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Demandbase Debuts Demandbase AI, the Pipeline Engine for Modern GTM Teams

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Demandbase Debuts Demandbase AI, the Pipeline Engine for Modern GTM Teams

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The unveiling of Demandbase AI marks a definitive platform evolution that turns GTM goals into coordinated action across the entire go-to-market

Today at its annual customer conference, GO London, Demandbase set a new standard for the AI GTM era with the debut of Demandbase AI. As the definitive pipeline engine for modern go-to-market teams, Demandbase AI represents a total transformation of the platform, built to help the enterprise scale strategy into measurable pipeline. The debut of this new AI-first experience presents a simplified, conversational interface for orchestrating go-to-market execution across the platform – and is anchored by several key innovations, including a Site Customization Agent, LLM integrations including ChatGPT and Claude, and new capabilities for proving Pipeline Influence.

Today, companies are drowning in GTM signals and struggling to turn insights into outcomes. Demandbase AI uses Context Intelligence—a proprietary layer that applies each company’s unique GTM context—to analyze account signals and patterns against pipeline goals, identifying the opportunities most likely to drive results. Instead of leaving teams to activate the strategy across every channel, Demandbase AI removes the overwhelm by coordinating programs and plays across marketing, sales, and advertising to drive pipeline.

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

“In the rush to adopt AI, the industry is seeing that more data and activity don’t lead to better outcomes,” said Gabe Rogol, CEO of Demandbase. “AI without context creates noise—it requires more oversight and misses what actually matters. Demandbase AI is moving the industry beyond insights and point solutions to a unified system that activates teams, focuses them on what matters, and helps them drive revenue more predictably.”

Built on this foundation, Demandbase AI brings together data, teams, and workflows across native and ecosystem integrations to form a continuous system that:

  • Turns goals into outcomes: Demandbase AI starts with defined outcomes and orchestrates activity across marketing, sales, and advertising at scale.
  • Transforms signals into actionable insights: Filters and prioritizes intent and engagement first- and third-party data to identify accounts most likely to convert.
  • Coordinates cross-channel activations: Turns insights into unified programs and plays across systems.
  • Continuously adapts: Evaluates performance in real-time and refines recommendations to improve results and prove impact.

“Our teams are under incredible pressure to both adopt AI and deliver real pipeline results,” said Ryan Oliver, Director of Enterprise Demand Generation Marketing, SAP Concur. “Demandbase is the first platform we’ve used that actually connects those two. It creates an AI-driven experience that works across our teams, keeps everyone aligned, and measures success based on the pipeline it generates. We’re reducing wasted spend and seeing better outcomes. Demandbase is truly delivering on the promise of AI and driving real business impact.”

Marketing Technology News: From MarTech Stack to MarTech Fabric: Weaving Brand, Content, and Conversion Into One Thread

Intelligent Daily Workflows

To bring this system into how teams work everyday, Demandbase is introducing new capabilities that enable harmonious workflows across the entire go-to-market. From agent interoperability to a robust ecosystem that enables data and tool integrations, Demandbase is extending AI-driven intelligence directly into the solutions teams rely on:

  • LLM Workflow Integration: Demandbase now delivers deep company, contact, technographic, and intent data through Model Context Protocol (MCP), an open standard that enables seamless data interoperability between Demandbase AI and major AI assistants like ChatGPT, Claude, CoPilot, and Gemini.
  • Site Customization Agent: A conversational interface that enables marketers to quickly refine campaign-matched landing pages. By “reading” page and audience context, it will reduce production time from days to minutes while improving conversion and pipeline outcomes, with every recommendation grounded in account and buying group signals.
  • Pipeline Influence measurement: Through Demandbase AI Chat—a chat-based interface that enables prompt-based insights—Pipeline Influence easily moves teams beyond fragmented metrics to show how programs are driving pipeline across the GTM, helping teams scale what’s working.

With these innovations, Demandbase continues to set new standards for what revenue teams can expect from their AI GTM stack: unified data, aligned teams, and predictable pipeline growth at scale. To help the industry keep pace with the speed of AI innovation, Demandbase also launched a new AI GTM Certification program that will empower teams with the strategic framework and technical skills needed to master the AI GTM era. The company’s leadership in unifying complex GTM motions was recently recognized by Forrester Research, naming Demandbase a Leader in both The Forrester Wave™: Marketing and Sales Data Providers for B2B, Q1 2026 and The Forrester Wave™: Revenue Marketing Platforms for B2B, Q1 2026. Demandbase is the only company recognized as a Leader in both reports.

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MarTech Acquisition: Viant to Acquire TVision

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MTS Staff Writer
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MarTech Acquisition: Viant to Acquire TVision

The acquisition will allow Viant to deliver advertisers an unbiased view of the TV landscape and a clearer path to results

Viant Technology, a leader in CTV and AI-powered programmatic advertising, announced it has entered into a definitive agreement to acquire TVision Insights, the only attention measurement provider delivering second-by-second, eyes-on-screen attention, co-viewership and in-room presence for TV.

With this acquisition, Viant strengthens its AI-powered programmatic platform by integrating TVision’s proprietary attention signals directly into its buying platform. Combined with Viant’s Household ID and IRIS_ID, TVision adds three new critical signals to Viant’s Intelligence Layer, creating a continuous feedback loop where viewer engagement flows directly into planning, buying, optimizing, and measuring advertising campaigns.  This creates an unprecedented level of granularity across TV at the network, CTV app, show, scene, pod, and spot level– delivering immediate improvements in inventory valuation, bidding precision, and return on ad spend, exclusively within the Viant platform.

Marketing Technology News: MarTech Interview with Haley Trost, Group Product Marketing Manager @ Braze

“Every advertising platform measures its own performance today, which makes it difficult for advertisers to understand what’s actually working. With TVision, we are providing advertisers a true market-wide view of how their advertising performs, free from any platform’s self-attribution bias.  While our competitors measure themselves, Viant measures the market,” said Tim Vanderhook, CEO and Co-Founder of Viant. “Advertisers can now use attention, co-viewing and in-room signals within Viant’s AI-powered buying platform giving them unparalleled strategic advantages, including a first-of-its-kind metric: the attention-adjusted CPM.”

Television advertising today spans linear, Google’s YouTube, Amazon’s Prime Video, and streaming platforms across the open internet. Yet each platform largely measures its own performance, leaving marketers without an objective, unbiased view of how their total advertising investment actually performs. TVision’s nationally representative panel uses advanced computer vision and Automatic Content Recognition technology to capture genuine viewer engagement across this entire ecosystem — giving advertisers a single, independent view of attention and enabling them to optimize spend toward impressions that are actually seen.

“TVision was built to provide a more accurate and transparent view of how people engage with television and streaming content,” said Yan Liu, CEO and Co-Founder of TVision. “By joining Viant, we can bring our measurement capabilities together with real-time activation and AI-powered optimization, helping advertisers turn attention insights into superior campaign performance.”

The result is the trifecta TV advertisers have long been waiting for: identity, context, and verified attention unified in one independent platform, free from the conflicts of walled garden inventory — enabling advertisers to confidently direct spend toward the ad inventory that truly performs and delivers optimal outcomes.

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Pursuant to the definitive purchase agreement, Viant will purchase TVision for a total consideration of $40.0 million, subject to customary adjustments and hold-backs.  The consideration consists of $22.5 million in cash and $17.5 million of shares of Viant’s Class A common stock delivered at closing.  The transaction is expected to close in April 2026, subject to customary closing conditions.

Viant Technology Inc. (NASDAQ: DSP) is an exclusively buy-side advertising platform powered by artificial intelligence and designed to drive performance across the open internet. Our omnichannel platform purpose-built for CTV turns data and intelligence into scalable, measurable performance for advertisers. With the launch of ViantAI and Outcomes, Viant has been at the forefront of AI innovation in advertising, building the future of fully autonomous solutions. Viant has been recognized for excellence in AI by Adweek, the Business Intelligence Group and MarTech Breakthrough and is Great Place to Work® certified.

TVision provides second-by-second, person-level data about how people watch TV — measuring who is watching, what they are watching, and how much attention they are paying across linear and streaming environments.

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SamsonPR Launches AI Visibility Index™ to Help Tech Companies Win in AI-Driven Buyer Discovery

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Globe Newswire
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Robutler Launches Unified Infrastructure Platform for AI Agent Commerce

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New offering measures how companies appear, rank and are recommended across AI platforms increasingly used for search and vendor research

SamsonPR, the growth public relations agency focused on B2B technology marketplace visibility, influencer engagement and demand acceleration, today announced the launch of the SamsonPR AI Visibility Index™, a new proprietary offering designed to help companies understand and improve how they are discovered, described and recommended across AI-powered platforms such as ChatGPT, Google Gemini, Perplexity, Microsoft Copilot and Claude.

As AI platforms rapidly become a primary tool for search, research and vendor discovery, many companies remain unaware of how these LLMs portray their brand, or whether they appear at all.

“AI has quietly become one of the most influential discovery channels in B2B buying,” said Scott Samson, founder and CEO of SamsonPR. “Prospective customers are asking AI tools who the leaders are, what platforms they should evaluate and which companies they can trust. Most companies have no visibility into how those answers are formed, and that’s a massive missed opportunity that is leaving money on the table. Where you show up matters, especially as technology and AI continue to evolve and transform a company’s bottom line.”

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

A New Discovery Problem for B2B Tech Companies
Buyers are increasingly turning to AI platforms early in the decision-making process to learn about market categories, identify leading vendors, compare alternatives and shortlist companies before ever visiting a website.

Unlike traditional search, AI-driven discovery synthesizes narratives from third-party content, authority signals, competitive positioning and category language. As a result, companies may believe they are visible in the market, while AI systems either overlook them, mischaracterize them or position competitors as category leaders.

Introducing the SamsonPR AI Visibility Index™
The SamsonPR AI Visibility Index™ measures how discoverable and recommended a company is when buyers use AI-powered platforms to research solutions within a specific category.

Marketing Technology News: From MarTech Stack to MarTech Fabric: Weaving Brand, Content, and Conversion Into One Thread

Each Index report evaluates:

  • Frequency of AI mentions
  • Strength of AI-generated recommendations
  • Authority signals influencing AI responses
  • Category association and clarity
  • Competitive positioning versus key rivals

Companies receive a percentage-based AI Visibility Index Score, competitive benchmarks and clear recommendations for improving visibility and leadership in AI-driven discovery.

“This isn’t about optimizing for algorithms,” added Samson. “It’s about shaping the narratives AI systems rely on when buyers are deciding who to trust. That’s fundamentally a PR challenge and a PR opportunity. My team is eager and ready to help with that.”

Turning PR Into a Measurable Growth Lever
The SamsonPR AI Visibility Index is now available as a standalone assessment, a recurring quarterly benchmark or as an integrated component of ongoing PR and positioning programs for all prospective and current SamsonPR clients.

By directly tying media strategy, executive visibility and category positioning to measurable improvements in AI discoverability, SamsonPR is helping clients strengthen their influence in the next era of buyer research.

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2X Taps Drew Murphy as Chief Financial and Operating Officer Amid Rapid Growth and Recent Acquisitions

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Globe Newswire
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2X Taps Drew Murphy as Chief Financial and Operating Officer Amid Rapid Growth and Recent Acquisitions

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Seasoned, Philly-based executive joins leadership team to help scale 2X’s integrated GTM engine

2X, a subscription-based go-to-market services partner for B2B organizations, today announced the appointment of Drew Murphy as Chief Financial and Operating Officer. Based at the company’s U.S. headquarters in Greater Philadelphia, Murphy will lead 2X’s newly established finance and operations function and brings an entrepreneurial, operator-style approach to building the infrastructure needed for the company’s continued expansion and momentum. Since the company’s founding in 2017, 2X has achieved an impressive, nearly 70 percent CAGR.

Murphy joins 2X with more than 25 years of experience supporting high-growth companies. A four-time private equity-backed CFO, he is known for hands-on leadership in deal processes, post-deal integration, and scaling financial and operating systems. His background spans finance, operations, administration and mergers and acquisitions, with a track record of designing disciplined operating models that support rapid growth and long-term value creation.

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

In January, 2X added the acquisition of The Kiln, a Clay partner known for advanced GTM engineering capabilities, to its roster of acquired companies. It marks the latest step in strengthening the company’s technology and AI-enabled services.

“Drew understands how to grow companies and brings the financial discipline, operational depth and private equity mindset that matters as we scale,” said Dom Colasante, Founder and CEO of 2X. “He’s led M&A and integration efforts, and his leadership strengthens our ability to evaluate and integrate future opportunities as we continue expanding the 2X platform.”

“2X has built a highly differentiated platform, and the opportunity to work with this leadership team and help support the next stage of expansion led to this move,” Murphy said. “Finance and operations should strengthen our unified GTM engine and support decision-making across the business. I am excited to help drive sustainable growth as we move forward.”

Marketing Technology News: From MarTech Stack to MarTech Fabric: Weaving Brand, Content, and Conversion Into One Thread

As 2X CFOO, Murphy will oversee finance and accounting, information technology, legal, mergers and acquisitions and delivery operations. The finance and operations function is designed to provide strategic counsel, proactive recommendations and shared ownership of budgets, business cases, operating metrics and investment discipline to help other teams focus on their core responsibilities and position 2X for continued scale.

Before joining 2X, Murphy held senior financial leadership roles at several private equity-backed services and technology-enabled companies, where he led financial strategy, operational execution, and M&A initiatives. Earlier in his career, he spent more than a decade at PwC (PricewaterhouseCoopers), including time in the firm’s national office advising organizations on complex accounting, revenue recognition and transaction-related matters.

Murphy was a Certified Public Accountant (CPA) for over 20 years and holds a bachelor’s degree in business administration from Temple University in Philadelphia.

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Basis Integrates Protected by Mediaocean to Deliver AI-Driven, Real-Time Media Quality & Performance Signals into Campaign Activation

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Globe Newswire
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everle Inc, Launches Blob AI 2.0: A Subscription-Based AI Companion Built on Privacy, Ethical Design, and No Ads

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Protected Verification, Attention, and Quality Optimization Integrated Directly into Basis to Help Marketers Reduce Waste and Improve Outcomes

Basis and Mediaocean announced a direct integration between Basis and Protected by Mediaocean, bringing AI-driven media quality, brand safety, and attention signals directly into campaign activation workflows. In the opening phase of their strategic, multi-pronged partnership, the companies are introducing a more intelligent, performance-based approach to media quality, verification, and optimization.

This latest integration builds on the companies’ shared vision to unify planning, activation, ordering, trafficking, execution, quality, measurement, and finance across the media lifecycle. With Protected now integrated into media workflows in Basis, marketers can seamlessly apply advanced media quality controls and real-time verification directly within their activation environment—ensuring campaigns reach real people in high-quality environments, while maximizing performance and minimizing waste.

“Advertisers need control, clarity, and simplicity across an increasingly complex media landscape. Together, Mediaocean and Basis are removing friction in our industry to bring higher quality decision-making and performance into a single, connected workflow,” said Mike Hoyle, chief product officer, Basis. “By unifying the ecosystem, we are making it easier for advertisers to activate media with confidence to maximize outcomes.”

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

Unlike traditional verification solutions that rely on rigid blocking or static rules, Protected introduces a more adaptive, performance-led approach. Its pre-bid intelligence is continuously informed by real-time post-bid data, creating a live feedback loop that adapts targeting decisions based on actual performance. This approach improves precision and reduces wasted spend without sacrificing scale.

Through the integration, marketers can:

  • Apply dynamic, customizable brand safety, fraud, and quality controls directly within Basis
  • Leverage attention, viewability, and supply intelligence data to prioritize high-quality inventory
  • Reduce wasted spend from invalid traffic, MFA sites, and low-quality placements
  • Optimize campaigns dynamically based on live performance and engagement signals

“Media quality shouldn’t come at the expense of performance, or vice versa,” said Sara Maskivish, SVP, Market Enablement – Verification, Protected by Mediaocean. “With this integration, we’re bringing a new model to market that connects verification directly to outcomes, using AI-driven, real-time intelligence to help marketers make smarter decisions and get more from every impression.”

Marketing Technology News: From MarTech Stack to MarTech Fabric: Weaving Brand, Content, and Conversion Into One Thread

Basis is an integrated cross-channel media orchestration and connectivity platform that automates the most important phases of the entire campaign lifecycle. Its enterprise AI system empowers marketers through a suite of applications for planning and operations across programmatic, publisher-direct, search, and social channels.

This milestone marks the first step in the Basis x Mediaocean partnership, which aims to eliminate fragmentation across the media lifecycle and create the foundation for AI-driven automation and optimization at scale. Future phases of the integration will continue to expand connectivity across Mediaocean’s platforms, including Prisma and Innovid, further aligning all aspects of advertising management into a single, intelligent workflow.

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Pacvue Launches Pacvue Agent, Advancing AI-Powered Commerce Media Execution

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Pacvue Launches Pacvue Agent, Advancing AI-Powered Commerce Media Execution

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Pacvue Agent extends the company’s AI-Powered Commerce Media OS, helping brands execute workflows up to 200x faster, achieve up to 80x faster time to insight, and improve performance by up to 54%

Pacvue announced today the launch of Pacvue Agent, the next evolution of its AI Outcome Engine that moves commerce media from analysis and explanation to recommendation and governed execution within a single workflow.

Building on years of investment in AI and machine learning, including early automation capabilities and the introduction of generative AI in 2023, Pacvue Agent represents the next phase of applied, outcome-driven intelligence for enterprise commerce media teams.

“As commerce media scales, teams are under increasing pressure to deliver stronger performance with fewer resources, yet organizational silos continue to create significant operational drag,” said Rahul Choraria, CEO of Pacvue. “Pacvue Agent unifies insights, recommendations, and execution within a single system, enabling teams to move faster while maintaining control and driving measurable outcomes.”

Pacvue Agent applies AI directly within daily commerce media operations, rather than limiting intelligence to reporting or surface-level insights. This enables teams to understand what happened and why, prioritize next steps, and make campaign updates all within one workflow and environment.

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

“Pacvue Agent is raising the standard for AI in commerce media,” said David Khoshpasand, Sr. Performance Marketing Manager, Amazon at Hasbro. “It’s helping us manage media performance faster, save time, and surface more actionable insights. Instead of spending hours moving between reports and dashboards to understand what changed, I can ask questions in plain language and get clear answers on what shifted, why it happened, and what to do next. Most impressive has been its impact on collaboration with our agency team. We can identify low-performing targets faster, reduce wasted spend, and align more quickly on next steps.”

Early adopters are already seeing significant impact. Teams have leveraged Pacvue Agent to execute key workflows up to 200x faster (saving each team member up to 3 hours per week), achieve up to 80x faster time to insight, and generate up to 54% performance improvement.

“Before Pacvue Agent, building AMC audience queries required significant and time-consuming SQL development effort that often delayed activation,” said Yoshika Ieiri, Manager, E-Commerce, Planning Team at Itsumo. “With Pacvue Agent, we accelerated how we translate key business challenges into measurable action, saving 200+ hours as we prepared for the Prime Member Appreciation Sale.”

Brand and agency teams can interact with Pacvue Agent through a conversational, natural-language experience embedded within Pacvue or directly in Slack, where many operational decisions already take place. Through agentic workflows, recommendations can be converted into approval-based execution with defined guardrails, ensuring that speed does not come at the expense of governance. By bringing trusted intelligence into the same threads where teams align on next steps, Pacvue Agent reduces context-switching and accelerates response time when performance shifts or new opportunities emerge.

Marketing Technology News: From MarTech Stack to MarTech Fabric: Weaving Brand, Content, and Conversion Into One Thread

With Pacvue Agent, teams can:

  • Diagnose performance changes instantly and understand what drove them. Ask plain-language questions and receive contextual explanations of trends, drivers, and outliers across campaigns and audiences.
  • Prioritize the actions that will have the greatest impact. AI-driven models surface next best actions aligned to efficiency, growth, or incrementality goals, reducing manual analysis and guesswork.
  • Move from recommendation to approved execution without losing governance. Convert insights into campaign and budget updates through agentic workflows with built-in guardrails, approvals, and auditability.
  • Accelerate advanced measurement without SQL bottlenecks. Translate business questions into AMC-ready queries, build activation-ready audiences, and interpret results into clear next steps.
  • Standardize reporting and stakeholder communication. Automatically generate structured, visual reports with clear narratives that align teams and leadership around measurable outcomes.

Unlike standalone assistants or generic automation tools, Pacvue Agent operates within Pacvue’s AI-Powered Commerce Media OS, which connects signals across campaigns, audiences, platforms, and outcomes.

Pacvue Agent is not a standalone chatbot layered onto reporting,” said Sunava Dutta, Chief Product Officer at Pacvue. “It’s embedded directly within the systems where commerce media decisions are made and executed. As these systems become more intelligent, humans focus on judgement and execution shifts from humans to software, with recommendations continuously tied to real outcomes. That’s what makes the intelligence not just actionable, but accountable.”

At launch, Pacvue Agent delivers AI-driven intelligence and governed action for Amazon Ads. The company will continue to extend Pacvue Agent across additional retailers, formats, and surfaces throughout 2026.

As commerce media scales, so does the need for systems that align intelligence with accountability. Pacvue Agent represents the next step in AI for the industry, combining speed and accountability and shortening the distance between insight and outcomes.

Pacvue is also excited to announce its work on Model Context Protocol (MCP), embracing emerging open standards that will help enterprise teams more seamlessly connect commerce media data with the AI tools they already use, including ChatGPT, Copilot, Gemini, and Claude. Pacvue is actively partnering with customers and technology providers to bring these capabilities to market and explore how MCP can power more connected, intelligent workflows across planning, analysis, and execution.

While MCP represents an important step toward a more open AI ecosystem, Pacvue believes enterprise value will ultimately be defined by how that data is operationalized. By focusing on data fidelity, robust pipelines, and systems that perform reliably at scale, Pacvue ensures that AI-driven outputs are not just accessible, but trusted, actionable, and built for outcomes.

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Moloco Launches AI-Powered Performance CTV for App Marketers, Bringing Mobile-Grade Measurement and Optimization to the Living Room

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Moloco Launches AI-Powered Performance CTV for App Marketers, Bringing Mobile-Grade Measurement and Optimization to the Living Room

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The introduction of Performance CTV for app marketers brings true performance advertising to the big screen, driving measurable outcomes and meaningful impact

Moloco, a global leader in AI advertising, announced the launch of Moloco Ads for Performance CTV. Powered by the same AI that has made Moloco a leader in mobile performance advertising, the launch opens an entirely new frontier for app marketers looking to drive downloads and engagement: the living room, where consumer attention is massive but true performance advertising has largely remained elusive.

“Connected TV represents one of the biggest untapped opportunities for app marketers ,” said Sunil Rayan, Chief Business Officer & General Manager, Moloco Ads. “With Performance CTV, we’re bringing the measurability and precision that app marketers expect from mobile to the world of television, giving them a genuinely new way to reach their audiences and drive results where attention has never been more valuable.”

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

Connected TV (CTV) is a fast-growing advertising channel, with global ad spending currently estimated at $40 billion to $45 billion per eMarketer – numbers which are projected to continue to rise – yet many CTV advertising solutions still target audiences using traditional demographic methods and measure performance only after the fact. These platforms can feel like they’re made for brand buyers and retrofitted for performance, optimizing for reach and frequency, and offering app marketers little more than a TV-sized impression with no real feedback loop.

Moloco Ads for Performance CTV is built differently. Performance CTV brings the same AI that drives Moloco’s mobile ads business to the big screen, making it among the first CTV solutions designed from the ground up as a true performance system. With Performance CTV, every impression is optimized in real time against specific marketing outcomes with attribution running through the advertiser’s mobile measurement partner (MMP) of choice. The result: app marketers can now reach and convert high-value users across screens with the measurability and precision their businesses demand. Early results show up to 1.5x higher return on investment on CTV than mobile when running campaigns across both, with approximately two-thirds of users who install an app as a result of viewing a Moloco-delivered Performance CTV ad doing so within six hours.

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“Moloco Ads for Performance CTV was a key component of our college basketball strategy for Fanatics Sportsbook this March,” said Blair Hilton, Director of Performance Marketing at Fanatics Betting and Gaming. “Moloco played a central role in delivering strong campaign results – performance exceeded expectations and enabled us to reach a broader audience efficiently.”

Moloco Ads for Performance CTV is built on three pillars that matter deeply to app marketers: access to premium, brand-safe, household CTV inventory across a growing network of supply partners; measurement transparency with full publisher-level reporting through integrations with a buyer’s preferred MMP; and true independence as an open platform that never favors its own inventory or audience data over what’s best for the advertiser, with optimization informed by Moloco’s depth of mobile performance expertise. Together, these pillars give app marketers the transparency, control, and accountability they need to drive real results on the biggest screen in the home.

Built on a compound AI system developed over more than a decade, Moloco’s technology can reach two billion consumers across more than two million mobile apps. Moloco Ads is the performance advertising platform trusted by app marketers around the world to find, acquire, and retain high-value users at scale – and with Performance CTV, that same proven capability now extends to the living room. As mobile, connected TV, and retail media continue to converge, Moloco is uniquely positioned to help performance marketers navigate that complexity and win.

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MeasureBoard Launches AI-Powered SEO, Marketing Automation & Analytics Platform

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MeasureBoard Launches AI-Powered SEO, Marketing Automation & Analytics Platform

MeasureBoard Launches AI-Powered SEO, Marketing Automation & Analytics Platform

MeasureBoard launches a free AI-powered web analytics, marketing automation, and SEO platform that combines Google Analytics reporting, keyword tracking, conversion funnels with CPA, site audits, uptime monitoring, and a dedicated AI analyst in one dashboard – replacing multiple tools that typically cost $500+/month. Available now with a free tier at measureboard.com.

MeasureBoard today announced the official launch of its comprehensive AI-powered marketing intelligence and automation platform, giving businesses of all sizes access to enterprise-grade SEO tools, automated analytics, and a dedicated agentic AI analyst — all at a price point that significantly undercuts the current market and allows marketers and business owners to replace costly tools and manual analysis.

Designed for marketers, growth teams, and business owners who want to automate insights and action, MeasureBoard (https://measureboard.com) integrates directly with Google Analytics, Google Search Console, and ad platforms to deliver a unified view of website performance, search visibility, and campaign effectiveness in a single, intuitive dashboard.

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

At the core of the platform is a dedicated agentic AI analyst that has full access to a website’s advertising and engagement data and works autonomously to surface trends, flag issues, and generate plain-language intelligence reports. Unlike passive reporting tools, the AI analyst actively interprets data across traffic sources, keyword rankings, and on-site behavior – providing strategic recommendations without requiring users to manually configure queries or build custom reports.

MeasureBoard also introduces true conversion funnels that track user journeys across all campaigns, referrers, and channels simultaneously, along with effective cost-per-acquisition (CPA) calculations that give advertisers and content teams a realistic picture of what each conversion actually costs. These analytical capabilities, rarely found together in a single SEO website tool, enable teams to make confident budget and content decisions based on real attribution rather than fragmented data.

Marketing Technology News: From MarTech Stack to MarTech Fabric: Weaving Brand, Content, and Conversion Into One Thread

Additional features include AI rank tracking that monitors keyword movement and search position changes in real time, comprehensive SEO page analysis that audits individual URLs for optimization opportunities, and uptime monitoring that ensures website availability is never a blind spot. The platform is built to serve as a true all-in-one solution for anyone looking to improve their SEO web presence, grow organic traffic, and understand the full performance of their digital footprint.

“We built MeasureBoard because powerful SEO and analytics infrastructure should not require an enterprise budget,” said a spokesperson for MeasureBoard. “Our platform gives users an agentic AI analyst, true conversion funnel reporting, and a complete suite of traffic and SEO tools at a fraction of what legacy platforms charge. The free tier means any business can start measuring smarter today – and when they see the value, upgrading is an easy decision.”

MeasureBoard is available immediately with a free tier that provides access to core features, including AI traffic intelligence reporting and SEO site analysis. Paid upgrade plans unlock advanced capabilities and expanded data limits, with new capabilities added monthly.

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LocaliQ ANZ Launches AI Voice Agent to Help Businesses Capture and Convert Every Call

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OnviSource Launches OmVista Engage™ - A Closed-Loop, Conversational AI Learning Platform for Real-Time Workforce Performance and Outcome Optimization

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LocaliQ ANZ, the digital marketing Solutions business of USA Co., announced the launch of its next-generation AI Voice Agent, a powerful new addition to Dash by LocaliQ, an AI-powered lead management platform designed to help businesses capture, manage and convert enquiries in real time.

Building on the success of Dash’s capabilities, the new AI Voice Agent introduces seamless voice interactions, giving businesses an edge to engage with customers 24/7 across multiple channels. Together, these tools create a smarter, more connected experience, helping businesses turn more enquiries into actual customers.

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

“Across Australia and New Zealand, local businesses work hard to generate enquiries, but too many opportunities are still lost, simply because no one is available to answer the phone or manage bookings in the moment,” said Rooman Osmany, Head of Product at LocaliQ ANZ.

Powered by advanced conversational AI, the AI Voice Agent engages customers instantly through natural, human-like conversations. It can answer questions, qualify leads, handle common objections, and guide prospects through the next step, whether that’s booking an appointment or requesting a quote.

Unlike traditional call handling or basic automation tools, Dash doesn’t just capture leads, it actively works to convert them.

Marketing Technology News: The Death of Third-Party Cookies Was Just the Start. Are You Ready for Consent Orchestration?

One of the biggest challenges small and medium businesses face today is missed opportunities. LocaliQ data shows that around 1 in 4 inbound calls go unanswered, often from high-intent customers ready to buy. Dash addresses this by ensuring every call is answered, even outside business hours, helping businesses stay responsive around the clock.

To further close the gap between enquiry and conversion, Dash includes an integrated AI-powered Scheduler.

The Scheduler allows customers to book appointments instantly during a call, removing the back-and-forth and reducing drop-off, by connecting directly with a business’ availability. It ensures bookings happen in real time, not hours later.

“With Dash Voice Agent and Scheduler, we’re removing the gap between a customer raising their hand and a business being able to respond helping SMBs capture and convert leads instantly” said Rooman Osmany.

Key capabilities include:

  • Voice Conversational AI — A tool that hat never sleeps and works around the clock
  • AI Call Handling & Transcription – Automatically captures inbound conversations, transcribes them and surfaces key insights
  • Smart AI Scheduler – Automatically books appointments directly into the calendar based on availability, business rules and lead priority
  • Real-Time Lead Scoring – Identifies high-intent prospects using AI-powered analysis
  • Sentiment & Intent Analysis – Understands tone and urgency to prioritise opportunities

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Reimagining Ad Ops: Building a Predictive Future

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Michele Bavitz
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Reimagining Ad Ops: Building a Predictive Future

For years, Ad Ops teams’ jobs have been defined by urgency. Stuck in reaction mode, employees have had to pivot their day at the drop of an inbox ping, IO change, or tag break. Often, they’ve needed to solve problems almost instantly.

However, as automation evolves and data becomes more interconnected, there’s a quiet but strong shift happening. Ad Ops is transitioning from firefighting to forecasting, leaving behind reacting to what’s broken and anticipating what comes next.

Moving From Reaction to Readiness

Ad Ops teams live in constant motion, but not from lack of discipline. Manual handoffs, real-time changes, and disconnected systems make it nearly impossible to look beyond today. When every fix is urgent, strategy falls to the bottom of the list.

The process itself is creating delays, meaning even the best people spend their time just managing the workflow instead of identifying ways to improve it. Fortunately, this was the cycle purpose-built automation was created to break.

Automation: Reinforcement, Not Replacement

Even the word automation can make some Ad Ops teams nervous. The idea that technology might replace human expertise has made even the most innovation-forward individuals hesitate.

The reality is that true, purpose-built automation does the opposite. The technology can remove the mundane, time-sensitive steps that keep Ad Ops stuck in maintenance mode. With connected platforms, tracking and reconciliation can happen in the background. Workflows are routed automatically, giving Ad Ops teams the space they need to focus on higher-value work like refining campaign strategy and partnering with client success teams.

Transforming Operations into Intelligence

When powered by automation, modern Ad Ops becomes a source of intelligence. The team closest to campaign delivery has the clearest view of what drives performance when clean data flows easily across systems. Using consistent campaign pacing and having clear visibility into delivery patterns and inventory helps Ad Ops identify challenges early, including clients that require extra QA time, workflows that are creating bottlenecks, and formats that underdeliver.

Having a holistic picture transforms Ad Ops from simply a reporting function into a predictive partner backed by operational intelligence. Rather than waiting for post-campaign reports, revenue and client success leaders can partner with Ad Ops to anticipate bottlenecks, adjust capacity, and plan more effectively for the future.

Dependability as the New Differentiator

Advertisers value partners who deliver consistently. Every delay undermines confidence in workflows as well as partnerships. Even factors beyond an Ad Ops team’s control, like a missed flight, can have a ripple effect. Automation can help by minimizing those moments to create a standard path through the entire process, from IO to invoice.

Modern automation can make the mountain of Ad Ops tasks flow in a sequence with instant approvals and visibility to keep stakeholders aligned. As a result, predictability can become the new performance metric, and Ad Ops becomes the foundation of dependability across an organization.

Purpose-built automation serves clients and strengthens collaboration across the board. Finance receives cleaner billing data, sales gains confidence in inventory commitments, and IT sees significantly fewer last-minute requests.

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

When Ad Ops Lead, The Business Follows

The move to purpose-built automation is about creating better work, not just systems. Ad Ops firefighting models of the past rewarded those who could juggle the most tasks, stay calm under pressure, and still meet every deadline.

The forecasting model shifts from endurance to perspective, rewarding those who can connect insights, shape smarter workflows, and anticipate challenges before issues arise, ultimately unlocking opportunity.

When Ad Ops teams are free from reactivity, they can step into new roles. Upleveled responsibilities include optimizing performance data, advising pricing strategy, influencing revenue forecasts, and collaborating across the entire organization.

Ad Ops becomes the training ground for leadership with purpose-built automation behind them. As technology evolves, Ad Ops won’t be defined by the tools teams use, but by how they use them. It’s essential, however, not to lose sight of the fact that while purpose-built automation lays the foundation, people bring true value. Because when Ad Ops teams stop firefighting and begin forecasting, the entire business can truly skyrocket.

About Theorem

Theorem’s consultancy teams and operational expertise helps brands simplify, streamline and automate complex digital tasks. This value exchange saves clients time, reduces their costs, and increases their revenue.

Marketing Technology News: The Death of Third-Party Cookies Was Just the Start. Are You Ready for Consent Orchestration?

TechAhead Announces OpenAI Services Partner Status to Help Businesses Accelerate AI Adoption

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PRNewswire
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TechAhead Announces OpenAI Services Partner Status to Help Businesses Accelerate AI Adoption

TechAhead, an AI-native app and enterprise software development company, announced that it is an OpenAI Services Partner. Through this collaboration, TechAhead will help organizations accelerate the adoption of AI solutions using OpenAI’s models and APIs.

TechAhead’s services include advisory, solution design, implementation, and ongoing support to help organizations integrate AI capabilities into their existing systems and business processes.

“We’re excited to be an OpenAI Services Partner and to expand how we help clients apply AI in responsible, scalable ways,” said Vikas Kaushik, Founder and CEO of TechAhead. “Our focus is on delivering real business outcomes, whether that’s improving operational efficiency, enhancing customer experiences, or enabling new digital products, using OpenAI’s models as part of a broader solution strategy.”

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This announcement builds on TechAhead’s continued investment in responsible AI and enterprise-grade delivery. The company holds ISO/IEC 42001:2023 certification for AI Management Systems, as well as SOC 2 Type II and ISO/IEC 27001:2022 certifications, supporting secure, compliant AI implementations.

With over 16 years of experience and 2,500+ apps and custom software solutions delivered across industries such as healthcare, financial services, manufacturing, retail, and real estate, TechAhead helps organizations turn digital and AI initiatives into real-world outcomes. Its capabilities span generative AI, IoT, data engineering, cloud consulting, and custom software development, enabling clients to modernize systems, unlock data value, and scale innovation.

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As part of its collaboration with OpenAI as a Services Partner, TechAhead will help organizations:

  • Integrate OpenAI’s models into business workflows and applications
  • Develop custom AI-powered apps using OpenAI’s APIs
  • Support user onboarding, customer success, and expansion
  • Scale AI deployments with governance, security, and operational best practices

TechAhead also maintains partnerships with leading cloud providers, including Amazon AWS and Microsoft Azure, enabling flexible and interoperable AI architectures.

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5W PR Strengthens Crisis PR and Generative Engine Optimization Services to Meet AI-Driven Reputation Demands

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PRNewswire
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5W PR Strengthens Crisis PR and Generative Engine Optimization Services to Meet AI-Driven Reputation Demands

5W PR, one of the largest independently owned PR and digital marketing agencies in the U.S., announced an expanded focus on its crisis communication and Generative Engine Optimization offerings as brands adapt to a new era of AI-driven search, online visibility, and reputation management.

As artificial intelligence continues to transform how consumers discover, evaluate, and engage with brands online, 5W is helping clients strengthen both proactive and reactive communications strategies through integrated programs designed to shape digital narratives before and during reputational challenges. The agency’s enhanced services combine crisis communications expertise with GEO strategies to help brands manage perception across traditional media, search engines, and AI-generated responses.

Marketing Technology News: MarTech Interview with Miguel Lopes, CPO @ TrafficGuard

5W’s crisis communications services provide clients with strategic counsel, rapid-response media engagement, executive messaging, and reputation support during sensitive or high-pressure situations. Paired with the agency’s Generative Engine Optimization capabilities, 5W helps clients proactively develop authoritative digital content and optimize online visibility so brands are accurately represented across emerging AI-powered search and discovery platforms.

“As AI increasingly shapes how consumers research and evaluate brands, reputation management requires a more forward-thinking and digitally integrated approach,” said Matt Caiola, Chief Executive Officer of 5W. “Organizations can no longer focus solely on traditional media or search rankings. They must also understand how AI platforms interpret and present their brand online. Our expanded GEO and crisis communications offerings ensure clients are prepared to both shape and protect their reputation in this new environment.”

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The agency’s Generative Engine Optimization services focus on building authoritative digital footprints through strategic content development, search-conscious storytelling, digital PR, and optimized content architecture designed to improve discoverability across AI-powered platforms. These capabilities complement 5W’s longstanding expertise in media relations and online reputation management, providing clients with a more holistic approach to digital visibility and brand protection.

This enhanced offering reflects 5W’s commitment to evolving alongside the communications industry and delivering forward-looking strategies that address the intersection of technology, reputation, and public perception. As AI becomes more deeply integrated into consumer search behavior, the agency continues to help clients navigate emerging challenges while building lasting authority across digital channels.

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Message Central Launches VoiceNow to Help Businesses Turn Every Missed Call Into Revenue

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MTS Staff Writer
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Subtext Unveils Significant SMS Platform Expansion, Giving Clients Greater Control Over Audience Management and Activation, Revenue Growth, and Campaign Customization

Message Central | F6S

New conversational AI voice agents respond to inbound calls instantly, around the clock, so businesses never lose a high-intent customer to a missed call again.

Every business loses revenue it never sees leaving. Not from bad products or weak marketing, but from a phone that rang and went unanswered. Research shows that 78% of customers buy from the first company that responds. A customer calls at 8pm, gets silence, and books with a competitor by morning. In a market where speed of response has become the baseline expectation, missing a call is not a minor inconvenience. It is a lost sale.

Customers don’t wait for a callback. They move on to the first business that responds.”

— Sumesh Menon

The problem is structural. Extending support hours means higher payroll. Hiring more staff adds cost and complexity. And in many markets with high-volume inbound economy such as the US and UK, customer expectations around immediacy have never been higher. The availability of skilled, customer-facing talent simply does not keep pace with demand. Growing businesses are caught in an impossible position: be available everywhere, or stay lean. Until now, those were mutually exclusive.

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

To close that gap, Message Central has launched VoiceNow, an AI-powered voice agent platform that answers every inbound call instantly, at any hour, without adding to the payroll. VoiceNow deploys AI agents that speak naturally, understand context, and handle the full range of high-frequency inbound interactions including answering questions, qualifying leads, taking bookings, managing service requests, and routing complex conversations to human agents when needed. The experience is designed to feel less like a phone tree and more like a capable, well-briefed member of the team. One who is always available.

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The platform supports multiple languages, serving multilingual customer bases in the US and UK. No coding is required to deploy it, and Message Central continues to expand the language base regularly.
“Every missed call is missed revenue. Businesses today do not lose customers due to lack of demand. They lose them due to lack of response,” said Sumesh Menon, Founder and MD at U2opia. “VoiceNow is built to ensure that every inbound intent is captured, especially in high-intent moments where timing is everything.”

VoiceNow is part of Message Central’s broader vision of building a unified customer experience infrastructure, enabling businesses to connect with users seamlessly across SMS, RCS, WhatsApp and voice. Voice remains the highest-intent channel in that ecosystem, where customers are closest to a decision and where the cost of a missed interaction is highest. With VoiceNow, Message Central is making it possible for any business, regardless of size or market, to be fully present on that channel around the clock.

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ZoomInfo and Pinecone Bring Real-Time, AI-Powered Contact Recommendations to Go-to-Market Teams

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PRNewswire
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ZoomInfo and Pinecone Bring Real-Time, AI-Powered Contact Recommendations to Go-to-Market Teams

Pinecone’s unique serverless vector database slab architecture — with Dedicated Read Nodes now generally available — gives customers exceptional price-performance for any use case

Pinecone, the leading vector database, announced that its next-generation serverless slab architecture and newly released Dedicated Read Nodes (DRN) are powering real-time, AI-driven contact recommendations for sales and marketing teams. With Pinecone, ZoomInfo now serves highly relevant suggestions instantly, driving a 50% increase in user engagement and enabling customers to identify the right buyers in minutes instead of hours.

Companies across industries are racing to operationalize AI, yet they increasingly face a core infrastructure challenge: every AI use case has different performance, concurrency, latency, traffic, and cost requirements. Databases with bolted-on vector capabilities struggle at scale because they were never designed for high-throughput semantic or hybrid search, while open-source vector databases often require deep ANN tuning, cluster management, and complex operational overhead. Neither approach can efficiently support the diverse, production-grade workloads enterprises now run. Pinecone’s serverless architecture — which includes On-Demand indexes, where storage scales elastically and customers pay only for the queries they make, and Dedicated Read Nodes for sustained high queries per second (QPS), low-latency workloads — eliminates these constraints and lets teams optimize price-performance for every use case.

Marketing Technology News: MarTech Interview with Nicholas Kontopoulous, Vice President of Marketing, Asia Pacific & Japan @ Twilio

Dedicated Read Nodes, generally available today, provides resource isolation and guaranteed warm data which prevents delays caused by cold fetches. This ensures predictable low-latency performance even under sustained high-QPS production workloads, which has been difficult for vector databases until now. Combined with Pinecone’s slab architecture, which stores vectors in large contiguous units to avoid fragmentation and ensure consistent performance, customers benefit from purpose-built managed infrastructure that delivers superior price-performance across all of their AI applications.

ZoomInfo selected Pinecone to power its new real-time recommendation engine, which now serves personalized contact suggestions across more than 390 million and growing high-dimensional embeddings and over 100,000 namespaces. With Pinecone, the Applied AI team moved from prototype to production in weeks, meeting strict sub-second latency requirements and achieving an order-of-magnitude improvement in throughput during scale testing with Dedicated Read Nodes. Pinecone enabled ZoomInfo to deliver a 50% increase in user engagement, a 2x improvement in relevancy and recall, and the ability to handle 50x more peak request volume, all while maintaining predictable low-latency performance. These improvements dramatically reduced ZoomInfo’s customer time-to-action, cutting workflows that previously took hours down to minutes by surfacing the right contacts instantly.

“Pinecone’s slab architecture and Dedicated Read Nodes gave us the speed, consistency, and isolation we needed to run real-time recommendations at scale. Instead of managing infrastructure, we spend our time improving our recommendation model and the product itself. That has reduced the time our customers spend researching, filtering, and evaluating contacts—from hours to minutes—by giving them the right people to reach out to with a single click.” — Carlos Nunez, Vice President of Engineering and Applied AI at ZoomInfo

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

Ash Ashutosh, CEO of Pinecone, emphasized the broader market significance:

“Every company today has multiple AI applications, and each one has different performance and cost profiles. Pinecone is the only vector database that lets customers run all of these workloads in one place, with exceptional speed, accuracy, and cost efficiency at scale. Our serverless slab architecture and Dedicated Read Nodes deliver trusted knowledge to our customers and make it possible to deploy production-grade RAG, search, recommendation systems, and agents without compromise.”

With Pinecone’s unique architecture, enterprises no longer face tradeoffs between price, performance, and scale. ZoomInfo’s deployment illustrates how organizations can use Pinecone to ship AI applications faster, improve user experiences, operate reliably at massive scale, and create experiences that previously weren’t possible.

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Using local AI-enhanced workflows on AMD Ryzen AI PCs Can Dramatically Reduce Task Completion Time for Professionals

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MTS Staff Writer
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New TDWI Research Report Provides Guidance for Gaining Value from Agentic and Generative AI

Principled Technologies

In our tests of developer and project-management scenarios, AI on new PCs saved 2 or more workdays per week vs. traditional approaches on older PCs

Principled Technologies (PT) has released two new reports demonstrating that using AI tools on a modern PC powered by AMD Ryzen AI processors can significantly accelerate routine project-management and development tasks compared to using traditional workflows on a 4-year-old PC. When professionals can leverage AI to complete certain tasks more quickly, they can redirect the time they save to higher-value work and innovation. Because the AI tools that PT tested primarily ran locally instead of in the cloud, professionals could save time while also better protecting sensitive data, enjoying quicker response times, and being able to work without an internet connection.

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

The report focusing on activities performed by developers stated: “In our testing, using local AI tools on a new HP EliteBook X G2a AI PC powered by an AMD Ryzen AI processor reduced task completion times by as much as 97.5 percent compared to completing the same tasks manually on a 4-year-old HP EliteBook 865 16 inch G9 Notebook PC. Based on our estimates of how frequently these tasks typically occur, we found that using AI tools on the newer system could lower weekly development-related work time from an average of 24 hours and 6 minutes to approximately 6 hours and 13 minutes. This represents a reduction of almost 18 hours of work per week—equivalent to over two standard workdays.”

Marketing Technology News: From MarTech Stack to MarTech Fabric: Weaving Brand, Content, and Conversion Into One Thread

The report focusing on project-management activities stated: “In testing with two HP systems, using primarily local AI tools reduced task completion times by as much as 95.6 percent. Based on estimates of how frequently the evaluated tasks occur, we found that using AI technologies on the new PC could reduce the weekly time spent on a set of common tasks from an average of 24 hours and 40 minutes to 4 hours and 45 minutes—a savings of almost 20 hours, half of a typical workweek.”

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Amplitude Names Serial Founder Gab Menachem as CPO

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Business Wire
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Amplitude Names Serial Founder Gab Menachem as CPO

Amplitude, Inc. Logo

Hire signals next phase of company’s AI analytics transformation

As part of its continued transformation into the world’s leading AI analytics provider, Amplitude, Inc. announced Gab Menachem as its new chief product officer.

Menachem founded Loom Systems, an AIOps company that was acquired by ServiceNow in 2020, and has spent the past six years scaling ServiceNow’s IT Operations Management product line to over $1 billion in annual revenue. He will oversee Amplitude’s product management, design, and growth organizations, reporting directly to co-founder and CEO, Spenser Skates.

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

“Every company building a digital product is asking the same question: are we building the right thing?” said Spenser Skates, CEO and co-founder of Amplitude. “That question is harder to answer than it has ever been, because products like AI agents, autonomous workflows, and entirely new kinds of user experiences are more complex than anything that came before. Gab has spent his career at the center of that problem, and he’s the right person to lead the team.”

“Amplitude continues to lead the way providing behavioral context for product builders,” said Menachem. “You build something, you want to see what users are actually doing in your platform, and then you bring it back to iterate. The difference is that what people are building today isn’t common software — it’s not web pages and applications. They’re building agents. So we’re moving into the world of agent analytics.”

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Menachem describes Amplitude’s evolving positioning as an intelligence platform for digital and AI builders. “As you build any digital product, you need the intelligence layer for what’s happening after you release it in order to iterate and improve. That’s the core of what Amplitude does,” he said.

Menachem is joining Amplitude amid its first company-wide AI Week – five days dedicated to every employee across every function building AI-powered tools to reinvent and transform their workflows. The initiative is a direct expression of the company’s mission ‘to help companies build better products.’

“Gab started onboarding this week and immediately had a way to influence what we ship next,” added Skates. “That’s exactly what we needed.”

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Qlik Brings Agentic Execution to Data Engineering

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Qlik Brings Agentic Execution to Data Engineering

Qlik

New capabilities across declarative pipelines, real-time routing, streaming, and emerging agentic experiences help data teams move from manual assembly to faster, more intent-driven delivery of trusted data.

Key takeaways:

  • Qlik extends its agentic approach into data engineering: This release takes Qlik’s agentic strategy beyond analytics users and into the teams building, moving, and maintaining trusted data for AI and operations.
  • The announcement centers on engineering execution, not just coding help: Declarative pipelines, real-time routing, Open Lakehouse Streaming, and broader agentic assistance are designed to reduce friction in how pipelines are built, changed, and operated.
  • Fresh, open data becomes easier to deliver: New and expanded capabilities help data teams reduce backlog, simplify delivery, and keep data current for analytics, automation, and agentic workflows.

Qlik® announced an expansion of its agentic execution strategy into data engineering, introducing capabilities designed to help data teams create, evolve, and deliver trusted data faster as demand for AI-ready data continues to rise.

The pressure on data teams has changed. They are being asked to support more AI initiatives, move faster on new data demands, and do it all without adding fragility, backlog, or unnecessary cost. In many enterprises, the constraint is not ambition. It is the amount of manual work still required to build pipelines, maintain transformations, troubleshoot issues, and keep data current enough to support decisions and automation.

Qlik’s latest data engineering release is designed around that reality. It brings agentic execution into the engineering workflow itself, giving teams new ways to translate intent into working data assets, reduce repetitive effort, and speed delivery without stripping away the control required for production environments.

“Most companies do not struggle to imagine AI use cases. They struggle to deliver the trusted, current data those use cases depend on,” said Mike Capone, CEO, Qlik. “As demand rises, data engineering becomes the critical path. Qlik is helping teams reduce friction, protect trust, and keep pace with the business.”

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

What’s new

  • Declarative pipelines: Qlik is introducing a more natural-language-driven way to help data engineers create and evolve pipelines in context with the pipeline canvas, offer next-step guidance, and lower the barrier to building trusted flows. This release also establishes the path toward broader Pipeline Agent capabilities over time.
  • AI Assistant for Talend Studio: A new context-sensitive AI Assistant inside the Talend Studio IDE, planned for later this year, is designed to help developers request help, generate jobs, create documentation, and write SQL using natural language, shifting engineering work from manual coding toward higher-level orchestration.
  • Real-time routing for agentic data flows: Qlik is expanding Talend Studio to support real-time message routing for agentic processes, helping data engineers work with large language models, build domain-specific RAG pipelines, and connect agentic systems through MCP components. The latest release also expands context and memory handling to support more complex enterprise-scale workflows.
  • Open Lakehouse Streaming: Qlik has extended its Open Lakehouse with native streaming support so teams can unify continuous event data with batch and CDC workloads in one environment, reducing the need for separate tooling and helping keep AI and analytics closer to current business conditions.
  • A more complete engineering path for agentic workloads: Across declarative pipelines, real-time routing, Open Lakehouse Streaming, Talend Studio AI assistance, and the broader path toward Pipeline Agent capabilities, Qlik is positioning data engineering as a more intent-driven, agent-assisted function, one designed to reduce reinvention and help teams spend more time on architecture, design, and business impact.

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Taken together, the capabilities available now, along with the broader agentic experiences planned ahead, are designed to help data teams move from manual pipeline assembly toward a more agent-assisted operating model — one where engineering work becomes easier to initiate, easier to evolve, and better able to keep up with the freshness and reliability demands of AI.

“There is a big difference between an assistant that helps write code and a system that actually helps a data team move faster end to end,” said Robin Astle, Principal Developer, Valpak. “The interesting part of this announcement is the focus on pipeline creation, data quality, metadata, and stewardship together, because that is much closer to how real engineering work happens.”

This announcement is part of a broader set of releases at Qlik Connect 2026, Qlik’s annual customer and partner event, focused on agentic analytics, operational trust, sovereignty-ready deployment, and the data capabilities required to support AI under real-world conditions.

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Glitter AI Turns Screen Recordings Into SOPs Automatically, Used by 11,000+ Teams

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MTS Staff Writer
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GPT Proto Now Fully Supports GPT Image 2

Scribe vs Glitter AI: 2026 Comparison | Glitter AI

AI-powered platform converts screen recordings and voice narration into publish-ready SOPs and training guides for operations teams.

Glitter AI (www.glitter.io), an AI-powered documentation and SOP creation platform, announced continued growth as more than 11,000 teams worldwide now use the platform to create standard operating procedures, training guides, and process documentation without manual writing.

Every company has one person who knows how everything works – when they leave, the knowledge walks out the door.”

— Yuval Karmi, CEO of Glitter AI

Positioned as a simpler, faster, and more affordable alternative to tools like Scribe and Guidde, Glitter AI records a user’s screen and voice simultaneously, then uses AI to generate both a written SOP and a video walkthrough from a single recording. The AI captures screenshots at every click, transcribes voice narration, removes filler words, and produces a professional guide – typically in under two minutes. Traditional documentation tools require separate workflows for video and written content; Glitter delivers both from one session at a fraction of the cost.

The Problem: Tribal Knowledge and Undocumented Workflows

Growing businesses face a persistent challenge: critical processes live inside people’s heads. When the office manager who runs payroll goes on vacation or the accounts payable specialist who knows the invoicing workflow leaves, operations slow down. Traditional documentation takes 30 to 60 minutes per procedure. Most teams never finish the project.

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

How Glitter AI Works

A user opens the Glitter desktop app or Chrome extension, performs the task while narrating the steps, and the AI SOP generator creates a structured guide with annotated screenshots. Existing videos – Zoom recordings, Loom videos, Microsoft Teams meetings – can also be uploaded and converted into guides automatically. Completed guides can be exported to PDF, HTML, or Markdown, or published directly to Confluence, Notion, Zendesk, or WordPress in 99 languages.

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Built for Operations Teams at SMBs

Glitter AI is designed for operations managers, office managers, accountants, team leads, and customer success managers – professionals who already know their workflows and need to transfer that knowledge to the rest of the team. The platform is used across accounting and finance, construction, logistics, SaaS, hospitality, and field services for workflows such as invoice processing in QuickBooks and Sage, payroll in ADP and Workday, and project management in Procore and Salesforce.

“Every company has one person who knows how everything works – and when that person leaves, the knowledge walks out the door with them,” said Yuval Karmi, CEO of Glitter AI. “We believe every business process should be captured the moment it’s performed, not written up after the fact from memory. That’s the future of documentation – you just do your job, and the guide writes itself.”

Why Teams Switch From Scribe, Guidde, and Other Documentation Tools

Glitter AI captures not just clicks, but also what a user hovers over and explains verbally – context that other click-only screenshot tools miss entirely. The original video recording is preserved alongside the written guide, giving teams both formats from one session. The platform also includes on-device blur for sensitive data, SOC 2 Type II compliance with GDPR and CCPA certification, and a desktop app on the free plan for Mac and Windows.

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Appdome’s IDAnchor™ Gets New Risk Intelligence APIs to Power Mobile Reputation & the Enterprise AI Age

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Appdome's IDAnchor™ Gets New Risk Intelligence APIs to Power Mobile Reputation & the Enterprise AI Age

New Server-to-Server Risk Intelligence APIs strengthen IDAnchor’s threat attribution and decision-ready risk intelligence across the mobile lifecycle.

Appdome, the leader in protecting the mobile economy, announced that its IDAnchor™ device identity and reputation product is now powered by a suite of new, Appdome-provided, server-to-server Risk Intelligence APIs. The new APIs provide operational reputation data and risk intelligence to the mobile backend and across the mobile business. As part of this release, IDAnchor will also use two new mobile identities, known as AppID and InstanceID, which provide a verified identifier for each mobile app (bundle ID) and maintain continuity of identity across updates, upgrades, and downgrades over time.

“At 1.3 trillion threat events per month and growing, we have the largest and most comprehensive data set of mobile threats,” said Tom Tovar, Co-Creator & CEO of Appdome. “It made sense for us to start to expose this via backend APIs and allow mobile brands to consume that data within well-understood and useful contexts to stop fraud and improve decisioning.”

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

Risk APIs Built for the AI-Generation

Building on the recently announced Threat-Memory™ framework, which provides a threat intelligence substrate within mobile apps, the new Risk Intelligence APIs allow brands to access threat histories and risk intelligence tied to verified mobile identities directly in their backend systems.

These new APIs provide verified threat attribution and history, as well as agentic risk intelligence in real-time within mobile backends. They are designed to support enterprise AI development with continuous, on-demand, and verified threat data and risk intelligence from the mobile business.

“Mobile devices are more a part of daily life than ever,” said Eric Newcomer, Principal Analyst at Intellyx. “Cybercriminals and fraudsters know this and are constantly ramping up their attacks. Fortunately, mobile defense vendors such as Appdome continue to respond. Their new IDAnchor APIs are an important addition to strengthening mobile app protection as well as server side intelligence.”

The new Risk Intelligence APIs announced today as part of IDAnchor include:

  • DeviceMATCH™ — verifies whether mobile activities and interactions originate from the same physical device.
  • InstanceMATCH™ — confirms the authenticity of the AppID and continuity of the mobile app lineage across upgrades, updates, and downgrades
  • ThreatHISTORY™ — provides longitudinal threat evidence associated with IDAnchor’s identity context for the app, install, instance, device or user
  • MobileRISK™ — delivers AI-generated risk and reputation scores for devices, accounts, and sessions

As part of this release, Appdome introduced two new identities in its IDAnchor lineup. AppID, replacing the previously announced ReleaseID, provides the app’s signature fingerprint and an attestation from Appdome that the app has not been modified.  InstanceID™ is new and the first durable identifier that fingerprints the initial installation of an app and maintains continuity across each update, upgrade, and downgrade on a device.

“Binding granular threat data and threat history across verified mobile identities on Appdome’s backend creates so many possibilities,” said Avi Yehuda, Co-Creator & CTO of Appdome. “On the one hand, it can be consumed on the mobile backend to improve risk-based decisions. It can also empower mobile brands to leverage Appdome’s APIs as a trusted and verified source of threat data and identity context to enrich Enterprise AI models.”

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Creating an Authentic Risk Pipeline

The sophistication and diversity of attack vectors are increasing. Network and fraud teams can no longer rely on inference-based risk scoring. They need to augment risk scoring with facts and correlate detailed runtime threat evidence with trusted, persistent identities across immediate, short, medium, and long-term time frames. With Appdome’s new APIs, mobile brands can do just that and:

  • Catch repeat offenders across mobile devices and accounts
  • Detect coordinated fraud and social media scams
  • Detect determined hackers and malware creators who reuse and manipulate application installs and device resets
  • Block high-risk devices used in fraud rings and device farms
  • Strengthen API authorization using device reputation and threat history
  • Reduce false positives by distinguishing new users from known high-risk hardware
  • Adapt authentication and transaction flows based on real-time risk

“Think of mobile risk as a data pipeline,” said Kai Kenan, VP of Identity & Reputation Solutions at Appdome. “Fraud and Identity team can’t perform risk-based decisioning on a single factor and risk false positives or negatives. Our APIs provide risk scoring but also provide detailed threat data attributed to the mobile identities that brands know and trust.”

APIs Built for Enterprise Decisioning

The new APIs allow mobile brands to retrieve intelligence from Appdome’s backend within secure server environments, enabling integration with fraud engines, case management systems, and risk orchestration platforms.

This backend-driven architecture supports:

  • secure decision orchestration
  • fraud workflow automation
  • risk-based authentication and step-up flows
  • device-level enforcement and bans
  • cross-channel risk intelligence correlation

“Secure access, threat data integrity, and continuous availability are built into our API services from the ground up,” said Srini Avernini, VP of Data & Infrastructure at Appdome. “We recognize that our new API services will be used for real-time and runtime decisioning in billions of mobile apps and as the bedrock for Agentic AI developments our customers invest in, and we’ve taken all of that into account in building the service.”

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

Optimizely Recognized as a Leader for the 9th Year in a Row in Gartner® Magic Quadrant™ for Content Marketing Platforms

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Optimizely Recognized as a Leader for the 9th Year in a Row in Gartner® Magic Quadrant™ for Content Marketing Platforms

Optimizely - DMFS NY Summit

Optimizely recognized as a Leader for the ninth consecutive year as the CMP category shifts from AI assistance to AI execution

Optimizely, the leading digital experience platform (DXP) provider, today announced it has been named a Leader in the 2026 Gartner® Magic Quadrant™ for Content Marketing Platforms. Gartner recognized Optimizely as a Leader for the ninth consecutive year*.

The recognition marks nearly a decade of consistent placement as a Leader in the category, during a period of significant change in how enterprises plan, produce, and distribute content at scale.

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“We believe nine years of recognition from Gartner reflects what our customers already know: consistency in this category is earned, not assumed,” said Shafqat Islam, President of Optimizely. “With Optimizely Opal, we’re turning AI into an active operator by embedding agents directly into CMP workflows to plan, create, and orchestrate content with speed, governance, and measurable impact. Our vision for ‘Autonomous Ops’ is about removing friction from the entire content lifecycle so marketing and digital teams can focus on what matters most: being creative and delivering results.”

Optimizely’s Content Marketing Platform, powered by its AI orchestration platform, Optimizely Opal, unifies content planning, creation, and execution within a single system. Built for large, global enterprises across industries including banking, healthcare, and technology, Optimizely Opal agents work natively inside CMP workflows, handling tasks such as drafting and localization, chaining together multi-step workflows, and maintaining enterprise governance and brand consistency.

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“The pressure on marketing teams is real with more channels, more markets, faster timelines, and higher standards,” said Rupali Jain, Chief Product Officer at Optimizely. “Our CMP gives teams the structure to operate at scale and Optimizely Opal gives them the speed. Together, they change the role of AI from something marketers consult to something that carries out the work inside the system itself, with governance and brand safety built in from the start. ”

This recognition adds to a strong run of recent analyst acknowledgments for Optimizely. Since November, the company has also been recognized as a Leader in the 2026 Gartner® Magic Quadrant™ for Personalization Engines and a Leader in The Forrester Wave™: Digital Experience Platforms, Q4 2025.

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

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