficient record intake, and faster, more confident clinical decisions. These agents work together across systems to reduce administrative tasks and give healthcare workers more time to spend with patients.
  • Agentic Accounts Payable: fully orchestrated set of financial operations agents that automate invoice processing, validation, and exception handling. Delivered as a ready‑to‑deploy capability, this solution is projected to drive up to 10x faster invoice cycle times, a 60% reduction in cost per invoice, and rapid ROI with a six‑month payback period.
  • Agentic Bank: preconfigured collection of underwriting and onboarding agents that streamline lending workflows by identifying gaps earlier and reducing process friction. This packaged solution is projected to enables applications to reach underwriter‑ready status in days instead of weeks, while reducing manual touchpoints and cutting follow‑up requests by up to 50%, allowing teams to focus on higher value work rather than mundane tasks.

Advancing the Agentic Enterprise Through Business Context that Drives Results

Hyland has announced the general availability of the Enterprise Context Engine, designed to make AI more actionable by delivering more reliable results based on specific business context. The Enterprise Context Engine is the layer that enables content curation, knowledge enrichment, and knowledge graphs, contextualized by industry-specific ontologies.

This set of industry-specific ontologies is designed to support organizations across healthcare, insurance, financial services, education, and government. An industry‑specific map of entities, terminology, relationships, and rules; an ontology enables AI systems to understand not just what content says, but how concepts connect and what constraints apply in the context of a given industry.

For regulated industries, context is mission-critical to ensuring AI does more than simply summarize documents; enabling agentic automation to safely support reliable decisions and actions. In healthcare, ontologies connect diagnoses to lab results, medications, physician notes, and treatment plans. In financial services, they link regulatory obligations to controls, policies, accounts, and compliance structures. In insurance, they define the relationships between policies, claims, coverages, risk indicators, and investigation signals, enabling more accurate and context-aware outcomes.

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Enabling Observability and Control for the Agentic Enterprise

Hyland expanded the Content Innovation Cloud platform with general availability of Enterprise Agent Mesh, giving organizations a single, unified layer to oversee how AI agents operate, interact, and deliver outcomes across the enterprise. The company also introduced Control Tower to serve as the operational command center for the Enterprise Agent Mesh, giving organizations the real-time observability and business metrics enterprises need to manage that complexity with confidence.

This allows organizations to deploy agentic automation at scale across their enterprise, with the ability to review and approve agents before deployment, track performance against KPIs, and take corrective action in real time, including pausing or adjusting agents based on metric thresholds, guardrail violations, or business impact. Built to ensure trust, accountability, and measurable business value, Control Tower enables organizations to actively manage their agent ecosystem, not just monitor it.

Scaling Agents to Power the Agentic Enterprise

As part of the Enterprise Agent Mesh, Hyland unveiled Agent Lifecycle Management, a framework that spans an enterprise agent’s existence from design through retirement. The framework is built to solve a core enterprise challenge: scaling agentic automation without forcing organizations to choose between automation and oversight. Hyland’s approach establishes a governed environment where organizations can scale an agent fleet while preserving accountability.

Key components include:

  • Agent Passport: Standardized certification every agent must hold before it runs in production. Agent Passport defines the agent’s identity, capabilities, guardrails, and compliance status in a format that is both human-readable and machine-enforceable, applying governance before deployment.
  • Agent Library: A governed, searchable catalog of every agent in the organization’s ecosystem. Agent Library tracks what agents exist, who owns them, what they do, and their version history, helping prevent duplication and sprawl as the agent fleet grows.
  • Base agents: The Agent Library comes with ready-to-use base agents and agent archetypes including orchestration, document, and task agents. These base agents simplify enterprise AI adoption by combining intelligent automation with human-in-the-loop oversight, enabling organizations to deploy trusted agentic workflows with confidence.

Bringing Hyland’s AI‑Native Content and Data Fabric to an Open Ecosystem

Hyland debuted headless mode, a new capability that exposes the AI‑native data and content fabric in the Content Innovation Cloud as consumable APIs. With this headless mode, customers and partners can embed Hyland’s content, context, and governance capabilities directly into their own applications, third‑party AI solutions, and custom workflows, without relying on Hyland’s user experience.

This makes the Content Innovation Cloud available to an open source ecosystem, enabling organizations to integrate governed content intelligence wherever work happens. It also expands Hyland’s reach to data engineering teams, ISVs, and platform ecosystems such as Databricks and Snowflake, where customers may not adopt a frontend solution but will invest in the developer‑first foundation of AI‑ready data, contextual understanding, and decisioning intelligence that powers content‑driven agentic enterprise.

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Apex Lubrication LLC Chooses Solace to Bring Real-Time AI Intelligence to Industrial Conveyor Operations

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Apex Lubrication LLC Chooses Solace to Bring Real-Time AI Intelligence to Industrial Conveyor Operations

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Integrating OmniView Platform with Solace Agent Mesh will deliver predictive maintenance, automated reporting and centralized visibility across client manufacturing facilities

Solace, the real-time data platform for the agent-native enterprise, announced that Apex Lubrication LLC, a leader in conveyor lubrication, chain monitoring and plant reliability, together with its long-standing partner Mighty Lube, will deploy Solace Agent Mesh across its OmniView machine learning platform to help customers monitor conveyor health, reduce unplanned downtime and move critical operational data in real time.

For more than 40 years, some of the world’s leading automotive manufacturers and large-scale production facilities have turned to Mighty Lube for proven conveyor maintenance, lubrication, and monitoring solutions. Apex recently unveiled the next generation of enterprise conveyor intelligence through its OmniView platform, designed to give manufacturers a centralized view of chain performance, lubrication health, wear trends, and maintenance priorities.

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By integrating Solace’s real-time data and agentic AI capabilities into OmniView, Apex and Mighty Lube are transforming how conveyor data flows and decisions are made, delivering:

  • Real-time alerts that notify maintenance personnel the moment a conveyor system shows signs of wear, lubrication failure, or abnormal operating conditions
  • On-premises LLM orchestration that enables AI-driven analysis and decision support without requiring cloud connectivity, an important consideration for secure, regulated manufacturing environments
  • Automated reporting that delivers maintenance summaries, trend analysis, and performance metrics directly to the teams and systems that need them
  • Intelligent data movement that connects OmniView insights to broader enterprise platforms, from ERP and CMMS systems to facility dashboards, ensuring the right information reaches the right people at the right time

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“Our customers have relied on Apex and Mighty Lube to keep their conveyor systems running. With Solace Agent Mesh, we’ve taken the OmniView platform to an entirely new level, delivering intelligence that helps manufacturers make smarter and faster decisions,” said Anthony P. Brown, Founder and Vice-President, Apex Lubrication LLC.  “This is the kind of real-time operational visibility that the industry has been moving toward. Maintenance teams gain confidence in the data they’re acting on, and plant operators gain a clearer picture of facility-wide reliability.”

“Apex Lubrication has the domain expertise, the hardware, and the machine learning platform; what they needed was a real-time, event-driven solution that could move data intelligently across systems, both in the cloud and on-premises,” said Paul Fitzpatrick, Chief Marketing and Business Development Officer, Solace. “We’re proud to see Apex and Mighty Lube invest their trust in Solace Agent Mesh to power real-time conveyor intelligence for some of the world’s most demanding production

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PubMatic Launches Decision Fabric on AgenticOS, Giving Partner Decision Models a Native Environment Inside the Programmatic Supply Path

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PubMatic Launches Decision Fabric on AgenticOS, Giving Partner Decision Models a Native Environment Inside the Programmatic Supply Path

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inPowered AI, MiQ, Chalice AI and SWYM.AI to Pilot New Capability, Running Buyer and Algorithm Intelligence Inside the Auction Alongside PubMatic’s Active AI Agents

PubMatic, the leading AI-powered ad tech company delivering digital advertising performance, announced Decision Fabric, a containerization layer built on AgenticOS that runs partner decisioning models natively inside the programmatic supply path. Piloting with inPowered AI, MiQ, Chalice AI and SWYM.AI as first partners, Decision Fabric enables audience qualification to happen at the exact moment of the auction, on live signals, across the full unfiltered inventory pool, allowing advertisers to reach higher-value audiences more efficiently and directly.

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“Advertising works best when advertisers and publishers work closely together,” stated Rajeev Goel, Co-Founder and CEO, PubMatic.

According to the ANA’s Programmatic Media Supply Chain Transparency Study (December 2023), working media efficiency ranges from as low as 36 cents on the dollar, a gap that has driven advertisers toward supply-side solutions with greater transparency and direct access to inventory. PubMatic’s Activate has been a proven answer to that problem: a direct-to-supply media activation tool that has operated as a native bidder on the sell side for years, demonstrating that running decisioning natively inside the auction, on live signals, delivers better economics for buyers and publishers alike. Decision Fabric opens that same architecture to PubMatic’s partners, giving their decisioning models a native environment inside the same auction infrastructure that has powered Activate’s results. It is a proven architectural advantage, now extended to the broader ecosystem.

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“Advertising works best when advertisers and publishers work closely together,” stated Rajeev Goel, Co-Founder and CEO, PubMatic. “Decision Fabric builds on our success with Activate and gives partner intelligence a native environment inside the supply path where signals are most complete, inventory scale is greatest, and AgenticOS agents are already at work. The longer partner models run here, the smarter the whole system gets, and the more value flows back to buyers and publishers alike.”

Through Decision Fabric, partner decisioning models, from algorithm companies, curators, agencies, and DSPs alike, run inside PubMatic’s auction infrastructure on live bidstream signals at the exact moment inventory becomes available. Audience qualification happens in real time, across the full unfiltered inventory pool, before traffic shaping occurs. For DSPs in particular, Decision Fabric represents a direct entry point into AgenticOS, with the ability to run their decisioning logic inside an environment where PubMatic’s own agents are already operating and can actively call on it. If a DSP deploys an audience model via container, PubMatic’s inventory and audience agents can invoke that model directly to sharpen campaign targeting or surface higher-value deals.

Connecting Decision Fabric to AgenticOS provides partners with access to the full weight of the infrastructure and intelligence behind PubMatic’s operating system for agentic advertising. This includes GPU-accelerated computing and dedicated AI inferencing servers purpose-built for advertising’s microsecond decisioning requirements, operating at approximately one millisecond inference latency with 85% fewer auction timeouts, as well as more than 20 autonomous agents and 1,000 AI-powered deals already active across discovery, deal management, and optimization — working across 2.7 trillion advertiser bids per day and 100,000+ streaming channels, apps, and websites globally, including 28 of the top 30 streaming platforms. Decision Fabric is built using the IAB Tech Lab’s ARTF open containerization protocol, enabling partners to deploy once on a standard architecture and operate across PubMatic’s full supply footprint without proprietary lock-in.

“We’ve always known that better signals produce better outcomes,” said Georgiana Haig, Global Strategy & Partnerships Director, MiQ. “The promise of Decision Fabric is that it gives us the ability to act on those signals at the moment they matter most right at the auction, across the full pool of available inventory. For our clients, that translates directly into campaigns that reach the right people with more of their budget channeled into media and not fees.”

The piloting partners each bring distinct decisioning capabilities to Decision Fabric at launch. inPowered AI’s models qualify outcomes against live bidstream signals at auction speed, reflecting real-time outcomes rather than pre-built segments. MiQ brings buyer-side trading intelligence inside the supply path, giving one of the world’s largest independent trading desks a native environment to optimize outcomes at the moment inventory is available. Chalice AI brings proprietary custom algorithms trained on advertiser-specific outcomes data, replacing platform-default AI with decisioning logic built exclusively around each brand’s business goals, and SWYM.AI’s algorithm applies real-time inventory curation and bid optimization directly against PubMatic’s full supply footprint, enabling advertisers to concentrate spend on their highest-performing inventory.

“The containerized environments enable impression-level decisioning across the entire exchange,” stated Peyman Nilforoush, Co-Founder and CEO, inPowered. “PubMatic’s Decision Fabric enables us to host our models on the sell-side with the strongest signals for outcomes all done prebid. Having AgenticOS operating in the same environment as our models means the whole system is working together, and that’s something we haven’t had anywhere else.”

“Chalice builds some of the most advanced algorithms for agentic advertising in the market today,” said Adam Heimlich, CEO, Chalice AI. “But an algorithm is only as powerful as the environment it runs in. Decision Fabric gives our models access to the full inventory pool, live signals at the moment of the auction, and an agentic infrastructure that can act on what our models surface in real time. That’s what turns a great algorithm into measurably better outcomes for buyers.”

“The buy side has been optimizing against a filtered view of supply for a decade,” stated Ravi Patel, CEO, SWYM.AI. “Decision Fabric flips that — our algorithms now run where the inventory actually lives, on every bid request, in the moment it matters. That’s outcome-driven bid shaping at full supply-side scale, and there’s no equivalent of it on the buy side of the fence.”

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Hightouch Launches Exposure Log Matching for The Trade Desk

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Equiniti Launches Real Time Analytics, First UK Registrar to Offer Immediate Share Ownership Visibility

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Advertisers and media networks can now tie campaign exposure directly to their own consented customer and household records, delivered straight to the warehouse without an intermediary identity layer.

Hightouch, the leading Composable CDP and Agentic Marketing Platform, announced Exposure Log Matching for The Trade Desk. The new Match Booster capability resolves The Trade Desk’s Raw Event Data Stream (REDS) logs directly to a brand’s own customer and household IDs, landing the data in the customer’s warehouse for measurement, reporting, and AI analysis.

The Trade Desk gives advertisers a detailed record of every impression, click, and conversion, along with metadata like placement, ad dimension, frequency, and more. But those events arrive behind anonymous identifiers like UID2s, mobile device IDs, and cookies. Until they resolve to consent to customer records, the data describes a campaign, not a customer journey.

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The industry has historically closed that gap with third-party identity providers. A brand exports the logs, ships them to a vendor, waits several days, and receives a file back keyed to a proprietary ID. More engineering follows to translate that vendor ID into the customer model. The workflow is slow, fragmented, and built on identifiers the brand does not own.

Exposure Log Matching removes the intermediary. Match Booster combines first-party signals with Hightouch’s identity graph in a priority waterfall, then delivers logs into the warehouse keyed to the customer’s own consented customer or household IDs. Logs are delivered daily or hourly, often with higher match rates than third-party-only approaches.

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“Measurement should run on the enterprise’s own identity model, not a vendor’s proprietary ID,” said Ian Maier, General Manager of AdTech at Hightouch. “Exposure Log Matching gives brands and media networks control over the bridge between ad exposure and business outcomes.”

Once resolved, exposure logs land in the warehouse, teams can run cross-channel attribution and incrementality, analyze performance by customer segment or SKU, build embedded reporting for advertisers, and give Hightouch agents the context to reason across performance, customer, and outcome data.

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Taggbox Reinvents the Social Media Widget Experience for Businesses Seeking Higher Website Conversions

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Taggbox Reinvents the Social Media Widget Experience for Businesses Seeking Higher Website Conversions

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Taggbox introduces advanced social media widget capabilities designed to help brands drive higher engagement and website conversions.

Taggbox introduces an enhanced Social Media Widget solution designed to help businesses transform social content into engaging website experiences that drive trust, engagement, and conversions.

Taggbox, a leading social media aggregation and UGC platform, today announced significant enhancements to its Social Media Widget solution, empowering businesses to seamlessly embed social media content on their websites and create more engaging digital experiences.

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As consumers increasingly rely on authentic content and peer recommendations before making purchasing decisions, businesses are looking for effective ways to showcase social proof directly on their websites. The Taggbox Social Media Widget enables brands to collect, curate, customize, and display social media content from multiple platforms, helping them build trust while improving website performance.

According to industry research, user-generated content and social proof have become essential components of modern digital marketing strategies. By bringing social media content directly to websites, businesses can create dynamic experiences that keep visitors engaged and encourage meaningful interactions.

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“Our goal has always been to help businesses leverage the power of social content beyond social platforms,” said a spokesperson for Taggbox. “The enhanced Social Media Widget makes it easier than ever for brands to showcase authentic customer experiences, increase visitor engagement, and create stronger connections with their audiences.”

Helping Businesses Turn Social Content Into Business Results

The Taggbox Social Media Widget is designed to address one of the biggest challenges businesses face online: building credibility and trust quickly.

With the platform, businesses can:

Display social media feeds directly on websites
Showcase user-generated content from customers
Highlight customer experiences and brand mentions
Create visually engaging social galleries
Keep website content fresh with automatic updates
Improve visitor engagement through authentic social proof

The solution supports content aggregation from leading social media platforms, allowing brands to create centralized social experiences without requiring complex technical implementation.

Designed for Marketers, E-Commerce Brands, and Growing Businesses

The updated Social Media Widget serves a wide range of industries and use cases, including:

E-commerce websites seeking to increase conversions
SaaS companies looking to build trust with prospects
Hospitality and travel businesses showcasing customer experiences
Educational institutions highlighting community engagement
Agencies managing social proof campaigns for clients
Corporate websites seeking dynamic and authentic content

By integrating social content into the customer journey, businesses can create more engaging website experiences while strengthening their overall digital presence.

Enhanced Customization and Performance

Taggbox continues to focus on providing businesses with flexibility and control over how social content appears on their websites.

The platform offers customization capabilities that allow users to align social feeds with their website branding, layouts, and design preferences. Advanced moderation tools help ensure that displayed content remains relevant, professional, and aligned with brand guidelines.

The latest improvements also emphasize website performance, helping businesses deliver engaging social experiences without compromising speed or user experience.

Meeting the Growing Demand for Authentic Digital Experiences

As digital competition continues to intensify, consumers increasingly favor brands that showcase real customer experiences over traditional promotional messaging.

Social Media Widgets have emerged as a practical solution for businesses looking to bridge the gap between social engagement and website conversions. By embedding authentic social content directly into their websites, brands can create stronger trust signals and provide visitors with valuable social proof at critical decision-making moments.

Taggbox believes this shift toward authenticity will continue to shape the future of digital marketing, making social content integration an essential component of website optimization strategies.

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TwelveLabs Bring Its Video Understanding Technology Directly to Creators

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TwelveLabs Bring Its Video Understanding Technology Directly to Creators

TwelveLabs Launches Ecosystem Partner Program to Extend Video Intelligence in the Enterprise

Company introduces Rodeo, an AI-powered creative copilot that transforms raw video footage into finished stories in minutes

TwelveLabs, the video understanding company, today announced the availability of its newest innovation: Rodeo. As TwelveLabs’ first application-layer product. Rodeo brings AI agents directly into video production workflows, enabling creators to find, edit and assemble footage using natural language. The release marks the company’s evolution from a pure infrastructure provider to a company also building tools that put its video intelligence directly into the hands of creators.

Rodeo offers a new way of working with video. It lets creators describe what they want, then TwelveLabs’ AI understands and searches their entire footage library to find and assemble the perfect clips instantly. TwelveLabs’ technology is unique in that it knows not just what’s in a creator’s video, but why it matters contextually. With such advanced contextual understanding, TwelveLabs delivers the right footage to creators the moment they need it. This allows them to skip hours of manual searching through footage and instead surface and focus on the exact moments that matter. Creators are free to make the most of existing content and leverage it in new ways– all in a fraction of time they would typically spend sifting through an extensive collection of footage.

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The Agent Moment Has Arrived for Creatives

To this point, AI agents have been hyped ahead of the infrastructure required to deploy them reliably. However, with the emergence of MCP servers and a more mature ecosystem, agents can now be deployed in real production workflows for creatives. TwelveLabs’ Rodeo delivers a finished product for end-users that bypasses traditional IT infrastructure entirely, enabling creators to work with advanced video intelligence without technical setup or integration.

For producers, editors, creative directors, documentarians, directors and more, Rodeo is like having an assistant who has watched everything in their video archive before serving it up within the workflow. This lets users spend more time creating and less time searching.

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Building on Excellence and Innovation

As the first end-user application for TwelveLabs, Rodeo is the natural progression for the company, having already established its leadership at the model layer. TwelveLabs introduced the world’s most powerful video understanding model with Marengo 3.0, which treats video as a living, dynamic system. It compresses audio, text, movement, visuals and context into something that can be searched, navigated and understood at scale; it doesn’t just watch video, it reads it, hears it and picks up on the rhythm of a scene.

Marengo 3.0 works in conjunction with TwelveLabs’ Pegasus 1.5 model, which achieves state-of-the-art performance in long video understanding. The model can support videos that are up to one hour long with best-in-class accuracy while also maintaining low latency and competitive pricing. Twelve Labs’ Pegasus foundation model was built to generate text descriptions about a video, understanding its content through analysis of both visual and audio elements. Together, these models power Rodeo’s ability to understand, search and assemble video at a level not possible with traditional tools.

“We’ve shown what is possible for the enterprise and businesses across a wide range of verticals at the model and infrastructure layer through Marengo and Pegasus. Now we’re opening another door,” said Jae Lee, CEO and founder of TwelveLabs. “Video is inherently a creative medium, so we wanted to deliver all of the foundation model power and innovation directly into creative workflows without any technical barriers. We’ve accomplished this with Rodeo, empowering creators to move from raw footage to finished stories faster than ever before.”

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PFU America, Inc. Unveils PaperStream® AI to Transform Document Capture with Intelligent Automation

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New AI-powered extension enhances PaperStream Capture Pro and Pro Premium to deliver fast, more accurate data extraction and workflow efficiency

PFU America, Inc., the U.S.-based subsidiary of PFU Limited and the leader in document scanning solutions, announced the launch of PaperStream® AI, a powerful new AI-driven extension to its flagship PaperStream Capture Pro and Pro Premium software suite. Designed for organizations managing high volumes of business-critical documents, PaperStream AI introduces intelligent automation that streamlines document capture from multiple sources, improves data accuracy, and accelerates the flow of information into downstream systems.

“With PaperStream AI, we are helping our customers move beyond entry-level digitization to truly intelligent document workflows by reducing manual effort, improving data quality, and enabling faster, more confident decision-making,” said Satoshi Kubo.

As enterprises continue to face increasing pressure to process information faster and more accurately, traditional document workflows, which are often reliant on manual setup, template creation, and verification, have become a barrier to efficiency. PaperStream AI addresses these challenges by applying advanced AI capabilities to automatically recognize, clarify, and extract data from a wide range of document types with minimal configuration or re-architecting existing systems.

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PaperStream AI enhances the capabilities of PaperStream Capture Pro and Pro Premium by enabling horizontal and process-driven organizations and departments to move beyond basic scanning and OCR toward fully automated, intelligent workflows. The new solution converts content from incoming business documents—from invoices and purchase orders to healthcare forms and logistics documents—into structured, usable data that can drive business operations and analytics.

PaperStream AI is ideal for data-intensive environments across finance, mailrooms, logistics, and business process outsourcing (BPO), where speed, accuracy, and efficiency are critical. By transforming document-based information into structured, AI-ready data, organizations can support use cases such as automation validation, compliance workflows, and retrieval-augmented generation (RAG) systems.

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“Deploying AI technologies in business systems must deliver real, measurable value in everyday work,” said Satoshi Kubo, President and CEO, PFU America, Inc. “With PaperStream AI, we are helping our customers move beyond entry-level digitization to truly intelligent document workflows by reducing manual effort, improving data quality, and enabling faster, more confident decision-making.”

Key features and benefits of PaperStream AI include:

  • AI-powered document recognition from the first scan: Automatically identifies and processes diverse document types without manual template setup, enabling immediate deployment and faster time to ROI.
  • Advanced data extraction with 99.99%1 recognition accuracy: Uses AI-driven interpretation, including index-level prompting and line-item extraction, to capture structured data from complex and unstructured documents.
  • End-to-end workflow automation: Combines capture, recognition, and verification into a unified process, reducing manual touchpoints and accelerating document processing that allows for 98%2 faster turnaround from end-to-end automation.
  • Operational visibility through an intuitive dashboard: Provides real-time insights into processing activity, accuracy, and performance, helping organizations optimize workflows and improve outcomes.
  • Flexible, scalable deployment: Supports incremental adoption from departmental use to enterprise-wide rollout, with low-code integration into existing systems and workflows.

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Iveda Launches Real-Time Zero-Shot AI Detection, Enabling Users to Instantly Build Custom AI Models With a Single Prompt

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New capability gives retailers an instant AI model for shoplifting, loss prevention, and more — activated in seconds with a single prompt

Iveda® a global leader in AI-driven video analytics and smart city technologies, announced a major advancement within its IvedaAI platform: real-time zero-shot AI detection powered by natural language prompts. For the first time, retailers and security operators can type a single word or phrase — “shoplifting,” “suspicious behavior,” or “graffiti” — and instantly activate a custom AI detection model that begins analyzing live video feeds on the spot, with no model training, data labeling, or deployment lag required.

The announcement marks a fundamental shift in how AI-powered video surveillance works. Traditionally, building a detection model required extensive datasets, weeks of training, and significant technical resources. With IvedaAI’s new capability, that process is compressed to seconds. The moment a user submits a prompt, a custom AI model is constructed in real time and immediately applied to live or recorded video — turning a natural language instruction into an active, accurate detection engine.

“This is the greatest leap forward yet in real-time AI video analytics,” said David Ly, CEO and Founder of Iveda. “For years, building an AI detection model meant collecting data, labeling it, and waiting. Now, a retailer can type ‘shoplifting’ and, in seconds, have a fully functioning AI model running live across their camera network. That’s never been possible before — and the accuracy of what we’re detecting is remarkable.”

A Game-Changer for Retail Loss Prevention

Shoplifting has long been one of the most difficult behaviors to address through traditional AI surveillance. It manifests in countless forms — concealment in bags, pockets, clothing, or carts — across a wildly diverse range of individuals and store environments. No training dataset could ever completely capture every variation, which made automated detection unreliable at best.

IvedaAI’s zero-shot approach sidesteps that problem entirely. By leveraging advanced Vision Language Models (VLMs) alongside Iveda’s decade of pre-trained object detection models, the platform can interpret the intent and context behind behaviors, not just the static objects in frame. The capability is already being evaluated with one of the world’s largest fast-fashion retailers – with thousands of store locations across more than 90 countries – to address loss prevention at scale.

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In early testing, retailers saw immediate results. A prompt of “suspicious behavior” successfully flagged individuals peeking into windows and people repeatedly scanning staff-only entry points — demonstrating the system’s ability to detect intent-driven, pre-incident activity that would have been invisible to conventional analytics.

Additional retail-relevant detections now available via live prompt include:

  • Shoplifting across diverse concealment methods
  • Suspicious or pre-incident behavior
  • Loitering in sensitive areas
  • Graffiti attempts and vandalism indicators
  • Smoking in restricted zones
  • Fighting or aggressive conduct

All detections are available immediately upon prompt submission, directly within a retailer’s existing IvedaAI dashboard — no new login, no new infrastructure required.

Marketing Technology News: Idle data is as good as no data

How It Works: Two Deployment Options

IvedaAI’s real-time zero-shot detection is available through two pathways, designed to meet retailers’ varying security and infrastructure needs:

  • Cloud-Connected Mode: Users can connect to large language model processing for live frame analysis without investing in additional on-site hardware. Ideal for organizations looking for rapid activation.
  • Local Secure Deployment (Cosmos-Reason Engine): For retailers requiring closed-network environments, Iveda deploys a dedicated on-premise server powered by its proprietary Cosmos-Reason engine. This option ensures zero open ports and fully local processing — delivering the full power of real-time AI analysis without any cloud dependency. Iveda will begin shipping the next-generation Cosmos-Reason-2 engine within the coming quarter, further enhancing inference performance and detection accuracy.

Built on a Decade of AI Expertise

As a platform that has spent more than ten years developing and refining AI object detection—including weapons recognition, license plate identification, and facial recognition—Iveda is uniquely positioned to deploy zero-shot AI at scale. The new capability layers advanced VLM reasoning on top of that proven foundation, enabling detection performance that holds up in low-light, crowded, and complex retail environments.

“We’ve always been committed to staying at the cutting edge,” added Ly. “We’re already integrating the latest frameworks from NVIDIA and are continuously future-proofing the platform. What we’re announcing today is the result of years of foundational work meeting this new wave of AI capability — and retailers are going to feel the difference immediately.”

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Vyond Appoints SaaS Industry Veteran Scott Ernst as Chief Executive Officer

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Business Wire
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Vyond Appoints SaaS Industry Veteran Scott Ernst as Chief Executive Officer

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Gary Lipkowitz transitions to Vyond’s Board of Directors as the company expands its AI-powered enterprise communications platform and accelerates its next phase of enterprise growth

Vyond, a leading enterprise video creation and communication platform, trusted by more than 17,000 customers worldwide, announced the appointment of Scott Ernst as Chief Executive Officer. Scott succeeds Gary Lipkowitz, who will transition to Vyond’s Board of Directors and continue to play an active role in guiding the company’s long-term strategy.

Vyond has appointed Scott Ernst as Chief Executive Officer to lead its next phase of growth. Trusted by more than 17,000 customers worldwide, Vyond is accelerating its enterprise strategy and expanding its AI-powered platform for business communication.

Scott brings more than 20 years of experience leading and scaling high-growth SaaS and technology companies from early stage through IPO and exit. He has built and transformed organizations across product innovation, go-to-market execution, and operational performance, including chief executive roles at Compete, Macromill and Drift. Throughout his career, Scott has helped companies accelerate growth, strengthen operational discipline, and navigate periods of significant market and technology change.

Marketing Technology News: MarTech Interview with Theresa Pham, Head of Product @ Wayvia

This leadership transition marks the next chapter in Vyond’s evolution as the company accelerates its enterprise strategy and expands its AI-powered enterprise communication platform. Vyond has helped organizations create over 40 million videos across training, HR, sales enablement, compliance, customer education, and internal communications.

“Scott is exactly the kind of leader Vyond needs for its next phase of growth,” said Matt Melymuka, Managing Partner at PeakSpan Capital and Board Member at Vyond. “He combines operational discipline with deep enterprise SaaS experience and a strong understanding of how to scale organizations through transformations. Just as importantly, Scott recognizes the incredible foundation Gary and the team have built over the last eight years. We believe his leadership will help guide Vyond through its next era of innovation and growth.”

Marketing Technology News: Idle data is as good as no data

Under Gary Lipkowitz’s leadership, Vyond evolved from a B2C animation platform into a trusted AI-powered enterprise solution used by organizations around the world to power training, onboarding, enablement, and communication workflows. During his tenure, the company significantly expanded its enterprise footprint, product and agentic capabilities, and operational scale.

“I’m looking forward to this next evolution of Vyond,” said Lipkowitz. “I am deeply committed to Vyond’s future and incredibly excited about the opportunities ahead. Scott brings the operational leadership, enterprise mindset, and scaling experience needed for our next chapter, and I look forward to partnering closely with him and the leadership team from the Board.”

Ernst said, “What drew me to Vyond was the combination of a proven customer base, a platform genuinely embedded in how large organizations operate, a strong team with deep experience and a product roadmap with real AI-driven upside. The next wave of enterprise AI isn’t just about creating content — it’s about helping organizations operationalize knowledge and workflows at scale. That’s a specific and executable opportunity, and I’m focused on translating it into durable growth.”

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Fingerprint Launches Automation Intelligence API and AI Assistant Detection, Delivering the Industry’s Most Complete View of AI Traffic

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Fingerprint Launches Automation Intelligence API and AI Assistant Detection, Delivering the Industry's Most Complete View of AI Traffic

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Fingerprint, a leader in device intelligence, launched the preview release of AI Assistant Detection and the Automation Intelligence API, delivering the market’s most comprehensive identification layer for AI traffic. AI Assistant Detection provides businesses with verified, real-time visibility into traffic from the world’s leading AI assistants, including OpenAI’s ChatGPT, Google’s Gemini, and Anthropic’s Claude. This is powered by the new Automation Intelligence API, Fingerprint’s platform-agnostic, edge-ready API that identifies automated traffic without requiring any client-side JavaScript.

The launch follows Fingerprint’s February 2026 release of Authorized AI Agent Detection. Together, these capabilities provide the market’s most comprehensive AI traffic identification layer. Businesses can now get a unified view of AI traffic, from agents that take actions on a user’s behalf to assistants that browse and summarize content, ensuring a secure and optimized experience for the AI-native web.

The Web Is Going Browserless

Until recently, most web security and analytics tools were built around a core assumption: that traffic comes from humans opening browsers. JavaScript-based detection worked because that assumption held. It is increasingly not holding.

AI assistants access websites over HTTP, pulling content, summarizing documentation, and conducting research across web properties without ever loading a page. And the shift is accelerating. Google’s Gemini Spark, announced at I/O 2026, runs on dedicated cloud virtual machines — working around the clock without a user ever opening a laptop or browser. OpenAI’s ChatGPT agent and Anthropic’s Claude are doing the same. The AI assistants driving traffic today are the infrastructure of how consumers will navigate the internet tomorrow.

“The web is going browserless — and the pace of that shift is faster than most security stacks were built to handle,” said Valentin Vasilyev, co-founder and CTO, Fingerprint. “Google’s Gemini Spark, ChatGPT, Claude — these assistants are how a growing share of traffic will arrive: no browser, no JavaScript, no traditional signals to rely on. The Automation Intelligence API is Fingerprint looking at where consumer behavior is going and building the intelligence layer that meets traffic where it actually is. The question is no longer ‘Is this a bot or a human?’ It’s ‘Can I trust this visitor, whoever it is?’ Fingerprint now gives businesses a verified answer.”

Verified Identity for AI Assistant Traffic

Traditional bot detection relies heavily on JavaScript, which most AI assistants don’t execute, creating a major blind spot for security and growth teams. Malicious actors have taken notice. Scrapers and low-quality bots have learned that spoofing the user-agent of a popular AI assistant is a fast pass through many bot defenses because operators don’t want to risk blocking legitimate assistant traffic and cutting themselves off from a valuable new discovery channel.

Fingerprint’s AI Assistant Detection closes that gap by operating at the HTTP level rather than relying on browser-based signals. This gives businesses real-time visibility into which AI tools are accessing their content, and flag impersonators before they can scrape data or skew analytics.

Marketing Technology News: MarTech Interview with Theresa Pham, Head of Product @ Wayvia

Powered by the Automation Intelligence API

Fingerprint’s AI Assistant Detection is built on the new Automation Intelligence API, built for a web increasingly shaped by AI assistants, AI agents, bots, and other automated systems. For the first time, Fingerprint delivers its full automation intelligence without requiring any JavaScript on the client. The API is deployable at the CDN edge, in middleware, or on any backend, on any cloud platform — wherever a request arrives, before the customer’s application ever sees it.

The API delivers not just a verdict but context: alongside every automation classification, it provides rich IP and network risk intelligence — including proxy, VPN, TOR, and geolocation signals — so security and product teams can make nuanced, real-time decisions at the point where traffic enters their stack. Block, throttle, step up, or allow — with full context, not just a flag.

Marketing Technology News: Idle data is as good as no data

“AI assistants like ChatGPT and Claude are rapidly becoming the primary way users navigate the web, but many security stacks still treat them like an edge case. Fingerprint’s approach gives enterprises real-time visibility into AI traffic without relying on browser signals,” said Todd Thiemann, principal analyst at Omdia. “For teams trying to protect content, reduce fraud, and still embrace AI as a discovery channel, this kind of foundational capability will quickly move from ‘nice to have’ to ‘essential.’”

Key Features and Benefits

  • Verified Identification: Distinguishes real ChatGPT, Gemini, and Claude traffic from spoofed AI assistant traffic in real time.
  • HTTP-Level Detection: Reaches AI assistants that bypass JavaScript-based detection, filling a massive blind spot in current security stacks.
  • Unified AI Classification: Clearly identifies which AI assistant is accessing content, including provider and assistant type.
  • Automation Intelligence API — No JavaScript Required: The engine behind AI Assistant Detection and the foundation of Fingerprint’s AI-native detection platform. A platform-agnostic, edge-ready API that identifies AI agents, AI assistants, bots, and other automated traffic across websites, APIs, CDNs, and edge environments — without requiring any client-side JavaScript. As AI assistants like Gemini Spark, ChatGPT, and Claude increasingly access the web on behalf of users, the Automation Intelligence API ensures Fingerprint’s intelligence works wherever requests arrive.
  • Actionable Intelligence: Enriches every detection with IP and network risk context — proxy, VPN, TOR, geolocation — so teams can apply nuanced policies rather than blunt blocks.
  • Seamless Integration: Available at no additional cost to existing Fingerprint customers using the Bot Detection Smart Signal.

AI Assistant Detection is currently available in preview to a select group of Fingerprint customers. Support for Microsoft’s Copilot, xAI’s Grok, and OpenClaw is next on the roadmap.

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

FreeCast Launches Multi-City Advertising Campaign Through Agreement with New to The Street

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Business Wire
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FreeCast Launches Multi-City Advertising Campaign Through Agreement with New to The Street

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Campaign Includes Times Square Videos, Billboards and Taxi Top Placements Across Key U.S. Markets

FreeCast, a digital streaming platform and technology company, announced the launch of a new multi-city advertising campaign in coordination with New to The Street TV featuring video billboards and taxi top media placements designed to increase public visibility of the FreeCast brand and its streaming platform technologies.

The campaign includes outdoor advertising placements across multiple metropolitan markets in the United States, utilizing high-traffic metropolitan locations as part of a broader brand awareness initiative.

According to the companies, the campaign is intended to increase exposure for FreeCast’s consumer streaming ecosystem and commercial platform offerings, including its Platform-as-a-Service (PaaS) infrastructure, FAST channel aggregation technologies, and related streaming solutions.

Marketing Technology News: MarTech Interview with Theresa Pham, Head of Product @ Wayvia

Advertising creative associated with the campaign highlights several FreeCast platform initiatives, including:

  • BEST (Broadcast Enabled Streaming Television)
  • Zer0Gap advertising technologies
  • RSSC (Regional Streaming Sports Channels)
  • PaaS (Platform-as-a-Service) FreeCast’s white-label all-in-one streaming media platform services for broadband, telecom, and media partners

The campaign is being distributed through media inventory coordinated by New to The Street, which provides televised business programming, digital media-based outdoor advertising placements, and public market brand awareness services.

Marketing Technology News: Idle data is as good as no data

William Mobley, Chief Executive Officer of FreeCast, stated:

“This campaign represents an opportunity to expand public visibility surrounding the FreeCast platform and its growing ecosystem of streaming and advertising technologies. Through this agreement with New to The Street, FreeCast is participating in a broad consumer-facing media initiative across multiple U.S. markets.”

The companies indicated that campaign placements began rolling out during the current quarter and include rotating video billboard displays and mobile advertising units positioned in high-density traffic corridors and entertainment districts.

FreeCast continues to focus on the expansion of its streaming aggregation technologies, advertising infrastructure, and Platform-as-a-Service capabilities serving broadband providers, telecom operators, sports distribution initiatives, and branded streaming deployments.

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