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Smartcat Unveils New Research on the Operating Models Behind High-ROI AI in Global Enterprise Teams

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Smartcat Unveils New Research on the Operating Models Behind High-ROI AI in Global Enterprise Teams

Smartcat, the leading content and language AI platform for real-time market adaptation, released its flagship research report, The 2026 State of Global Enterprise Growth, on how enterprise teams are scaling AI ROI across global content operations.

Market expansion remains a key priority for Enterprises, and Smartcat’s research indicates that the defining challenge for global enterprises in 2026 is the ability to reach customers and employees with speed, cultural relevance, and governance, as operational complexity rises across markets and channels.

Participants included enterprise leaders and practitioners accountable for global workforce enablement, brand growth, and revenue generation. According to the research, 98% of surveyed enterprises report a significant increase in content demands over the last year. Key drivers of this strain include rising expectations for culturally adapted content, expanding omnichannel content volume, and frequent compliance updates requiring immediate, accurate, and governed changes.

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The research highlights a significant performance gap between teams reporting the strongest AI outcomes and the broader market. Content teams with the highest AI ROI are nearly seven times more likely to have achieved significantly faster localization workflows compared to their peers. Rather than using AI for isolated tasks, these teams are more likely to embed AI within connected workflows between content creation, review, localization, and maintenance.

Teams reporting stronger AI ROI are distinguished by three operating transformations: more unified workflow orchestration across content creation, review, and regional distribution to reduce manual handoffs; structured AI training that enables deeper process-level automation; and more proactive governance that integrates security and regulatory checks into workflows to maintain speed and compliance.

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To help organizations respond to rising content demand and operational complexity in 2026, the report introduces a stage-based framework to assess AI maturity and prioritize investments in technology, training, and governance to improve AI ROI and scale global operations more effectively. The framework provides a practical path for organizations looking to overcome common barriers to successful AI implementation.

“Enterprise teams are under pressure to produce more content across more channels, markets, and regulatory environments, and that pressure exposes the limits of task-level automation,” said Falk Gottlob, Chief Product Officer at Smartcat. “Our research shows that higher AI ROI comes from designing workflows that connect people, AI, and governance from the start. The organizations translating AI investment into operational impact are the ones putting clear process, training, and oversight in place, not just adding tools.”

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Protege Launches DataLab to Make AI Data a Scientific Discipline

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Protege Launches DataLab to Make AI Data a Scientific Discipline

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New research institution brings rigor and standards to the AI data layer, launching with participation from five of the world’s leading AI companies

Protege, an AI data platform providing trusted, real-world data at scale, announced DataLab at Protege, a new research institution advancing the science of AI data. Built to support leading AI labs and global technology companies operating at the frontier of AI, DataLab helps AI researchers and pioneers navigate challenges and ambiguity in data quality, selection, representation, complexity, methodology, and safety for AI research.

DataLab’s team of in-house experts and researchers innovate to produce, repackage, and surface novel training and evaluation datasets from data produced in the real world. At launch, a majority of the “Magnificent 7” AI companies and major frontier AI labs are collaborating with DataLab across various AI training and evaluation data projects.

DataLab launches at a time when AI development is increasingly shaped by data limitations. As models grow more advanced, progress depends not only on model size and compute, but also on access to high-quality, well-curated training data. Built with the same scientific ambition of a frontier model lab, DataLab brings discipline to dataset design, construction, and evaluation, establishing clear quality standards and reproducible methodologies that translate into more reliable systems and measurable performance gains.

“We understand the three core pillars driving AI: models, chips, and data. We are convinced that with the right datasets—the third, underdeveloped pillar—you can push the entire frontier forward,” said Bobby Samuels, CEO of Protege. “We created DataLab to treat data as infrastructure, not exhaust. If we want more capable, reliable systems, we need standards, reproducibility, and real scientific discipline at the data layer.”

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DataLab operates across three core areas:

  • Scientific partnerships: DataLab engages directly with leading AI researchers to navigate frontier-level technical discussions and identify commercially viable pathways.
  • Building high-value datasets and data products: Through deep methodological discipline, exposure to commercial data applications, and rigorous processes, DataLab develops new product opportunities that originate from the lab.
  • Leading AI data research: DataLab maintains an active presence within the broader academic community by publishing cutting-edge data research, designing evaluations and benchmarks, and identifying gaps in today’s training and evaluation data.

Led by Engy Ziedan, Co-Founder and Chief Scientific Officer at Protege, DataLab brings together machine learning researchers, economists, and domain experts with deep experience in evaluation, dataset design, and applied AI systems. Built to operate alongside both frontier AI research institutions and the world’s leading technology companies, the team combines academic rigor with applied expertise to raise the standards of the AI data layer.

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“The strength of DataLab is its ability to integrate perspectives that are often siloed,” said Ziedan. “Advancing AI requires more than larger models or more data alone. It requires thinking at the margin, where we weigh the marginal value of a datapoint on learning and the opportunity cost of choosing the wrong dataset. This requires disciplined dataset design, careful evaluation, and a deep understanding of real-world complexity. Our team is structured to deliver exactly that.”

Since its launch, DataLab has released multimodal healthcare benchmark datasets designed to reflect diagnostic ambiguity and longitudinal clinical context, co-designed MedScribe and Medcode, two multimodal benchmarks for healthcare, and is collaborating with frontier AI organizations on high-stakes data challenges ranging from advanced cancers to agentic task selection to audio de-identification to international healthcare representation.

“Data quality has become the defining constraint in frontier AI development, yet investment and innovation have lagged,” said Nikhil Basu Trivedi, Co-Founder and General Partner at Footwork. “That changes with DataLab at Protege, which brings the same level of rigor and expertise to AI data that we have for AI chips and models. DataLab experts are doing the essential AI data infrastructure work and research that moves the AI frontier forward.”

As AI systems move from research environments into high-stakes, real-world use cases, the strength of the data foundation becomes decisive. DataLab is inviting collaboration from frontier labs, academic researchers, and domain experts committed to raising the standards for how AI data is built, validated, and measured.

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Solidigm Introduces New AI Vision Platform, the Luceta AI Software Suite

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Solidigm Introduces New AI Vision Platform, the Luceta AI Software Suite

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Unique AI Software Platform Enables Enterprises to Build, Deploy, and Improve Visual Models Quickly Across Manufacturing, Logistics, Retail, and Other Industries

Solidigm, a pioneer in enterprise data storage, announced the launch of the LucetaTM AI Software Suite, a breakthrough AI vision platform that solves the core challenges plaguing traditional computer vision applications for quality and inspection.

“The Luceta AI Software Suite is designed to make visual AI practical and accessible for the teams closest to the data, while remaining powerful enough to improve efficiency of data science teams,” said A.J. Camber, Vice President of the AI Software Business Group, Solidigm.

“Our new software closes this gap by enabling faster data preparation and cleaning, model creation, deployment, and rapid continuous improvement in a production environment. Accelerated annotation capabilities and seamless integration across the data life cycle can enable anyone to quickly deploy new models directly at the edge, where data is generated and decisions need to happen,” Camber said.

many critical decisions still rely on manual inspection that can be slow, inconsistent, and typically limited in accuracy. Traditional machine vision systems lack flexibility and can have challenges — from rule sets that break with minor variations to lengthy programming needs for each new product setup or adjustment. Additionally, alternative AI approaches to date often require months of custom, specialized development from a computer engineer.

As enterprises across industries rapidly find new ways to collect and take advantage of visual image and video data, the applications for Luceta software rapidly expand. Example Industrial quality inspection and anomaly detection applications include:

  • Manufacturing: looking for defects in ‘orange peel’ in automotive paint, weld quality, apparel and textiles, rubber or plastic mold injection, and cracks or dents in metal stamping at line speed.
  • Safety and compliance monitoring: the detection of personal protective equipment compliance (hard hat or gloves) or detecting pedestrians near forklifts at blind corners.
  • Logistics and warehouse: counting applications to ensure ‘ship to order’ verifications and receiving mismatch reconciliation.

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Designed for Everyone

Early Luceta customer feedback demonstrates its ease of use with how quickly non-data science users can realize value. One manufacturing customer using the newly installed platform produced their first inspection model with Luceta achieving more than 90 percent precision within two weeks. After initial deployment, the same user is now able to generate new inspection models in minutes, adapting to new conditions and use cases.

The Luceta AI Software suite is comprised of multiple integrated modules:

  • Data agent – Automatically filters, groups, and annotates production images, turning raw data into labeled datasets without a lot of extra effort;
  • Model agent – Generates inspection models based on use case requirements, abstracting machine learning complexity while remaining extensible for data scientists;
  • Pipeline Manager – Deploys models directly to edge devices, integrating with existing cameras and operational workflows; and
  • Adaptive agent – Continuously improves models from production data and user feedback without manual retraining workflows.

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Key technical advantages of the new platform include:

  • Accessible to a wide range of user expertise while providing full extensibility for data scientists;
  • Edge-first architecture processes data locally, eliminating data transfer latency, costs, and privacy concerns;
  • Fully automated data selection and model convergence using generative AI techniques; and
  • Hybrid cloud strategy leverages cloud resources as elastic compute only when needed.

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Simulmedia Appoints Adam Gaynor as SVP and General Manager of Skybeam to Scale Self-Serve TV Advertising for the Performance Era

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Simulmedia Appoints Adam Gaynor as SVP and General Manager of Skybeam to Scale Self-Serve TV Advertising for the Performance Era

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Simulmedia, the leader in converged TV advertising, announced the appointment of Adam Gaynor to the newly created role of Senior Vice President and General Manager of Skybeam. Gaynor, a distinguished veteran of the advanced advertising and streaming landscape, will lead the growth and evolution of Simulmedia’s self-serve platform, reporting directly to Founder and CEO Dave Morgan.

Adam is a proven builder who has spent his career at the intersection of traditional television and the digital future

The appointment marks a strategic milestone for Simulmedia as it accelerates the expansion of Skybeam, the industry’s first self-serve platform designed to give brands and agencies direct, friction-free access to converged TV. Gaynor will oversee all aspects of the Skybeam business, including product innovation, go-to-market strategy, and revenue growth.

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“Adam is a proven builder who has spent his career at the intersection of traditional television and the digital future,” said Dave Morgan. “As advertisers increasingly demand the same precision and ease of use in TV that they expect from search and social, Skybeam is the solution. Adam’s deep expertise in programmatic, streaming, and linear ecosystems makes him the perfect leader to scale this platform and empower a new generation of performance-driven marketers.”

Gaynor joins Simulmedia with more than two decades of leadership experience across the media landscape. Most recently, he has held executive roles at organizations including Locality, where he oversaw sales and marketing; VIZIO, where he led the company’s industry-wide addressable television initiatives; and AMC Networks, where he spearheaded advanced advertising and data-driven sales. His career also includes a key leadership tenure at DISH Network, where he helped launch the company’s addressable advertising platform, consistently focusing on using technology to make television more accountable and accessible.

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“The friction that has historically defined TV buying is finally falling away,” said Adam Gaynor. “What Simulmedia has built with Skybeam is a category-defining tool: it unifies the reach of premium local linear with the precision of CTV in a single, elegant self-serve interface. I am thrilled to join Dave and the team to democratize access to the most powerful advertising medium in the world and help brands of all sizes drive measurable business outcomes.”

The launch of this new leadership role underscores the momentum of Skybeam, which leverages Simulmedia’s patented TV+® technology to provide a “system of record” for outcomes. By automating the complexities of planning and activation across a fragmented landscape, Skybeam allows advertisers to launch high-impact campaigns across streaming, cable, and broadcast with unprecedented speed and simplicity.

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Four Predictions for How AI Answers Will Redefine Marketing Performance in 2026

By
Leah Nurik
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Four Predictions for How AI Answers Will Redefine Marketing Performance in 2026

Marketing is going through a structural shift.

Search, social and advertising still matter. They haven’t disappeared. But they no longer explain how buyers actually discover, evaluate and choose brands. That work is increasingly happening elsewhere—inside generative AI engines such as ChatGPT, Google Gemini and Perplexity.

Instead of clicking through tabs, buyers now receive synthesized answers that aggregate, interpret and rank brand narratives. These answers frame markets, signal credibility and narrow options before a website is ever visited. This doesn’t replace existing channels. It rewires them by shifting where influence is formed.

Brand visibility is no longer about rankings or reach. It’s about how AI systems describe your brand in natural language, when no one is watching and whether that description helps or hurts you.

The dangerous part? Most dashboards still look fine.

The five predictions below aren’t incremental trends. There are fault lines in 2026, and they will start breaking marketing performance models.

Prediction 1: If You’re Not Measuring AI Visibility, You’re Already Behind

By mid-2026, failing to track brand presence in AI-generated answers will be malpractice. Generative Engine Optimization (GEO), also called Answer Engine Optimization (AEO), won’t be niche experiments. It’ll be table stakes, sitting alongside SEO, analytics and marketing ops. Teams will routinely track how often AI systems reference their brand, which attributes are associated with it and which competitors are framed as stronger answers to the same questions.

The casual question—“What does AI say about us?”—will stop being a curiosity and start being an executive liability.

If leaders can’t see how AI positions the brand, they won’t trust claims about awareness, authority or category leadership. AI visibility becomes a reportable surface, just like pipeline or share of voice. Not measuring it will feel negligent.

Prediction 2: Clicks Will Still Happen—But Content Dominance Will Decide Outcomes

In 2026, the collapse of the clickstream is no longer theoretical. It is operational reality.

Buyer journeys increasingly begin and end inside AI-generated answers. Discovery, comparison, and shortlisting occur without a site visit, a form fill, or a clean analytics trail. In this environment, clicks still show up, but they stop signaling influence.

What does matter is content presence, freshness, and credibility. Visibility no longer tapers off once a keyword is won. AI systems continuously reassess which sources to surface, prioritizing recent, authoritative, and consistently published content. Static content strategies decay quickly. Investment in content creation becomes a prerequisite for dominance, not a marketing nice-to-have.

Brands that treat publishing as episodic will fade from AI answers, even if their rankings remain intact. Those that publish continuously—and credibly—compound visibility over time.

Prediction 3: PR Stops Being Defended and Starts Being Required

As behavioral signals fade, AI systems lean harder on credibility. And that changes what PR is.

In 2026, PR stops being framed as “awareness” or “top-of-funnel.” It becomes essential credibility infrastructure.

AI systems rely on third-party validation, including earned media, analyst commentary, authoritative bylines and customer proof, to decide which brands are legitimate and which are noise. When clicks no longer explain trust, PR becomes the evidence layer AI uses to form judgments. This reframes PR for MarTech and RevOps leaders. It’s no longer soft, reputational or optional. It’s AI-ingested signal.

Teams that can connect PR outputs directly to AI visibility will justify investment long before marketing automation or sales engagement even enters the picture.

PR doesn’t get a seat at the table because it’s persuasive. It gets one because AI systems require external validation to make recommendations.

Prediction 4: A GEO Tool Boom—Followed by a Brutal Shakeout

Once executives can see how AI answers shape brand perception, they’ll demand control. That pressure will ignite a gold rush on GEO platforms.

In 2026, a wave of platforms will promise to measure, monitor and influence how brands appear in AI-generated answers, tracking where brands surface, how consistently they’re referenced and where competitors are winning instead.

Most of these platforms will be rushed. Many will oversimplify. Some will quietly fail. But the GEO category itself will stick.

This moment will feel familiar to anyone who lived through early SEO platforms, customer data platforms or attribution tools. Measurement creates governance. Governance establishes a budget. Budget creates platforms.

By the end of 2026, AI visibility and GEO will be operationalized, even if the tooling is still uneven. And once it’s operational, it’s no longer optional.

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What This Means for Marketing Leaders

Taken together, these predictions describe a reality many teams are already operating inside—without shared language or ownership models.

Funnels still appear intact. Dashboards still look reasonable. But influence is being shaped elsewhere, in systems most teams aren’t measuring, owning or governing.

In 2026, effective marketing organizations will do three things early—while others debate whether the shift is “real.” They will stop treating communications, content, and digital as separate disciplines and begin operating them as a unified system, because modern traffic and visibility are produced by their combined strength, not individual optimization.

Step 1: Measure What AI Says About Your Brand—Not What You Hope It Knows

AI already describes your brand using existing signals. Without direct measurement, teams are guessing. Establish a baseline for visibility, citation frequency, narrative accuracy and competitive displacement inside AI-generated responses.

Step 2: Assign Ownership of GEO or Accept Drift

AI visibility spans SEO, content, PR, brand and product marketing, making it easy to ignore. Measurement without ownership stalls. Alignment without authority fragments. Without a single accountable owner, AI narratives drift on their own.

Step 3: Consolidate Brand Messaging Into a Single Source-of-Truth Narrative

AI rewards consistency. Fragmentation produces distortion. Define how you want to be described, then align websites, media coverage, documentation and third-party validation to reinforce that position across every surface AI learns from.

Conclusion

The biggest mistake in 2026 won’t be getting AI visibility wrong. It will be assuming it happens automatically.

AI systems learn from whatever signals are most consistent, credible and available. Brands that deliberately shape those signals control how they’re described, compared and recommended. Brands that don’t inherit whatever narrative forms by default.

By the time the shift feels obvious, the leaders will already be established. Everyone else will be asking when the market moved, and why it happened without them.

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New Relic to Launch Japanese Data Center to Accelerate Enterprise Digital Transformation and Operational Excellence

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Business Wire
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New PhotoShelter Research Finds AI Accelerating Content Creation While Engagement Lags

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Japanese Data Center Marks Company’s Continued Commitment to Meeting the Needs of Local Customers and Furthering Regional Market Leadership

New Relic, the Intelligent Observability company, announced plans to launch its Japanese data center. The strategic investment will optimize New Relic’s product suite for the unique requirements of its Japanese customers and will be New Relic’s first data center in the region.

New Relic plans to launch a Japanese data center. The strategic investment will optimize New Relic’s product suite for the unique requirements of its Japanese customers, and will be New Relic’s first data center in the region.

“New Relic helps some of the most prominent Japanese companies bring impactful solutions to market. In the fast-moving AI era, observability is the engine behind Japan’s legacy of high-performance technology,” said New Relic CEO Ashan Willy. “Our new local data center is a strategic milestone that resolves data residency challenges, providing Japanese enterprises with the high-performance governance and data sovereignty required to maintain their global competitive edge.”

Japan is a critical, fast-growing market for New Relic. The company has held the number one position in observability market share for the past seven years. In addition to retail, manufacturing, and telecommunications, there has been an increase in customers from the financial and infrastructure and public services sector. In the past year, New Relic Japan grew its local employee base by 20 percent.

Anchoring its data center as a data residency hub, customers from highly regulated industries like finance and manufacturing will soon have control over domestic data residency through data collection, storage, and processing. Advanced compliance will provide a reliable foundation to meet Japanese security and privacy requirements, with the data center hosted entirely within Japan to meet strict data residency regulations. Its ultra-low latency will support real-time insights so customers can make rapid business decisions.

The data center, which will be located in Tokyo, will be available to all New Relic customers, with those in close proximity to Japan more likely to benefit from its performance. The data center will be available starting in July 2026.

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Quotes from Customers and Partners

“NTT DOCOMO welcomes the establishment of New Relic’s Japan region. The launch of this local data center will enable us to benefit from low-latency services through reduced physical distance, while also expanding the possibilities for compliance with laws and regulatory requirements in Japan. We are confident that this will accelerate the enhancement of observability for Japanese enterprises that demand high reliability, including ourselves.”

Yoshio Umezawa
Vice President, General Manager of Service Innovation Department, R&D Division, NTT DOCOMO, INC.

“We wholeheartedly welcome the launch of New Relic’s first Japanese data center in Asia. Ensuring that our data remains within domestic borders has been a long-standing governance priority for us, making this a truly long-awaited announcement. By integrating our distributed log infrastructure into New Relic, we will finally achieve ‘True Full-Stack Observability.’ With this robust domestic foundation and data centralization, we look forward to further accelerating our digital transformation toward the creation of innovative medicines.”

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Keisuke Ohara
Head of Digital Solution Dept. Digital Transformation Unit, Chugai Pharmaceutical Co., Ltd.

“We are thrilled to see the launch of New Relic’s Japan region. While we have helped many customers modernize their operations, local data residency has remained a key requirement for those in finance, government, and public infrastructure. This new domestic foundation allows us to deliver advanced full-stack observability to a broader range of clients with complete peace of mind.”

Takehiro Kobayashi
Senior Vice President, Deputy Head of Managed & Facility Services Sector, NTT DATA INTELLILINK Corporation

“The launch of the New Relic Japan region is a strategic catalyst for our mission to drive business growth through advanced IT services. With the added flexibility of a local region, we can now proactively deliver sophisticated observability solutions even to industries with the most stringent governance and security requirements. Through our deepened partnership with New Relic, we remain committed to providing services that elevate customer value and accelerate operational excellence.”

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Redslim Expands Into Asia-Pacific to Support Global Brands with Data and AI Infrastructure

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Redslim expands into Asia-Pacific to support global brands with data and AI infrastructure

Redslim

Redslim, a specialist in end-to-end data management solutions and an Astorg portfolio company, announced its expansion into the Asia-Pacific region and the appointment of Kyriakos Zannikos as Regional Director, APAC. The move marks an important milestone in Redslim’s global growth strategy and brings the company closer to clients operating in one of the world’s fastest-growing and most data-driven consumer markets.

“Expanding into Asia-Pacific is a key step in our growth journey to becoming a truly global company,” said Alberto Alcaniz, Co-CEO at Redslim. “Establishing a dedicated Asia-Pacific presence reinforces our commitment to grow alongside our clients.”

As global consumer brands accelerate digital transformation and AI adoption, many organizations still struggle with fragmented data ecosystems spanning multiple agencies, markets and datasets. These challenges are particularly pronounced in Asia-Pacific, where diverse market structures and rapid growth create complex data environments.

Redslim helps organizations transform fragmented market information into valuable data assets, empowering clients to make confident decisions and unlock the full value of their data. By building strong data foundations, Redslim supports clients as they modernize their data infrastructure and prepare for the next generation of analytics and AI-driven capabilities.

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Expanding into Asia-Pacific strengthens Redslim’s ability to support global clients operating in the region, particularly across fast-moving consumer goods (“FMCG”), consumer healthcare (“CHC”), beauty and luxury sectors. Establishing a dedicated regional presence will allow Redslim to work closely with local teams and partners while maintaining the high global standards that underpin its services.

Kyriakos Zannikos will step into the role of Regional Director, APAC, to lead this next phase of growth. An entrepreneur with deep experience across the data ecosystem and a track record of working with leading global beauty and healthcare brands, Kyriakos brings valuable insight into the region’s competitive landscape and the operational challenges faced by global organizations.

Kyriakos Zannikos, Regional Director, APAC, commented, “Asia-Pacific is one of the most forward-looking and data-driven regions in the world. Companies here are scaling fast and investing heavily in digital transformation and AI. By combining Swiss precision with strong regional proximity, Redslim is well positioned to support organizations building scalable, future-ready data ecosystems.”

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“Expanding into Asia-Pacific is a key step in our growth journey to becoming a truly global company,” said Alberto Alcaniz, Co-CEO at Redslim. “As our clients strengthen their regional focus, we are committed to investing where they invest. Establishing a dedicated Asia-Pacific presence brings us closer to our clients, enhances our support on the ground, and reinforces our commitment to grow alongside them in one of the most dynamic regions.”

The expansion represents an important milestone in Redslim’s development following Astorg’s Mid-Cap investment in November 2024. Astorg partners closely with management teams to scale specialized technology and services platforms globally, supporting Redslim as it strengthens its position as a trusted data management partner for multinational consumer brands.

Charles-Hubert Le Baron, Partner, Head of Software & Technology for Astorg Mid-Cap, said:

“Redslim exemplifies the type of specialized technology platform we seek to support in the software and data ecosystem. Positioned at the intersection of data management, analytics and AI enablement, the company addresses a critical need for organizations seeking to structure and activate their data at scale. Asia-Pacific is an important step in Redslim’s continued development as a global platform, further strengthening its ability to support multinational consumer brands operating across increasingly complex data environments.”

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Protege Launches DataLab to Make AI Data a Scientific Discipline

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Business Wire
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Protege Launches DataLab to Make AI Data a Scientific Discipline

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New research institution brings rigor and standards to the AI data layer, launching with participation from five of the world’s leading AI companies

Protege, an AI data platform providing trusted, real-world data at scale, announced DataLab at Protege, a new research institution advancing the science of AI data. Built to support leading AI labs and global technology companies operating at the frontier of AI, DataLab helps AI researchers and pioneers navigate challenges and ambiguity in data quality, selection, representation, complexity, methodology, and safety for AI research.

DataLab’s team of in-house experts and researchers innovate to produce, repackage, and surface novel training and evaluation datasets from data produced in the real world. At launch, a majority of the “Magnificent 7” AI companies and major frontier AI labs are collaborating with DataLab across various AI training and evaluation data projects.

DataLab launches at a time when AI development is increasingly shaped by data limitations. As models grow more advanced, progress depends not only on model size and compute, but also on access to high-quality, well-curated training data. Built with the same scientific ambition of a frontier model lab, DataLab brings discipline to dataset design, construction, and evaluation, establishing clear quality standards and reproducible methodologies that translate into more reliable systems and measurable performance gains.

“We understand the three core pillars driving AI: models, chips, and data. We are convinced that with the right datasets—the third, underdeveloped pillar—you can push the entire frontier forward,” said Bobby Samuels, CEO of Protege. “We created DataLab to treat data as infrastructure, not exhaust. If we want more capable, reliable systems, we need standards, reproducibility, and real scientific discipline at the data layer.”

DataLab operates across three core areas:

  • Scientific partnerships: DataLab engages directly with leading AI researchers to navigate frontier-level technical discussions and identify commercially viable pathways.
  • Building high-value datasets and data products: Through deep methodological discipline, exposure to commercial data applications, and rigorous processes, DataLab develops new product opportunities that originate from the lab.
  • Leading AI data research: DataLab maintains an active presence within the broader academic community by publishing cutting-edge data research, designing evaluations and benchmarks, and identifying gaps in today’s training and evaluation data.

Led by Engy Ziedan, Co-Founder and Chief Scientific Officer at Protege, DataLab brings together machine learning researchers, economists, and domain experts with deep experience in evaluation, dataset design, and applied AI systems. Built to operate alongside both frontier AI research institutions and the world’s leading technology companies, the team combines academic rigor with applied expertise to raise the standards of the AI data layer.

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“The strength of DataLab is its ability to integrate perspectives that are often siloed,” said Ziedan. “Advancing AI requires more than larger models or more data alone. It requires thinking at the margin, where we weigh the marginal value of a datapoint on learning and the opportunity cost of choosing the wrong dataset. This requires disciplined dataset design, careful evaluation, and a deep understanding of real-world complexity. Our team is structured to deliver exactly that.”

Since its launch, DataLab has released multimodal healthcare benchmark datasets designed to reflect diagnostic ambiguity and longitudinal clinical context, co-designed MedScribe and Medcode, two multimodal benchmarks for healthcare, and is collaborating with frontier AI organizations on high-stakes data challenges ranging from advanced cancers to agentic task selection to audio de-identification to international healthcare representation.

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“Data quality has become the defining constraint in frontier AI development, yet investment and innovation have lagged,” said Nikhil Basu Trivedi, Co-Founder and General Partner at Footwork. “That changes with DataLab at Protege, which brings the same level of rigor and expertise to AI data that we have for AI chips and models. DataLab experts are doing the essential AI data infrastructure work and research that moves the AI frontier forward.”

As AI systems move from research environments into high-stakes, real-world use cases, the strength of the data foundation becomes decisive. DataLab is inviting collaboration from frontier labs, academic researchers, and domain experts committed to raising the standards for how AI data is built, validated, and measured.

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

FreeWheel Launches AI Agent Infrastructure to Transform How Premium Video Advertising Is Bought and Sold, Pilots with PMG

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FreeWheel Launches AI Agent Infrastructure to Transform How Premium Video Advertising Is Bought and Sold, Pilots with PMG

New MCP Server and Intelligence Tools automate negotiation, optimization, and execution, advancing FreeWheel’s mission to modernize premium video transactions.

By providing a secure, open foundation for AI-driven automation, FreeWheel is enabling partners to build differentiated capabilities that work best for their needs.

FreeWheel, the leading global technology platform for the streaming advertising ecosystem, announced the launch of its new AI agent infrastructure, powered by FreeWheel’s Model Context Protocol (MCP) server and a suite of Intelligence tools. These innovations embed AI directly into the core of premium video transactions, enabling buyers and sellers to automate workflows, optimize performance in real time, and operate with greater speed and confidence. Global independent platform company PMG is among the first partners piloting these capabilities for its clients to use directly in Alli, PMG’s marketing operating system.

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FreeWheel’s MCP Server provides a secure foundation that allows AI agents to talk directly to FreeWheel’s platform and take action. Built on this infrastructure, FreeWheel’s Intelligence tools continuously monitor deal performance, analyze spend and inventory quality, track commitments, and automate routine decision-making. Together, these capabilities transform traditionally manual, fragmented processes into intelligent, always-on execution.

“FreeWheel’s mission is to modernize how premium video is transacted, and that means embedding AI directly into the systems our clients rely on every day,” said Mark McKee, General Manager, FreeWheel. “With our MCP Server and Intelligence tools, we are creating a new foundation where AI can help buyers and sellers operate more efficiently, make smarter decisions, and unlock greater value from premium inventory. Partners like PMG are helping lead this transformation by putting these capabilities into action.”

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PMG is piloting these new capabilities within Alli, enabling its teams and clients to monitor and analyze deal performance, identify opportunities, and optimize global streaming campaigns faster and more efficiently. Integrating directly with FreeWheel’s AI infrastructure allows Alli to query and act on streaming data with minimal latency.

With this deep technical bridge, PMG is advancing its ability to deliver more intelligent, automated media buying strategies.

“Often AI in our industry is just a wrapper around generic models. What we have built with FreeWheel is true technical interoperability,” said Mike Treon, Head of CTV & Video Strategy at PMG. “By connecting Alli to FreeWheel in real-time, we have given our customers an agentic AI solution that goes beyond reporting and actually understands the streaming ecosystem. We are moving past manual setup to an era where teams use our industry-leading marketing operating system to optimize complex global deals instantly.”

This launch represents a major milestone in FreeWheel’s broader innovation strategy to embed AI across its platform, making it easier for buyers and sellers to transact, integrate, and optimize across premium video. By providing a secure, open foundation for AI-driven automation, FreeWheel is enabling partners to build differentiated capabilities while advancing the infrastructure that powers the streaming advertising ecosystem.

Today’s announcement also follows FreeWheel’s recent milestone at CES, where the company introduced cross-platform agentic AI media buying for the first time alongside other industry leaders. FreeWheel will continue introducing new AI-powered capabilities throughout 2026, reinforcing its commitment to helping clients operate more efficiently and accelerating the industry’s transition toward a more intelligent, automated future.

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monday.com Welcomes AI Agents to Its Platform, Marking a Shift in How Work Gets Done

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monday.com Welcomes AI Agents to Its Platform, Marking a Shift in How Work Gets Done

monday.com logo

New infrastructure enables AI agents to sign up, access the platform, and execute work alongside human teams.

monday.com , the AI work platform that turns strategy into execution at scale, announced new infrastructure that enables AI agents acting on behalf of humans to sign up, authenticate, and operate directly within the monday.com platform.

monday.com is introducing dedicated infrastructure designed to help agents onboard and use the full capabilities of the monday platform to support their humans.

With dedicated agent onboarding and purpose-built infrastructure, monday.com now enables external AI agents to access the platform and operate alongside the humans who rely on monday.com to run their organizations. monday.com introduces a dedicated pathway designed specifically for AI agents acting on behalf of humans. Once inside the platform, agents can organize projects, update workflows, trigger automations, generate reports, and coordinate work across teams, giving their human counterparts a clear, visual view of progress and priorities.

Building on the success of monday sidekick, monday.com’s first operational AI agent embedded within the platform, and the introduction of the monday agent builder, currently in Beta, these updates expand how AI systems and AI agents specifically interact with the platform and support teams in executing work.

“As AI agents begin taking on more operational tasks, platforms need to make themselves ready for all agents,” said Roy Mann, co-CEO of monday.com. “Instead of treating agents as background integrations, we’re building the infrastructure that allows humans and AI agents to collaborate directly. monday.com is where that collaboration happens.”

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Building an Agent-Ready Platform

Until now, AI agents have typically interacted with work management platforms through indirect integrations or automation layers. monday.com is introducing dedicated infrastructure designed to help agents onboard and use the full capabilities of the monday platform to support their humans. With this launch, monday.com offers AI agents a range of capabilities designed to help them operate on behalf of their human teams, including:

  • Broad Agent Compatibility. Designed to integrate with leading AI agents and frameworks, we extend an open invitation to platforms such as Claude (Anthropic), ChatGPT (OpenAI), Co-Work (Anthropic), Frontier (OpenAI), Copilot (Microsoft), Gemini (Google), Perplexity, Cursor, OpenClaw, and Grok (xAI)
  • Dedicated Agent Signup Flow. A purpose-built onboarding experience designed specifically for AI systems operating on behalf of humans https://monday.com/agents-signup
  • Free Sign-Up And API Access Across All Plans. Agents use the same account structure and pricing model as human customers, with free sign-up and API access available across all monday plans.
  • Instant API Key Provisioning. Immediate GraphQL access to boards, items, automations, dashboards, and docs upon signup.
  • Model Context Protocol (MCP) Support. Standardized agent tool interaction across major frameworks.
  • OpenClaw Integration. Native tools and skills enabling OpenClaw agents to operate out of the box.
  • HATCHA (Hyperfast Agent Task Challenge for Access). An open-source reverse CAPTCHA designed to verify AI agents during
  • Full Enterprise Grade – AI agents operate under the same governance, security, and permissions standards as the humans they work alongside.

Together, these capabilities create a structured way for AI agents to interact with monday.com while helping their human teams plan, coordinate, and execute work more efficiently.

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Infrastructure Built for Execution

monday.com’s architecture makes it particularly well-suited for agent interaction.

Every board functions as a structured data layer, enabling precise querying, filtering, and aggregation through the platform’s GraphQL API. Agents can respond to workflow changes through real-time webhooks, trigger automations, and generate structured outputs that help teams understand and act on work.

With more than 250,000 customers running workflows across work management, CRM, service, software development, HR, IT, marketing, operations, and more, monday.com provides a shared operational environment where humans and AI agents can work together.

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Canva Introduces Magic Layers, Turning Static AI Outputs Into Editable Designs

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Canva Introduces Magic Layers, Turning Static AI Outputs Into Editable Designs

Breakthrough in Canva Design Model now unlocks ability to transform flat content and images into layered and fully editable designs

Canva, the world’s leading all-in-one visual communication platform, unveiled Magic Layers, a new breakthrough technology that turns any flat design or image into something you can edit, refine, and remix to suit your vision.

After a breakthrough from our AI research team, we’re introducing Magic Layers so anyone can take a flat image and turn it into a fully editable design inside Canva.

Generative AI has triggered a flood of visual content, but most of it remains locked in static image files. Even small changes can require starting over, with reprompts that can unintentionally alter the entire design.

Powered by years of internal research and Canva’s growing investment in its AI development arm, Magic Layers ushers in a new era of editable content, where speed meets true creative control.

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Available in public beta , it turns AI-generated content into a launchpad, not a locked file, empowering creators to refine, reshape, and perfect every detail.

How it works

Magic Layers bridges the gap between AI-generated content and true creative control by turning flat images into structured, editable layers inside the Canva editor. Fixed files are unlocked, becoming brand-ready and scalable design assets. Whether starting with a new idea or an existing design, Magic Layers brings a new level of flexibility to AI-powered content creation:

  • Upload your image, and Canva does the rest:
    • Elements are intelligently separated into individual, movable objects
    • Layout relationships are preserved automatically
    • Text remains live and fully editable
    • Outputs can be refined and iterated without starting over each time
  • Generate a fully editable design with Canva AI:
    • Go from prompt to refining in the Canva Editor in moments
    • Create visually-rich and on-brand presentations, docs, social posts and more
    • Then, move elements, swap backgrounds, or change fonts, all inside Canva

Magic Layers supports single-page .png and .jpg files in beta, with expanded capabilities in development.

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For marketing teams refreshing campaigns, small businesses updating product messaging, and creators remixing ideas, what was once a barrier is now a starting point.

“There’s been an explosion of AI-generated content that has, until now, been a dead end. You’d get a finished image you couldn’t edit, refine, or make your own. We think AI should spark creation, not stop it,” said Cameron Adams, co-founder and Chief Product Officer, Canva. “After a breakthrough from our AI research team, we’re introducing Magic Layers so anyone can take a flat image and turn it into a fully editable design inside Canva. There’s no need to start over, or to figure out the right prompt. Generation is just the beginning – real creative freedom comes from being able to edit without losing momentum.”

The Technology Behind Magic Layers

When an image is exported, flattened, or generated by AI, its structure collapses. Text becomes pixels, individual objects merge together, and the design logic that once held everything in place disappears. Until now, editing that image meant starting over.

While traditional vector tools can trace shapes by converting pixel regions into outlines, they can’t understand what those shapes represent. They can’t distinguish a headline from a background, or identify which elements belong together. Magic Layers was built to solve that problem.

Instead of simply tracing an image, Magic Layers interprets the design as a whole. It analyzes structure, identifies relationship between elements, restores text as live boxes, and separates components while preserving the original layout. The result is a fully editable design – not just traced shapes, but a set of elements that preserve the intent behind the original creation.

Canva’s Foundational AI Layer

Magic Layers is a new capability of the Canva Design Model, the company’s proprietary foundation model, and the first to generate designs that are editable from the start. Since launching in October, the Canva Design Model has generated hundreds of millions of editable presentations, documents, and social posts while also powering Canva’s integrations with ChatGPT, Claude, and Microsoft Copilot.

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Equinix Unveils the Distributed AI Hub to Simplify and Secure Enterprise AI Infrastructure

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Equinix Unveils the Distributed AI Hub to Simplify and Secure Enterprise AI Infrastructure

Integrated with Palo Alto Networks to deliver real-time threat detection for AI workloads

Equinix, Inc., the world’s digital infrastructure company®, unveiled the Distributed AI Hub, powered by Equinix Fabric Intelligence™, to provide a single, unified framework for enterprises to connect, secure and simplify their increasingly complex and distributed AI ecosystems. The Hub is a neutral location that allows enterprises to discover, connect to and consume AI infrastructure providers—including model companies, GPU clouds, data platforms, network and security services, and AI frameworks—all through private, low-latency connectivity at Equinix’s 280 high performance data centers.

“Enterprises are racing to deploy agentic AI but are finding that their existing infrastructure was never designed for the complexities of distributed intelligence,” said Mary Johnston Turner, Research Vice President, Digital Infrastructure Strategies at IDC. “By 2027, IDC expects 80% of enterprises will deploy distributed edge infrastructure to improve the latency and responsiveness of AI applications. Enterprises will need solutions like Equinix’s Distributed AI Hub to enable them to unify these disparate systems.”

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To unlock the true value of agentic AI, enterprises need to unify inherently distributed workflows: training data and inference workloads sprawled across public clouds, private data centers, edge environments and a rising wave of specialized neoclouds, each with unique performance and sovereignty constraints. This maze of silos can slow innovation, complicate governance and make it nearly impossible to run AI workloads close to the data that fuels them—limiting business impact and user experience.

That is why Equinix is taking its distributed AI infrastructure a step further with the launch of the Distributed AI Hub, giving enterprises a simple, secure, more performant way to run AI across different locations.

“AI isn’t centralized—but the right infrastructure can make it run as seamlessly as if it were,” said Jon Lin, Chief Business Officer at Equinix. “Equinix is the neutral ground where AI, cloud and networking infrastructure converge. We are providing enterprises the freedom to build and scale AI wherever their data, partners, and teams already live, while running inference close to the data and users that depend on it, without the operational drag that comes from stitching together complex, distributed systems. With our Distributed AI Hub, we’re giving customers a simpler, smarter, and far more connected way to run and scale their AI today. We are building one of the most expansive and neutral AI ecosystems.”

The Distributed AI Hub provides a unified framework that brings together data, compute, cloud platforms and AI ecosystem partners in a vendor-neutral environment. It enables enterprises to run AI workloads where they perform best without rebuilding their architecture each time or moving data to different locations. The Hub offers a simple, secure way to connect models, move data, run inferencing and manage distributed AI systems with consistent governance and control. Unlike hyperscaler AI marketplaces that favor their own services, the Distributed AI Hub is open and vendor-neutral by design, giving customers the freedom to compose their own AI stack from best-of-breed providers.

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The Hub’s first integration with Palo Alto Networks empowers customers to enable real-time protection for agent and model interactions with external tools and data sources. By combining Equinix’s global distributed AI infrastructure and high-speed, private interconnection with Palo Alto Networks Prisma AIRS real-time AI security and centralized policy enforcement, enterprises gain visibility and control over AI applications, data and interactions, across any location. Additionally, Prisma AIRS will be available on Equinix Network Edge, allowing organizations to centrally manage AI-driven security services at the digital edge, closer to users, clouds and critical workloads.

“The conversation around distributed AI is finally getting real,” said Lloyd Taylor, CTO/CISO, at Alembic. “It’s more than compute and data, it’s controlling where the data lives and how the compute runs. Equinix is framing that problem the right way, by bringing placement, governance, and predictable performance into the same architecture with the Distributed AI Hub. This is what makes distributed AI viable at enterprise scale.”

The Distributed AI Hub is available globally at 280 Equinix data center locations, enabling enterprises to deploy consistent AI infrastructure patterns worldwide. Equinix will be participating at NVIDIA GTC—located at Booth 1030—and will be previewing the Hub.

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Zendesk Advances Resolution Platform with Self-improving AI Agents from Proposed Forethought Acquisition

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Zendesk Advances Resolution Platform with Self-improving AI Agents from Proposed Forethought Acquisition

Proposed acquisition positions Zendesk to lead the agentic service era, projecting 2026 as the year AI agents will surpass human service

Zendesk expects autonomous AI to handle more service interactions than humans this year, marking a structural shift in customer service. To lead this transition, the company today announced it has entered into a definitive agreement to acquire Forethought. This proposed transaction will expand Zendesk’s AI agent offering on the Resolution Platform, operating seamlessly across all service platforms and channels.

“The era of simply managing conversations is over. The future of customer experience requires agentic capabilities built for definitive resolution,” said Tom Eggemeier, CEO, Zendesk. “Forethought’s advanced capabilities perfectly align with our vision for agentic service. Together, we will be scaling self-improving AI that learns from every interaction. But technology is just the means. Resolution is our identity, and loyalty is the outcome. This proposed acquisition will ensure our customers have the absolute best tools to drive measurable growth in the AI era.”

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“Forethought was founded on the belief that AI will transform customer experience for every business,” said Sami Ghoche, Co-Founder and CEO, Forethought. “Joining Zendesk is the fastest way to accelerate that mission. With Zendesk’s platform, resources, and global reach, we will bring our technology to many more organizations around the world, move faster on innovation, and continue pushing the boundaries of what AI can do in customer experience. For our customers, this means the same innovative products and teams they trust today will be strengthened by the scale, platform, and investment of Zendesk.”

Zendesk AI agents routinely resolve over 80% of interactions end-to-end across a broad customer base – with human and autonomous agents working in concert. The Resolution Learning Loop enables continuous improvement by learning directly from every customer conversation, without the need for manual retraining. With the addition of Forethought, Zendesk will be able to advance this into fully self-learning AI agents that can generate, adapt, and execute complex workflows across any channel or platform. Each interaction strengthens performance over time, expanding what AI can resolve independently.

Forethought AI agents by Zendesk will build on this foundation to support more complex workflows, additional channels, and a wide range of service environments. Key capabilities will include:

  • Specialized AI agents: Purpose-built AI agents for B2B, B2C, and B2E use cases by integrating Zendesk AI Agents, Unleash, and Forethought.
  • Self-improving AI backed by the Resolution Learning Loop: Detects workflow gaps, generates new procedures, and tests optimizations before deployment, enabling AI agents to improve autonomously over time.
  • Autonomous workflow execution: AI agents autonomously design and execute complex multi-step procedures, shortening time to resolution across customer journeys.
  • Native voice automation: Fully autonomous AI into voice channels, resolving high-volume, high-complexity interactions end-to-end.
  • Expanded reach into enterprise systems (e.g., computer use): Extends AI into existing enterprise systems even where APIs do not exist, eliminating manual work and unlocking previously unreachable workflows.

Forethought customers can expect uninterrupted service and continued product innovation, which will be backed by Zendesk’s global scale. Zendesk customers will gain access to expanded AI capabilities, improved support, and a more unified experience. Additionally, new customers will be able to adopt the solution independently with no requirement to use the Zendesk platform.

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The proposed acquisition of Forethought will significantly accelerate Zendesk’s product roadmap by over a year, providing immediate value to customers and reinforcing Zendesk’s commitment to driving resolutions for customers. With every business seeking a trusted partner to transition to the agentic future, the Zendesk Resolution Platform is uniquely positioned to deliver on that promise.

“To deliver a world-class customer experience today, service must be autonomous and deeply integrated. As a leader in customer success, we believe in the power of agentic AI to treat every customer like your best: Zendesk’s proposed acquisition of Forethought validates that the future of support is self-improving. For Gainsight, this deal will provide the sophisticated, cross-platform automation we need to ensure every customer interaction is intelligent, seamless, and aligned with our broader mission for driving retention for our customers,” added Chuck Ganapathi, CEO, Gainsight, a customer of both Zendesk and Forethought.

“Zendesk is making a bold statement that agentic AI will define the next era of customer experience,” said Keith Kirkpatrick, Vice President and Research Director, The Futurum Group. “At a time when many software companies are cautious or still in pilot mode, this investment reflects strong confidence in both the technology and the market’s readiness.”

The transaction is expected to close by the end of March, pending customary closing requirements, including regulatory approvals.

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Orum Achieves 36% Conversion Rate With Idomoo Personalized AI Video

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TwelveLabs Transforms UNICEF Korea's 8TB Media Archive with Video Intelligence, Reducing Search Time by 95%

Idomoo logo

Thanks to Lucas AI Video Creator, Orum created a high-quality personalized year in review at scale.

Orum delivered an unforgettable end-of-year experience for its users with a hyper-personalized video campaign powered by Idomoo’s Lucas AI Video Creator. By transforming individual data into an exciting, shareable showreel, the campaign gave customers a dynamic way to relive their biggest sales wins.

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“Idomoo’s AI video technology allowed us to produce an incredibly high-quality, engaging personalized experience. This is something we could not have achieved with a traditional approach to video production,” said Sarah Reece, Director of Demand Gen, Orum.

The videos showcased unique user achievements, seamlessly weaving in a wealth of customized stats — from the number of calls made to how they compared with users nationwide — into a compelling visual narrative. The campaign had impressively high engagement, including viewers watching their videos more than once and sharing their year in review across social media, Orum’s top goal for the campaign.

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A look at the numbers:

  • 36% conversion rate on the core CTA
  • 523% higher click-through rate compared to past emails
  • 96% video completion rate

“Our users achieve amazing results, and we wanted a special way to recognize their hard work,” said Sarah Reece, Director of Demand Gen at Orum. “Idomoo’s AI video technology allowed us to produce an incredibly high-quality, engaging personalized experience for our customers at scale. This is something we could not have achieved with a traditional approach to video production. User engagement with the campaign was 5x what we normally see via email and social. Pretty sure that means they loved it.”

“A year in review is one of the most effective ways to boost loyalty because it focuses entirely on the customer’s own success,” said Yotam Ben Ami, Idomoo CMO. “By integrating Lucas into the workflow, Orum was able to rapidly launch an exciting campaign that clearly resonated with their audience. The phenomenal engagement and share rates are a testament to what happens when you combine personalized data with AI-driven video.”

Designed to simplify complex video production while prioritizing accurate, on-brand output, Lucas handles everything from scripting to post-production, using simple prompts like text, docs and webpages.

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Comviva Launches NGAGE for Enterprises to Power Secure, AI-Driven Customer Engagement at Scale

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Comviva Launches NGAGE for Enterprises to Power Secure, AI-Driven Customer Engagement at Scale

Next-generation CPaaS platform that integrates omnichannel communication, network-based identity, and conversational AI to help enterprises deliver trusted digital experiences

Comviva, a global leader in digital transformation solutions across customer experience management, data monetization, and digital financial services, announced the launch of NGAGE for Enterprises, a next-generation CPaaS platform designed to help enterprises deliver seamless, secure, and intelligent customer experiences at scale.

Unveiled ahead of Enterprise Connect 2026, NGAGE for Enterprises empowers organizations to orchestrate meaningful customer journeys across every digital touchpoint—while embedding trust, identity, and fraud protection directly into the engagement layer. The platform combines omnichannel communications, network-based identity intelligence, AI-driven automation, and resilient global connectivity within a unified SaaS environment—helping enterprises simplify operations, accelerate deployment, and improve customer experience.

Speaking on the launch, Deshbandhu Bansal, Chief Operating Officer for the RevTech Solutions at Comviva, said, “As enterprises scale digital engagement, they are also confronting rising fraud risks, fragmented communication infrastructure, and growing pressure to deliver personalized experiences. NGAGE for Enterprises addresses these challenges by bringing together communications, identity intelligence, and AI automation into a single unified SaaS platform—enabling organizations to build trusted, scalable, and cost-efficient customer engagement journeys.”

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The platform enables enterprises to design and deploy intelligent customer journeys through an intuitive low-code workflow builder. Organizations can create personalized, context-aware interactions across service, support, marketing, and lifecycle engagement.

NGAGE supports engagement across channels including SMS, Email, RCS, and WhatsApp, while also enabling enterprises to leverage network-based identity services such as phone number verification and SIM check to strengthen security and reduce fraud.

The SaaS-based platform also offers transparent billing and real-time performance visibility, allowing enterprises to manage and optimize customer engagement strategies across regions while controlling costs.

NGAGE builds on Comviva’s established communications infrastructure, which currently supports deployments across more than 200 countries and is trusted by over 7,000 enterprises and 100+ telecom operators worldwide.

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NGAGE consolidates enterprise onboarding, configurable journey orchestration, omnichannel engagement, fraud management, and real-time usage monitoring within a unified architecture.

Built for interoperability, the platform supports TMF931 for enterprise and application lifecycle management and aligns with TM Forum Open APIs and CAMARA standards—enabling telcos to participate in aggregator ecosystems, expand go-to-market channels, and seamlessly connect enterprises to network capabilities.

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Industry First by ChurnZero Gives AI Agents Unparalleled Understanding of a Company’s Unique Processes and Product Know-How

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Industry First by ChurnZero Gives AI Agents Unparalleled Understanding of a Company’s Unique Processes and Product Know-How

AI Knowledge Sources allows ChurnZero’s ‘digital teammates’ to learn every detail and best practice within company knowledge bases.

ChurnZero, the platform and partner for customer success, has enhanced its embedded AI agents with connected knowledge source integrations—enabling them to more completely understand the nuances of any business, its products and services, the needs of its customers, and how its customer success team works. Available now, AI Knowledge Sources offers initial integrations with Atlassian’s Confluence and Zendesk Guide, with more integrations to follow shortly.

This additional knowledge further differentiates ChurnZero AI as the most context-aware and deeply embedded agentic AI within a customer success platform, providing extra confidence for ambitious teams looking to scale and drive revenue autonomously. ChurnZero’s suite of more than a dozen agents is already fueled by the most comprehensive customer datasets, ranging from call notes, sentiment, and product usage data to seamless data syncs with CRM, LMS, support and other business systems.

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“AI is only as good as the datasets it has,” says Abby Hammer, ChurnZero’s chief customer and product officer. “With datasets and sources this comprehensive—plus thoughtful engineering focused on what customer success teams really need—ChurnZero AI is transformative. Our customers are rapidly recognizing our AI agents as digital teammates, aware of and attuned to the nuances of their businesses, and reliable in a way that generic AI solutions are not.”

Customers can selectively connect their ChurnZero AI agents directly to their knowledge sources with a few clicks, maintaining detailed control of which articles, spaces, or documents ChurnZero can reference. Once enabled, the agents’ actions and recommendations will reflect this extra knowledge of products, processes, and internal playbooks. For example:

  • Echo detects dissatisfaction signals in unstructured customer engagement data and cross-references each finding against your product documentation before creating a feedback ticket. If a customer says they “can’t export reports,” Echo checks whether that feature exists before flagging it as a gap, so your product team gets filtered, validated feedback instead of noise.

  • Scribe composes customer-facing emails that go far beyond generic AI drafts. It references your knowledge base for accurate instructions, surfaces related features the customer may not be using, and weaves in best practices from internal playbooks, creating detailed, useful emails your CSM can send in seconds.

  • Consult creates custom Success Plans based on customers’ strategic goals and cross-references internal playbooks to recommend the best steps and measurable actions. Grounded in the customer’s own words and your team’s proven best practices, Consult delivers plans that feel tailored and credible, unlike generic templates.

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AI Knowledge Sources is the latest in a series of AI firsts by ChurnZero. ChurnZero was the first customer success platform first to embed generative AI, the first to incorporate AI-powered relationship scoring and analysis with Engagement AI, the first to embed purpose-built agentic AI for customer teams, and the first to launch a dedicated, in-platform AI Marketplace.

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CallRail Expands Voice Assist Real-Time Scheduling Capabilities with Addition of Google Calendar Integration

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CallRail Expands Voice Assist Real-Time Scheduling Capabilities with Addition of Google Calendar Integration

Voice Assist checks Google Calendar availability and schedules meetings in real time, helping a broad range of businesses convert callers instantly.

CallRail, the AI-powered lead engagement platform, announced a new integration between its AI voice agent, Voice Assist, and Google Calendar that enables businesses to automatically schedule appointments during phone calls handled by Voice Assist.

CallRail announces an integration between its AI voice agent, Voice Assist, and Google Calendar.

This marks the second major scheduling integration for the AI agent this year, following the recently announced integration with Calendly. With this new integration, Voice Assist can check Google Calendar availability and book meetings instantly, helping businesses convert inbound calls into confirmed appointments without requiring staff involvement.

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Turning Missed Calls Into More Revenue

For many businesses, missed calls and slow responses lead to lost revenue. Approximately 28% of business calls go unanswered, and more than 70% of customers choose the first company to respond, making responsiveness essential to driving revenue.

By integrating Google Calendar with Voice Assist, businesses can make it easy for potential customers to turn interest into action instantly. When a customer calls, the AI voice agent can answer immediately, collect key details, qualify and score the lead, provide business service details, check calendar availability, and schedule an appointment directly on a business’s Google Calendar, all while staff are away from the phone tending to their business.

“Speed-to-lead is everything for small businesses,” said Ryan Johnson, Chief Product Officer at CallRail. “When someone calls, they’re ready to take action. By connecting Voice Assist directly to Google Calendar, which is widely used by our customers, even more businesses can instantly turn that interest into a confirmed appointment, without worrying about staffing, missed calls, or manual scheduling.”

Real-Time Scheduling That Converts Calls Into Customers

Appointment scheduling is one of the most common reasons customers call businesses, accounting for roughly 20% of inbound calls. At the same time, leads are 6.4x more likely to engage with Voice Assist than voicemail, according to CallRail data. Additional benefits include:

For Businesses: Convert More Calls With Less Manual Work

  • Instant Appointment Booking: Voice Assist checks Google Calendar availability and schedules meetings in real time during inbound calls.
  • 24/7 Lead Conversion, Not Just Capture: Voice Assist doesn’t just record caller details, it converts leads to appointments, even outside business hours or while staff is away from the phones.
  • Simplifies operations: This new integration reduces the need for staff to manually coordinate appointments.

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For Callers: A Faster Way to Secure an Appointment

  • Immediate Assistance: Callers can connect with an AI voice assistant and receive help instantly, rather than reaching voicemail.
  • Effortless Scheduling: Qualified callers can book appointments live without navigating complex booking systems.
  • A Better Customer Experience: Faster responses help customers get the help they need when they need it.

“Voice Assist continues to evolve into a true AI-powered conversion engine for our customers,” Johnson added. “By giving it new capabilities like live scheduling, we’re helping businesses automate more of the work that turns leads into revenue, so their teams can focus on delivering a great customer experience.”

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Google Completes Acquisition of Wiz

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Google Completes Acquisition of Wiz

Google LLC announced the completion of its acquisition of Wiz, a leading cloud and AI security platform headquartered in New York. Wiz will join Google Cloud and maintain its brand and commitment to securing customers across all cloud environments.

This acquisition is an investment by Google Cloud to improve cloud security and enable organizations to build fast and securely across any cloud or AI platform. In today’s AI era, more businesses and governments are migrating their most important data and systems to the cloud and turning to agile and continuous software development. As these organizations operate in a multicloud environment and adopt AI, attackers are using AI to operate with greater speed and sophistication.

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Wiz delivers an easy-to-use security platform with deep expertise of cloud environments and code, connecting to all major clouds and helping prevent and respond to cybersecurity incidents. Its capabilities complement Google Cloud’s leadership in cloud infrastructure and deep AI expertise, including AI-powered threat intelligence and security operations tools.

Together, Google Cloud and Wiz will provide a unified security platform that improves the speed with which organizations can detect, prevent, and respond to threats. It will help them stay ahead of the curve by detecting emerging threats created using AI models, protecting against threats to AI models, and using AI models to help security professionals hunt for threats more effectively. The platform will also provide a consistent set of tools, processes, and policies across all major cloud environments at every layer, from code to cloud to runtime.

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The combined capability will also boost the adoption of multicloud security, enhancing companies’ ability to use multiple clouds – further spurring innovation in cloud computing and AI applications. Enterprises and government agencies can vastly improve how security is designed, operated, and automated, scaling cybersecurity teams while lowering the cost of implementing and managing security controls. The combined platform will also help protect small businesses, which often do not have the expertise and resources to protect themselves, from increasingly sophisticated and destructive cyberthreats.

Consistent with Google Cloud’s commitment to openness, Wiz products will continue to work and be available across all major clouds, including Amazon Web Services, Google Cloud Platform, Microsoft Azure, and Oracle Cloud, and will be offered through an array of partner security solutions.

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UJET Launches Agentic Experience Orchestration to Unify CX Data and AI, Automate the Agent Experience, and Consolidate Enterprise Systems

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UJET Launches Agentic Experience Orchestration to Unify CX Data and AI, Automate the Agent Experience, and Consolidate Enterprise Systems

Ujet logo

New category of CX software introduces a persistent AI layer that unifies disparate enterprise tools, supercharging the agent experience and delivering seven-figure ROI through automation and legacy system elimination.

UJET, a leader in AI-powered contact center innovation, announced Agentic Experience Orchestration (AXO), a transformative architectural framework designed to eliminate the systemic complexity that has historically hindered the customer service industry.

For decades, the CX industry has suffered from a critical bottleneck: forcing human agents to serve as the manual integration layer between real-time conversations and disconnected enterprise tools. This structural inefficiency requires agents to navigate billing, ERP, shipping, and other back-office systems during interactions, with up to 30% of productivity lost to swivel-chair data entry and accrued administrative debt.

AXO redefines this paradigm by introducing a persistent AI layer that obscures system complexity by natively integrating with enterprise-wide data and systems. This persistent automation captures data at the front end using AI-first virtual agents and maintains that intelligence throughout the entire workflow, a force multiplier increasing agent capacity and throughput, and enabling more emotive, empathetic customer connection.

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“People are essential in customer service, yet the industry’s massive bets on AI have focused almost entirely on the wholesale elimination of people, creating even more complexity and frustration,” said Vasili Triant, CEO at UJET. “AXO doesn’t replace humans, it supercharges them. We built this to solve the industry’s greatest weakness: the agent experience. By providing a persistent AI layer that automates workflows and eliminates back-end system complexity, we allow agents to focus on building relationships with customers. The true ROI of AI isn’t just in reducing headcount, it’s in the value created by empowering agents to serve customers with unprecedented efficiency and scale.”

UJET’s AXO desktop leverages customer data, contextual intelligence, agentic AI assistants, enterprise system integrations, and LLM-based, Computer-Using Agents to overcome the long-standing challenge of agents using 4-10 applications during a customer interaction. Rather than relying on AI assistants to tell the human agents what to do next, AXO empowers them to easily execute autonomous workflows with a simple click of a button.

“While the first wave of AI investment in CX focused on surface-level automation, the industry has struggled to translate that into deep operational value,” said Cathy Gao, Partner at Sapphire Ventures. “UJET’s AXO represents a fundamental shift. By introducing a persistent AI layer that orchestrates complex workflows across the entire enterprise, UJET is finally bridging the gap between a company’s data strategy and its customer experience. This isn’t just another AI tool – it’s the architectural evolution the market has been waiting for to drive real, seven-figure ROI.”

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How it works:

  • UJET’s AXO ingests historical conversations and customer data to deploy autonomous agentic AI virtual agents that allow humans in the loop to control how much or little AI to deploy.
  • These virtual agents automate low-value tasks and seamlessly escalate to humans when interactions are high-value or require emotive support.
  • Upon escalation, the AI agent stays in the loop to surface relevant customer information from the CDP/CRM based on conversational context, providing real-time summaries, suggested responses, next-best action, and click-to-execute workflow automation without the need for other, siloed business tools.
  • Computer-Using Agents then execute workflows across disparate back-office systems, even when APIs are not available (ex. filing claims, processing refunds, etc).
  • AXO then syncs structured tickets and summaries to your data lake, CDP, or CRM to maintain a single source of truth.
  • Finally, the platform continually learns from interaction outcomes, optimizing automated flows based on successful resolutions, best practices, and customer sentiment.

“UJET’s AXO platform represents a fundamental shift in how we think about AI in customer service,” said Damian Brychcy, CEO at Capital on Tap. “Rather than replacing our human agents and creating frustrating automated experiences, AXO will enable us to deliver personalized, contextual support at every touchpoint. For a fintech company serving small businesses where every interaction matters, this allows us to maintain the personal touch our customers value while handling complex queries around our product suite. AI that augments our team is essential to maintaining the service standards that define Capital on Tap.”

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Anoki and Amagi Bring Scene-Level Intelligence to In-Content CTV Ads

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Anoki and Amagi Bring Scene-Level Intelligence to In-Content CTV Ads

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Anoki’s ContextIQ™ integrates with Amagi’s THUNDERSTORM SSAI platform to scale and power smarter in-content ad formats for publishers, viewers and advertisers.

Anoki and Amagi, as part of their strategic partnership, announced the launch of In-Scene Ads powered by Anoki ContextIQ™ across Amagi’s portfolio of in-content ad formats for Free Ad-supported Streaming TV (FAST). This collaboration integrates Anoki’s ContextIQ™, the industry-leading multimodal AI platform, with Amagi’s THUNDERSTORM server-side ad insertion (SSAI) solution to offer a seamless, non-disruptive way for advertisers to engage viewers during the scenes that matter most at scale. The new offering is first available across Amagi-powered FAST channels and streaming apps.

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Traditional ad pods often disrupt the viewing experience. This joint solution moves beyond those limitations.

Industry response

Dentsu is the first partner to utilize ContextIQ In-Scene Ads in a campaign. The dentsu partnership spans the agency’s three go to market media brands, Carat, dentsu X, and iProspect.

“Anoki continues to be an innovative partner for dentsu,” said Kevin Weigand, VP, Marketplace & Partnerships – Video & Audio, dentsu. “We’re always exploring emerging formats that elevate the viewer experience in order to provide positive brand outcomes for our clients. In-Scene Ads offer a promising new way to deliver relevant messaging without disrupting content.”

The rollout builds upon Amagi’s robust ecosystem of In-Content advertising partners, including leading platforms and premium content partners.

This launch marks a significant evolution of the partnership between Anoki and Amagi, which first introduced scene-level contextual targeting to FAST in 2024. By prioritizing formats that enhance rather than interrupt the viewer experience, the partnership aims to create a more sustainable and effective ecosystem for advertisers, publishers, and audiences alike.

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A new canvas for CTV advertising

Traditional ad pods often disrupt the viewing experience. This joint solution moves beyond those limitations by unlocking previously unreachable inventory within the content itself. By leveraging scene-level video intelligence, advertisers can now align their creative with the specific sight, sound, motion, and emotion of any given scene.

“In-Content ad formats unlock previously untapped inventory, but their full value is best realized when paired with scene-level contextual intelligence,” added KA Srinivasan, Co-founder and President – Global Business at Amagi. “By integrating with Anoki’s ContextIQ platform, we’re giving advertisers a way to appear inside the content and meet audiences at exactly the right moment.”

Key features include:

  • High-Impact Formats: A suite of options including Squeeze Backs, Overlays, and Picture-in-Picture ads now enriched with ContextIQ for scene, sentiment and brand suitability without pausing the program.
  • Interactive Engagement: Brands can drive immediate actions through integrated tools like QR codes.
  • Generative AI Customization: Advertisers can use Anoki’s CreativeAI to generate GenAI versions of these formats, tailored for specific markets, seasonality, or messaging.

Raghu Kodige, Co-Founder and CEO of Anoki, said, “When you bring true scene-level video intelligence to CTV, you have access to an entirely new canvas for brand storytelling and connection. Combined with Amagi’s seamless ad insertion, advertisers gain precision targeting and creative relevance that simply hasn’t been possible before.”

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