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

Moloco logo primary

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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prweb
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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.

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

USA TODAY Co., Inc. Logo

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.

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“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.

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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

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

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.

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

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.

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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.

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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

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

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.

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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.”

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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.

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“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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Business Wire
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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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From ChatGPT to Claude and Grok: AI.cc’s One-API Solution Powers Next-Gen AI Agents and Applications

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.

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

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.”

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

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.”

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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.

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

“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.

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Optimizely ‘Opal University’ Participants Build 375 AI Agents in Five Days as Demand Grows for Hands-On AI Training

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Optimizely ‘Opal University’ Participants Build 375 AI Agents in Five Days as Demand Grows for Hands-On AI Training

Optimizely - DMFS NY Summit

First training cohort draws 1,500-plus signups as enterprise teams turn to structured AI workflows that deliver up to 95% time savings

Optimizely, the leading digital experience platform (DXP) provider, today shared new data from its Opal University program, highlighting growing momentum for Optimizely Opal, its agent orchestration platform for marketing and digital teams, and signaling increased demand for hands-on AI training across the enterprise.

In the first two weeks, more than 1,100 marketing and digital leaders signed up for Opal University, with a waitlist for future cohorts now over 1,500. In its initial cohort, 50 participants built 170 AI agents in five days, with many already delivering measurable time savings across core marketing workflows.

The results highlight a broader shift in how marketing teams are approaching AI. While adoption of AI tools and generative platforms continues to grow, most organizations are still in the early stages of applying AI in a structured, repeatable way across their workflows.

“The teams that are actually winning with AI right now are focusing on change management and ensuring adoption happens not just because of top-down push but because marketers can get time back to create and optimize powerful campaigns,” said Allison Skidmore, Chief Customer Officer at Optimizely. “That’s exactly why we built Opal University. When marketers get hands-on time building agents that work for their workflows, adoption follows because they feel the benefit directly. That’s how you scale AI across the entire marketing lifecycle.”

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

From interest to impact in days

Opal University is a free, hands-on certification program designed for senior marketing leaders. Each five-day cohort walks participants through building three AI agents tailored to their organization’s needs, with a focus on immediate, practical application.

Early results include:

  • 1,500+ sign-ups to date

  • 375 AI agents built by over 60 participants in five days across two cohorts

  • 80% to 95% time savings reported across recurring weekly workflows

Participants represent a broad mix of global enterprises, including Canva, Asana, LinkedIn, Zoom, DocuSign, KPMG, Deloitte, Bloomberg, EY, and Foot Locker.

Across both cohorts, participants built agents spanning a wide range of marketing functions, including:

  • 70 agents for SEO, GEO and AI search optimization

  • 39 agents for content operations

  • 30 agents for CRO and experimentation

  • 28 agents for research and intelligence

  • 26 agents for customer success and sales

  • 16 agents for compliance and QA

  • 14 agents for productivity and ops

In practice, these agents are already reshaping how teams work:

  • A CRO prioritization workflow was reduced from several hours to 30 minutes

  • Performance benchmarking and analysis dropped from six hours to 18 minutes

  • Content migration timelines were reduced from seven to 10 days to about two days

  • Prospect research and landing page generation that previously took hours per week can now be completed in two minutes

Moving beyond AI pilot projects

The strong response to Opal University reflects a common challenge across the market. While teams are eager to use AI, many lack the frameworks and integration training needed to apply it consistently across campaigns, content and experimentation.

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Optimizely Opal addresses this gap by embedding agentic AI directly into the Optimizely platform, connecting content creation, campaign management, experimentation and personalization into a single workflow. This allows teams to move beyond isolated use cases and operationalize AI across the full marketing lifecycle.

“Most teams are still running AI in pockets because MarTech has become too complex for it to work any other way,” Shafqat Islam, President at Optimizely added. “What Opal does is absorb that complexity — the governance, the brand context, the orchestration — so teams can build agents that understand their brand, their data, and their processes, and reuse them across the whole organization. That’s why we’re seeing adoption accelerate the way we are.”

This approach is already reflected in broader platform benchmarks, with Optimizely reporting a 79% increase in experiment velocity, an 85% increase in campaigns delivered, a 54% faster speed to market and an 80% increase in pages created.

Building the next generation of AI-native marketing teams

Opal University will continue as an ongoing program with weekly cohorts, designed to help senior marketing leaders build practical AI skills and scale those capabilities across their organizations. Participants receive certification, access to a dedicated community and early access to new features and agents.

As adoption grows, Optimizely is expanding its agent ecosystem through its directory of ready-to-use agents. In 2026 alone, the company has launched more than 15 out-of-the-box agents designed to help marketing and digital teams improve GEO performance, stay ahead with competitive analysis and run more impactful experimentation programs.

The company will continue to introduce new agents alongside deeper integrations across the platform, helping teams apply AI consistently across content, experimentation and personalization workflows.

Optimizely is helping pave the way for a more AI-native approach to marketing, where teams can plan, execute and optimize campaigns through coordinated, governed workflows that improve speed, consistency and performance.

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Sprinklr Unveils Next Wave of AI‑Native Customer Experience Innovation with Spring ’26 (26.4) Release

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Sprinklr Unveils Next Wave of AI‑Native Customer Experience Innovation with Spring ’26 (26.4) Release

File:Sprinklr Logo.png - Wikimedia Commons

  • As AI Agents autonomously resolve more customer issues and deliver measurable business outcomes, Sprinklr’s new autonomous evaluation capability provides transparent, test‑backed, explainable validation — helping teams understand, trust, and continuously improve agent performance.

  • AI+ Studio (a centralized, no-code workspace to build, manage, and scale GenAI agents and workflows) provides simple tools to test AI in bulk and monitor its behavior, giving teams clearer oversight and control.

  • Marketing Copilot introduces deeper conversational automation and performance insights for social and paid teams.

  • Powerful enhancements across Voice of the Customer, Marketing, and Customer Service—delivered through Sprinklr’s Unified-CXM Platform—transform how enterprises listen, learn, automate, and act at scale.

Sprinklr , the AI‑native Unified Customer Experience Management (Unified‑CXM) platform, today announced the Spring ’26 Release (26.4) — a major advancement in AI‑powered insights, marketing automation, service intelligence, and platform governance. This release deepens Sprinklr’s AI leadership with new agentic and copilot capabilities, precision listening, governed automation, and a next‑generation foundation for safe, scalable enterprise AI.

“With the Spring ’26 Release, we’re taking a major step forward in how enterprises drive outcomes with AI,” said Karthik Suri, Chief Product and Corporate Strategy Officer at Sprinklr. “As AI Agents resolve more customer issues autonomously, we’re giving teams the transparent, test‑backed validation they need to trust and scale them. Paired with a more intuitive AI+ Studio and smarter copilots across the Sprinklr suite, these advancements help brands turn automation into measurable impact — and ultimately into more seamless, personalized moments of customer delight.”

Sprinklr AI: Smarter Intelligence Across the Suite with Expanded Copilots

Recently named a leader in the 2026 Gartner® Magic Quadrant™ for Voice of the Customer Platforms, Sprinklr continues to strengthen VoC capabilities with Customer Feedback Copilot, transforming feedback into accurate insights, visual trends, comparisons, and multi‑level drilldowns. Marketing Copilot brings conversational automation to social and paid workflows — helping teams explain performance changes, summarize engagement, and build analytics widgets instantly, while Deep Research provides structured, cited analysis for faster decision‑making.

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Sprinklr Service: Contact Centers Gain Transparent, Test‑Backed AI

As AI Agents are rapidly deployed to autonomously deliver more measurable business outcomes, Spring ’26 introduces Autonomous Evaluation — providing clear, explainable logs and test‑backed validation so teams can understand, trust, and continuously refine agent behavior. Agent Copilot is now proactive, offering real‑time nudges that improve core service metrics like first call resolution (FCR) and average handle time. Service organizations can also streamline operations with automatic shift bidding for fair, preference‑aligned scheduling and guided service analytics that unify KPIs and accelerate insight‑to‑action workflows.

Sprinklr Insights: Higher‑Fidelity Listening and Unified, Actionable Intelligence

Sprinklr is strengthening the entire insights workflow — from how signals are captured to how teams activate them. AI Topics now use GenAI enrichments to filter out noise and surface only the social and conversational mentions that truly matter to brands, driving far more precise listening. With unified, governed customer profiles consolidating feedback and signals across channels, teams gain a consistent, complete view of each customer without digging through dashboards or disconnected data. Expanded support for global Web Surveys — including one-click localization, stronger governance, and intelligent sampling — helps organizations capture cleaner, more representative feedback at scale. And with Action Plans now extended across the Insights suite, teams can operationalize insights immediately by creating tasks, assigning owners, and tracking progress directly inside Sprinklr.

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Sprinklr Marketing & Sprinklr Social: Modern Marketing Powered by Automation and Creative Integration

Marketers can now easily create on‑trend, compliant video content with access to TikTok’s Commercial Music Library. New integrated workflows with Canva’s Digital Asset Management system streamline how teams import creative assets while strengthening brand governance across channels.

Sprinklr is also enhancing performance insights by automating root‑cause analysis for sudden shifts in campaign results and providing a unified dashboard comparing pre‑ and post‑boost metrics. Additionally, teams can now track and optimize seller profile performance on LinkedIn, giving marketers deeper visibility into how social selling efforts are performing.

Sprinklr Unified-CXM Platform: A More Open, Governed, Self‑Service Platform

New bulk testing and AI telemetry in AI+ Studio help enterprises evaluate AI performance at scale. Additional platform upgrades include unified integration management through the Sprinklr Marketplace, CRON-based automated ingestion via the UDC Connector, AI‑powered guidance through Sprinklr Assist, and next‑generation compliance controls with DRP 2.0.

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Teradata Launches Analyst Agent on Microsoft Marketplace for AI-Assisted Business Decision-Making

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Teradata Launches Analyst Agent on Microsoft Marketplace for AI-Assisted Business Decision-Making

Move from insight to action with Teradata Analyst Agent—designed for business and data analysts, with built-in telemetry for transparent, governable AI

Teradata announced the availability of its enterprise-grade Analyst Agent on Microsoft Marketplace, bringing AI-assisted, conversational analytics directly into customers’ existing Azure environments. Microsoft Marketplace is the unified online destination for customers to buy trusted cloud solutions, AI apps, and agents to meet their business needs. Teradata customers can now discover and deploy trusted solutions through Microsoft Marketplace, with smooth integration and streamlined management across Microsoft Azure and other Microsoft products.

About the Teradata Analyst Agent
The Teradata Analyst Agent enables business and data analysts to ask questions and explore data through a conversational interface, without needing to write code or build BI reports. The agent orchestrates complex SQL queries on the Teradata platform, performs iterative analysis, and surfaces supporting visualizations to help users understand patterns, trends, and outcomes faster.

At the core of the Analyst Agent is Agent Telemetry, developed by Teradata to capture execution details for every request – including performance, estimated cost, model usage, agent orchestration steps, and user feedback. This makes the agent’s reasoning and behavior observable and auditable, replacing “black box” AI with a transparent, continuously improvable system. Customers can also configure quality signals to monitor based on their business priorities – such as detecting orchestration loops, identifying prompt weaknesses, or flagging hallucinated results – turning raw telemetry into actionable intelligence that improves agent performance over time.

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Key Benefits of the Teradata Analyst Agent on Microsoft Marketplace

  • Seamless Integration: Designed to work effortlessly with existing Teradata environments, Teradata Enterprise MCP, and Azure platforms, minimizing integration complexity.
  • Transparent, Governable AI: Built-in Teradata Agent Telemetry provides full visibility into agent planning, execution steps, performance, estimated cost, quality signals, and user feedback—supporting governance, optimization, and trust at scale.
  • Interactive, Insight-Driven Experience: A conversational UI designed for business and data analysts—not just technical users—surfaces visualizations alongside answers, helping users move from question to understanding to action without writing a single line of code.
  • Configurable Quality Signals and Guardrails: Customers can define which quality signals matter most and enforce customizable guardrails aligned to enterprise policies, compliance needs, and risk tolerance.
  • Faster Time-to-Value: A pre-built, Analyst Agent for Azure and extensible multi-agent template reduces development effort, shortens deployment cycles, and enables teams to move from experimentation to production quickly.
  • Cost Efficiency: Reduce upfront investment and leverage shared innovation for a lower total cost of ownership.
  • Customizable AI Services: Expert guidance provided by Teradata AI Services to align with enterprise architecture, governance standards, and business requirements.

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Executive Quotes
“Enterprises don’t just need AI that can answer questions, they need AI they can trust, govern, and continuously improve,” said Sumeet Arora, Chief Product Officer, Teradata. “By bringing our Analyst Agent to Microsoft Marketplace with built-in Agent Telemetry, we’re giving organizations a practical, transparent path to operationalizing agentic AI where their data already lives – within their existing Azure environments.”

“Microsoft Marketplace helps organizations and partners move faster, work smarter, and grow by connecting them with the right solutions—all in one trusted place,” said Cyril Belikoff, vice president, Microsoft Azure Product Marketing. “We’re happy to welcome Teradata’s Analyst Agent solution to the growing Microsoft Marketplace ecosystem.”

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Philo Selects Reelgood to Power Content Intelligence and Personalization Across Its Streaming Platform

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Philo Selects Reelgood to Power Content Intelligence and Personalization Across Its Streaming Platform

Reelgood for Business

Partnership integrates AI-powered metadata into Philo’s machine learning infrastructure to sharpen recommendations and deepen audience understanding

Philo, the San Francisco-based live TV streaming service, has selected Reelgood to provide content metadata, catalog intelligence, and historical availability data across its U.S. programming. Reelgood, the streaming data and metadata platform tracking more than 300 streaming services across 25+ countries with a database of 4MM+ titles, will deliver daily-refreshed metadata covering Philo’s complete catalog via automated data exports.

We needed a metadata partner that could support our machine learning work at the level of quality and coverage it requires. We chose Reelgood because of the depth of its metadata infrastructure.”

— Sai Vuppalapati, Lead Product Manager, Data and Machine Learning, Philo

The partnership integrates Reelgood’s metadata platform directly into Philo’s machine learning infrastructure, giving Philo’s product and data teams the content intelligence foundation they need to advance personalization and deepen audience understanding at scale. Philo also gains access to Reelgood’s cross-platform content intelligence, providing real-time visibility into which titles and genres are resonating across the broader streaming ecosystem. That signal informs both recommendation logic and content acquisition strategy, helping Philo stay ahead of shifting audience tastes and ensure its library reflects where viewer demand is heading.

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“We needed a metadata partner that could support our machine learning work at the level of quality and coverage it requires. We chose Reelgood because of the depth of its metadata infrastructure, which is central to how we build content understanding and a recommendation system. We love that its cross-platform signals give us a meaningful view into what’s trending outside our own network.” — Sai Vuppalapati, Lead Product Manager, Data and Machine Learning, Philo

Reelgood’s platform uses proprietary machine learning models to match, clean, and maintain metadata at scale, refreshing streaming availability across hundreds of services continuously, and applying AI-powered taxonomy to ensure that genre and sub-genre classifications are accurate, consistent, and ready to use. For Philo, this means access to structured content intelligence that can be applied directly to recommendation ranking, audience segmentation, and content acquisition decisions, with the reliability that machine learning work requires.

Beyond core metadata, Reelgood provides Philo with current and historical title availability across more than 300 streaming services, with records dating back to 2019. For content and licensing teams, knowing where a title has been available and during which windows is foundational to acquisition decisions. The longitudinal dataset also supports competitive catalog strategy, tracking how rival services are investing across genres and where licensing opportunities are emerging.

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“Philo’s experienced teams understand that any recommendation engine is only as good as the metadata feeding it. They came to us for complete, deduplicated coverage refreshed daily. And its content team came for the historical availability for every show and movie, so it can make licensing decisions based on evidence, not guesswork. We’re seeing more teams reach the same conclusion.” – David Sanderson, CEO & Founder, Reelgood

“Reelgood will help us better understand what our audiences want to watch and how to connect them with it. That means stronger recommendations across the content we already carry, and identifying gaps in our library where viewer demand is heading, so we can go out and acquire it. High-quality machine learning depends on high-quality metadata, and Reelgood gives us that foundation.” — Edward King, Chief Product Officer, Philo

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StackAdapt Launches Industry First Live Events Campaign Workflow for CTV

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StackAdapt Launches Industry First Live Events Campaign Workflow for CTV

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New capability helps advertisers plan, pace, and activate campaigns around live sports moments with greater transparency and control

StackAdapt , the leading AI advertising and orchestration platform, announced the launch of its dedicated Live Events campaign workflow designed to help advertisers activate and manage CTV campaigns during live sports moments. The new workflow introduces a centralized planning hub, a dedicated campaign subtype, and enhanced pacing and frequency controls tailored for the short, high-demand event windows that define live sports advertising.

As more broadcasters and streaming platforms introduce programmatic access to live sports, advertisers have new opportunities to reach audiences during premium live moments. At the same time, audience demand continues to grow as sports viewership shifts from linear television to streaming environments. Digital live sports viewership in the U.S. is projected to grow from 114.5 million viewers in 2025 to more than 137 million by 2029, reaching nearly 40% of the population, according to EMARKETER. Major global events like the 2026 FIFA World Cup are expected to accelerate this trend further, creating powerful opportunities for brands to reach highly engaged audiences in real time.

Yet traditional CTV campaign workflows are designed for always-on delivery models, making it difficult to manage the sudden demand spikes, pacing constraints, and inventory coordination required during live events. StackAdapt’s Live Events campaign workflow addresses these challenges with a purpose-built solution designed specifically for live sports advertising within CTV, making premium live sports inventory more accessible to advertisers.

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Key benefits include:

  • Purpose-Built Live Events Workflow: Advertisers can launch campaigns using a dedicated Live Events campaign subtype designed specifically for live sports activation.
  • Simplified Event-Based Planning: A centralized inventory hub and integrated calendar allow advertisers to discover upcoming sports moments and align campaigns with specific events.
  • Pacing For High Demand Moments: Pacing settings to ensure campaigns spend effectively during unpredictable traffic spikes.
  • Protect the Viewer Experience: Frequency controls to ensure ads don’t appear on repeat, creating a poor brand experience and ad fatigue.
  • Greater Transparency into Performance: Package-level reporting and improved delivery visibility provide clearer insights into live sports campaign performance.
  • Access to Premium Live Sports Inventory: Advertisers can activate campaigns across premium broadcast and streaming partners without rigid spend minimums or complex planning requirements.

“Premium live events have become one of the most valuable environments in streaming, but it’s also one of the most operationally challenging for advertisers to execute effectively,” said Greg Joseph, VP of Inventory Development at StackAdapt. “With a dedicated Live Events workflow, advertisers gain a simpler and more reliable way to plan and activate campaigns around major sports moments while maintaining full visibility and control over pacing and performance.”

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StackAdapt’s Live Events campaign workflow is designed specifically for the operational realities of live sports, combining event discovery, event-based pacing controls, and transparent reporting within a single interface. The platform’s infrastructure also supports the high-concurrency traffic environments live sports generate, helping ensure reliable campaign delivery during periods of intense demand.

“Live sports has always been high impact but difficult to execute,” said Sarah VanLandingham, Associate Director, Media Strategy at Silverback Strategies. “With StackAdapt’s dedicated Live Events workflow, we finally have more confidence in how our campaigns will pace and perform during critical moments. The added transparency and controls make it easier to activate around premium inventory without overcomplicating our setup.”

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Uniform Appoints Industry Veterans to Accelerate Next Phase of Growth

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PRNewswire
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Uniform Appoints Industry Veterans to Accelerate Next Phase of Growth

Uniform, a leader in digital experience management, announced the appointment of Gary Roberts as Board Director and Jason Crea as VP of Growth, strengthening the company’s leadership as it executes on ambitious global growth plans.

Roberts brings decades of senior-level experience advising and scaling technology-led organizations, with a proven track record of helping companies move from high-growth stages into sustained market leadership. Known as a trusted operator and board-level advisor, he has supported leadership teams through periods of rapid expansion, product innovation, and commercial scale.

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Crea joins Uniform with a strong track record of scaling technology businesses at critical inflection points. Most recently, he served as Chief Revenue Officer at Cherwell Software, where he led commercial strategy and revenue operations during a period of significant growth. Prior to that, Crea held senior leadership roles at Sitecore, where he was instrumental in scaling the company’s US operations, expanding its enterprise footprint and go-to-market reach across the region. His deep experience in the digital experience and enterprise software ecosystem, combined with a hands-on approach to building high-performing revenue teams, makes him ideally suited to drive Uniform’s next chapter of growth.

“Gary and Jason are true veterans of building and guiding technology businesses,” said Lars Petersen, CEO of Uniform. “Their experience, pattern recognition, and steady leadership will be invaluable as Uniform accelerates growth, expands our ecosystem, and continues to define the future of composable digital experiences.”

As Board Director, Roberts will work closely with Uniform’s executive team to support strategic planning, go-to-market execution, and operational scaling, ensuring the company maintains focus while growing aggressively across enterprise, partner, and global markets. His guidance will be particularly valuable as Uniform deepens relationships with technology partners and agencies, expands its customer footprint, and continues investing in its platform and community.

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As VP of Growth, Crea will spearhead Uniform’s commercial expansion, bringing the operational discipline and scaling playbook he refined at Sitecore and Cherwell to bear on Uniform’s rapidly growing pipeline. He will focus on accelerating customer acquisition, strengthening partner channels, and building a repeatable growth engine to match the company’s ambitious market opportunity.

Uniform has already demonstrated strong momentum, including significant venture backing and continued expansion of its composable digital experience platform, positioning the company to meet increasing enterprise demand for flexible, scalable digital experience solutions.

“I’m excited to join Uniform at such a pivotal stage,” said Gary Roberts. “The team has built a category-defining platform with enormous market opportunity. I look forward to supporting the company’s leadership as they scale responsibly, move fast, and capitalize on the momentum they’ve created.”

“Having spent my career scaling companies in the digital experience space, I see enormous potential in what Uniform has built,” said Jason Crea. “The platform, the team, and the market timing are all aligned. I’m looking forward to helping Uniform capture the growth opportunity ahead and bring composable experiences to more enterprises worldwide.”

Both appointments reinforce Uniform’s commitment to pairing innovative technology with experienced, proven leadership as it enters its next phase of growth.

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

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