Quisitive, a global technology consulting company, announced it has earned the status of Microsoft Frontier Partner, a distinction reserved for an exclusive list of partners with deep expertise in leading AI transformation across the Microsoft Cloud. This milestone follows Quisitive’s achievement of the Microsoft Copilot Specialization, its 19th specialization, which validates Quisitive’s ability to implement and scale Microsoft 365 Copilot, customize solutions with Copilot Studio, and develop AI agents.

Quisitive Achieves Microsoft Frontier Partner Status for Secure AI Transformation, Following Copilot Specialization

The Microsoft Frontier Partner designation recognizes organizations that lead AI transformation through an AI-first, human-led approach, combining AI agents and human ingenuity to scale innovation and impact. To qualify, partners must hold three Microsoft Solutions Partner designations and specializations spanning Copilot, Data Security, and AI application development. Quisitive goes far beyond these requirements, holding all six designations and 19 specializations, reinforcing the depth of its Microsoft partnership and the strength of its AI leadership.

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This announcement coincides with the general availability of Microsoft 365 E7, Microsoft’s new Frontier Suite, which brings together productivity, AI, security, and identity in a single platform. As a Frontier Partner, Quisitive is uniquely positioned to help customers evaluate, adopt, and operationalize E7 across their organizations, from deploying Copilot and AI agents, to implementing the governance and security controls that make AI work at enterprise scale.

“Quisitive helps customers move from AI experimentation to scalable, measurable results. Starting with technology strategy, Quisitive architects systems with security and governance built in from the start, transforms data silos into AI-ready knowledge, and activates intelligence through agentic AI applications. These milestones validate the depth behind that approach,” said Jason Hudnall, Chief Revenue Officer at Quisitive. “We are very proud to be one of Microsoft’s few Frontier partners.”

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Quisitive is a global technology consulting firm helping organizations design and activate the technology systems that power measurable business outcomes in an AI-first world. With deep expertise across the Microsoft ecosystem, Quisitive connects strategy, data, security, and modern applications to help our customers compete, scale, and adapt as the pace of innovation accelerates.

• Nectar members can now spend points at over 20 Merlin attractions across the UK, including Alton Towers Resort, Thorpe Park, LEGOLAND® Windsor Resort, Chessington World of Adventures Resort, the London Eye and SEA LIFE aquariums

• Members can also double the value of their Nectar points on tickets; for example, swap £5 worth of points for £10 off

• To redeem, open the Nectar app, select the Merlin offer, then book via the dedicated booking page

Nectar has launched a new partnership with Merlin Entertainments, giving members a new way to save on days out across the UK. Customers can now spend their loyalty points to secure entry at more than 20 Merlin attractions when they book through the Nectar app.
The offer covers popular destinations across the UK, including LEGOLAND® Windsor Resort, Chessington World of Adventures Resort, Alton Towers Resort, Thorpe Park, the London Eye, SEA LIFE aquariums, Warwick Castle, Cadbury World and more.
For even greater value, Nectar and Merlin are giving customers the opportunity to double the value of their points. For example, by simply swapping £5 worth of Nectar points customers can save £10 off Merlin ticket prices.

From world famous theme park rides to immersive indoor experiences, the partnership offers Nectar members a new way to redeem their points, turning their everyday grocery shopping into opportunities for families to visit destinations, experiences and attractions across the UK. It’s quick and easy to redeem. Nectar members simply open the app, select the Merlin partner offer, book via the Merlin x Nectar website, choose how many points they want to use at the checkout and receive their tickets by email.

Mark Given, Sainsbury’s Chief Technology, Marketing and Data Officer, said: “We know our Nectar members want great value and real rewards. That’s why our partnership with Merlin matters. It’s all about giving families fun days out for less and making every point count towards something special.”

Amir Rasekh, Nectar360’s Managing Director, said: “Making it easy for customers to spend their points is really important. By stripping out unnecessary steps, we’ve created a faster, more intuitive redemption experience in partnership with Merlin – one that’s much better for our Nectar members.”

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Stan Swinton, Merlin’s Chief Growth Officer, said: “With Nectar, we are able to offer even better access to days out and holidays for families across the UK. This partnership is another step in realising our ambition of providing affordable attractions that bring families close together through play. With Bluey the Ride: Here Come The Grannies at Alton Towers and World of PAW Patrol at Chessington World of Adventures, now is the best time for Nectar customers to enjoy the benefits of Merlin attractions and even more Nectar points.”

Nectar360 starts with the UK’s largest multi partner loyalty programme and ends with brands connecting to their customers in smarter, more meaningful ways.Working with over 900 brands, including Sainsbury’s, Argos, British Airways, Esso and American Express®, we use rich data and deep behavioural insight to understand who customers are, what they value, and how to reach them with relevance. With access to over 24 million members, we help brands, agencies and partners turn insight into loyalty — and loyalty into growth.We’re a full‑service, full‑strategy retail media network.

That means pairing data with creativity; using loyalty to fuel precision; and giving clients the clarity and confidence to plan (including CPG and General Merchandising brands like Unilever, Samsung and PepsiCo), activate and measure with impact. From omnichannel campaigns that move customers from social to shelf, to tools that unlock billions of real data points, we make every decision count.Since 2002, we’ve redefined what retail media can do – blending media, loyalty, data and insight to deliver outcomes for brands and better experiences for customers.

Merlin Entertainments is a world leader in branded entertainment destinations, offering a diverse portfolio of resort theme parks, city-centre gateway attractions and LEGOLAND Resorts which span across the UK, US, Western Europe, China and Asia Pacific. Dedicated to creating experiences that inspire joy and connection, Merlin welcomes more than 60 million guests annually to its diverse global estate in over 20 countries. An expert in bringing world-famous entertainment brands to life, Merlin works with partners including the LEGO Group, Sony Pictures Entertainment, Peppa Pig, DreamWorks and Ferrari to create destinations where guests can immerse themselves in a wide array of brand driven worlds, rides and uplifting learning experiences.

Helping enterprises unify fragmented data and build production-ready AI solutions

Wishtree Technologies Inc., an AI-native product engineering services company, today announced a partnership with Databricks, the Data and AI company. This collaboration marks an important step in Wishtree’s continued commitment to enabling enterprises to harness the full potential of their data.

The promise of AI often gets stuck in the gap between platform investment and production deployment. With Wishtree and Databricks, joint customers can bridge this gap by accessing expert engineering for solution design, delivery, and platform adoption.

Built on an open lakehouse foundation with unified governance, the Databricks platform ensures that enterprises maintain complete control over their data while accelerating the development of AI apps, analytics, and agents.

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Wishtree leverages the Databricks platform to help global enterprises across fintech, healthtech, adtech, supply chain, and HVACR build scalable data pipelines, unify data, deploy AI agents, and accelerate time-to-insight.

A unique challenge the Databricks platform solves, enables Wishtree to AI from pilots to production across fragmented legacy systems – delivering industry-specific data models, real-time pipelines, and production-grade AI agents that standard ETL tools cannot handle.

Proven on real customer platforms
Wishtree has already implemented Databricks platform on AWS for clients such as Confianza and BlueRidge, moving from brittle batch ETL to governed lakehouse architectures ready for BI and AI workloads.

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These engagements have delivered faster data pipelines, stronger governance, and cost-efficient foundations for advanced analytics and AI on Databricks.

A partnership built on real engineering
“This partnership reflects our focused investment in data and AI capabilities,” said Dilip Bagrecha, CEO and Founder of Wishtree Technologies. “Enterprises today need reliable partners who can translate data into meaningful business outcomes. With Databricks, we are better positioned to deliver modern, scalable, and impactful data solutions to our clients.”

As part of this engagement, Wishtree Technologies will work closely with Databricks to support customers across industries in:
– Building unified data platforms
– Modernizing data architectures
– Enabling advanced analytics and AI use cases
– Improving data governance and scalability

The Wishtree team builds the critical components that sit between an enterprise’s operational systems and Databricks’ AI capabilities:

Industry-specific data models for Unity Catalog. Wishtree can develop reusable data models for fintech transaction processing, healthtech claims and clinical data, adtech audience and measurement data, supply chain logistics, and HVACR service operations. These models will land directly into Unity Catalog with full governance and lineage, and will give customers a running start instead of a blank slate.

Production-grade AI agents on Agent Bricks. Wishtree will build custom AI agents, predictive models, and intelligent automation that run natively on Databricks Mosaic AI. Customers will get deployed AI features rather than just proof-of-concept demos.

Real-time pipeline engineering for Delta Lake. For use cases that demand freshness – fraud detection, inventory optimization, personalized recommendations – Wishtree has built low-latency pipelines that stream live operational data directly into Delta Lake. This replaces fragile batch ETL with real-time ingestion.

Who this partnership is for
Enterprises scaling AI from pilot to production. Many companies have Databricks and a handful of AI pilots. The challenge is moving to dozens or hundreds of production AI applications. Wishtree is set to provide the engineering capacity to scale.

Organizations with deep investments in legacy systems. If your most valuable data lives in custom-built systems, legacy ERPs, or industry-specific platforms, standard ETL tools will not get you to AI-ready. Wishtree engineers custom pipelines and data models designed for your specific systems.

New block-level change tracking capabilities enable faster backup and recovery for virtualized environments

Simplify Kubernetes operations by managing storage, data protection, and disaster recovery for AI workloads, containers and VMs directly within the Red Hat OpenShift console.

Everpure, the company revolutionizing storage and data management, announced new capabilities for Red Hat OpenShift users designed to deliver a native Kubernetes experience for managing storage and data across AI workloads, containers, and virtual machines (VMs).

“Enterprises shouldn’t have to juggle separate platforms for VMs and containers as they scale existing applications and emerging workloads like AI and edge,” said Greg Muscarella, General Manager, Portworx. “Portworx and Red Hat simplify this challenge by enabling enterprises to manage Portworx storage and disaster recovery capabilities from within the OpenShift UI. Together, Red Hat and Everpure deliver a single, powerful platform for all their workloads at scale.”

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Accelerating AI-Ready Infrastructure

As enterprises build AI foundations, they are evolving their data architectures to support the scale and speed of modern workloads. By adopting systems designed for highly efficient, automated, and intelligence-driven operations native to Kubernetes, organizations can meet modern performance demands and strict data sovereignty requirements, while maintaining consistent data services across cloud, edge, and on-premises environments.

“Red Hat OpenShift is at the core of modern enterprise transformation, delivering a hybrid application platform that can manage any workload across any environment with consistency,” said Steve Gordon, senior director, Product Management, Hybrid Cloud Platforms, Red Hat. “By bringing Portworx’s comprehensive data management—including storage, protection, and disaster recovery—directly into the Red Hat OpenShift console, we are providing a unified experience for customers to accelerate their infrastructure modernization and confidently run AI, containers, and VMs at scale.”

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New Capabilities for Data Management

Portworx Plugin 2.2 for Red Hat OpenShift brings storage and data management directly into the Red Hat OpenShift console, making it easy for teams to monitor and protect their data without using complex command-line tools. With integrated support for Red Hat Advanced Cluster Management, teams have a single pane of glass to orchestrate disaster recovery for VMs and containers across sites.

Portworx for Edge enables organizations to cost-effectively modernize their edge infrastructure. Supported on Red Hat OpenShift, Portworx helps ensure data stays local and compliant by providing automated data protection and encryption for small clusters, extending enterprise-grade data management to two-to-five node Kubernetes clusters at the edge.

The new capabilities are available now, including Portworx Enterprise 3.6, Portworx Plugin 2.2 for Red Hat OpenShift and Portworx Backup 2.11.

Retailers are sitting on more customer data than ever. Most of it is contradicting itself

Most organisations can agree on how many customers they have. Sometimes, the agreement ends there. Ask which channel best reaches a specific customer, what their lifetime value actually is, or whether they already own the product you are about to recommend, and you will get different answers from every team.

Retailers have invested heavily in omnichannel strategies, AI-powered customer experiences, and personalisation tools, yet many are building those capabilities on a foundation of data that does not align across systems. The investment is real. The unified view of the customer it depends on often is not.

Amperity’s recent expansion into the AWS Asia-Pacific (Sydney) and Asia-Pacific (Melbourne) regions brings that challenge into sharper focus for local enterprises, for whom data residency and governance are now operational requirements, not just strategic considerations.

Every team has their own version of customer data governance. Marketing deduplicates aggressively to maximise campaign reach. Analytics applies strict matching rules to avoid inflating customer counts. Operations relies on whatever the CRM says. Loyalty uses its own member ID. Each team’s logic is defensible in isolation.

However, when those conflicting views feed the same personalisation engine, the same AI models, or the same board report, the brand cannot deliver the experiences leadership is asking for.

The customer count might line up. But the loyalty programme cannot reconcile purchase history across channels because each channel defines “same customer” differently. And that is before you account for the customers who forget to scan their loyalty card, share an account with someone in their household, or never enrol in the programme at all despite being high-value repeat buyers.

Marketing sends reactivation campaigns to customers who are active in the loyalty programme but dormant in the email platform. The data is not wrong in any one system. It is wrong in aggregate.

One Amperity customer discovered that a single shopper appeared as four separate profiles in their system because they used email as their golden record. Each profile had a different lifetime value and different shopping preferences. None was a complete or accurate representation of the actual person. When that happens at scale, personalisation is not just imprecise. It is fiction.

Why customer data governance breaks down without identity resolution

Most companies govern data at the system level, and some agree on an overarching standard like email or loyalty ID. But no single identifier captures every customer interaction.

Each platform, be it email, point of sale, loyalty, support, or the data warehouse, still applies its own matching rules, its own thresholds, its own definition of what makes two records the same person. Over time, the gaps between those definitions add up.

This is the core challenge of customer data unification: not collecting more data, but connecting the data you already have into a unified customer profile that every team trusts.

Customer identity resolution connects fragmented records across systems, linking identifiers like email addresses, phone numbers, device IDs, loyalty accounts, and transactions into a single, accurate customer profile.

Identity resolution approaches fall on a spectrum. Deterministic matching links records through exact identifiers, such as a shared email address or login credential. Probabilistic and AI-based methods go further, evaluating patterns across data points to surface connections that exact matching misses, like when the same person uses different email addresses across channels or checks out as a guest in-store.

The most effective systems combine both, using deterministic rules as a foundation and machine learning to find the connections that rules alone cannot.

That gap compounds with every new tool and data source, each introducing its own governance logic. And when leadership asks the brand to personalise at scale, to recommend the right product on the right channel at the right time, the teams cannot deliver. Not because they lack the tools or the talent, but because no one has a complete picture of the customer to work from.

Try this thought experiment: pick a customer at random. How long would it take to gather enough detail to confidently send the right message, on the right channel, to drive their next purchase? Now imagine doing that for every customer.

How contextual identity graphs produce a unified customer profile

Before you can contextualise a customer, you need a complete picture. You cannot recommend the right product if you do not know what they have already purchased or returned.

You cannot choose between a discount code via SMS and an exclusive preview via email if you do not know which channel drives their purchases. You cannot calculate real lifetime value if the same person exists as four separate records.

That complete profile is the foundation. Contextual identity is what makes it useful.

Preferences change. A customer who never buys from a particular category might be shopping for a gift next week, or for someone else in their household. A full-price buyer exploring a new category for the first time might or might not respond to a promotional code.

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A single, static customer identity graph cannot handle that complexity. It forces every team into the same rigid view, and someone is always compromising.

Amperity’s Customer Data Cloud takes a contextual identity approach: purpose-built identity graphs optimised for each use case, all constructed from the same resolved foundation using first-party identity resolution.

Marketing: maximise reach. Identity graphs tuned for broad audience coverage so campaigns connect with as many real customers as possible, without duplicates inflating the numbers.

Analytics: consistency. Identity graphs built for accurate customer counts, reliable lifetime value calculations, and reporting that holds up across teams and time periods.

Operations: precision. Identity graphs optimised for transactional accuracy, where matching the right record to the right person at the right moment matters most.

Every graph is built from your first-party data. IDs stay consistent day to day. When data changes, the system learns and adapts. Connections are transparent, rules are tuneable, and every decision is auditable. No black box. No third-party data spine. No vendor lock-in.

One resolved foundation. Multiple purpose-built views. Every team works from the same truth, expressed for their specific need.

Identity infrastructure is now a compliance requirement

Transparency in data handling carries legal weight. Organisations cannot make accurate disclosures about automated decision-making unless they have clear visibility into how personal data moves through their live systems.

Consent signals, data lineage, and access controls need to be built into the foundation of customer data infrastructure from the outset.

As mentioned, Amperity’s platform is available in the AWS Asia-Pacific (Sydney) and Asia-Pacific (Melbourne) regions, allowing organisations to keep customer data resident locally while supporting performance and scalability requirements for real-time customer intelligence.

Brands that treat identity resolution as a compliance exercise end up reacting to problems. Those that build it into their data infrastructure from the start solve them before they surface, with a governed, trusted customer view that serves marketing, analytics, operations, and regulators alike.

About Amperity

Amperity’s Customer Data Cloud empowers brands to transform raw customer data into strategic business assets with unprecedented speed and accuracy. Through AI-powered identity resolution, customisable data models, and intelligent automation, Amperity helps technologists eliminate data bottlenecks and accelerate business impact. More than 400 leading brands worldwide, including Accent Group, Alaska Airlines, DICK’S Sporting Goods, BECU, and Wyndham Hotels & Resorts, rely on Amperity to drive customer insights and revenue growth. Founded in 2016, Amperity operates globally with offices in Seattle, New York City, London, and Melbourne. For more information, visit amperity.com or follow us on LinkedIn, X, Facebook and Instagram.

ZINFI Technologies, Inc. is the #1 user and analyst-rated channel management and partner ecosystem management platform for technology and manufacturing companies and the industry leader in Unified Partner Management (UPM), delivering enterprise-grade solutions for Partner Relationship Management (PRM), Channel Management, Partner Marketing Management, Partner Ecosystem Management, and Partner Incentives Management. Today, ZINFI announced the general availability of its AI-native Partner Co-Selling Management application — the most comprehensive AI co-sell platform in the partner ecosystem management category — now live inside ZINFI’s Unified Partner Management (UPM) platform. ZINFI is rated 97/100 on G2 — the highest customer satisfaction score in the Partner Relationship Management category — for the 15th consecutive quarter since 2019, based on 600+ verified G2 reviews.

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Key Capabilities at Launch

• AI-driven partner discovery and match scoring across the channel ecosystem — surfacing the highest-fit partners for each named account in seconds rather than days, with confidence scoring on every match.
• Multi-persona architecture purpose-built for Global Admins, Partner Account Managers, channel partner sales reps, and Alliance/ISV partners — every persona working in the same 12-step co-sell flow, scoped to their role.
• Privacy-first mutual opt-in and reveal engine — channel partners and vendors match accounts without exposing customer lists, and only reveal overlap when both sides agree.
• Field-level visibility governance for every matched account — channel program admins control exactly what each persona sees, with role-scoped data access end-to-end.
• Unified Co-Sell Hub for collaborative deal execution — every joint deal lives in a shared cockpit with deal-anchored tasks, categorized notes, integrated multi-channel messaging, and bidirectional CRM sync to Salesforce and HubSpot.
• Tier-based price book automation for Platinum, Silver, Bronze, distributor (Storage, Value-Added DISTI), and referral routes — applied automatically at quote time, with multi-currency support.

Closing the Co-Sell Gap Across Channel and Partner Ecosystem Programs
The partner co-selling problem is well-documented across the channel ecosystem and the partner ecosystem management category. In ZINFI’s analysis of 200+ recent discovery calls with channel and partner ecosystem leaders, 78% of programs reported that “everything is manual right now” — co-sell tracking lives in spreadsheets, partner deal-status reconciliation runs through email threads, and joint pipeline visibility breaks down at every handoff between vendor and partner. For manufacturing companies operating dealer and distributor networks, the visibility gap is wider still: 51% of channel programs report no real-time visibility into what partners are doing in shared accounts.

ZINFI’s new AI co-sell platform closes both gaps. Built into the SELL zone of ZINFI’s 8-pillar Unified Partner Management framework — spanning Partner Strategy, Recruitment, Onboarding, Enablement, Marketing, Co-Selling, Incentives, and Profitable Growth Acceleration — the application orchestrates the full 12-step co-sell flow across every persona in the program. Whether a manufacturer is co-selling through a dealer network or a software vendor is co-selling through ISV, MSP, MSSP, and VAR partners, the co-sell motion now runs on a single platform with a single analytics layer, scoped by role. Unlike CRM-native tools, ZINFI is purpose-built for partner management — requiring no Salesforce customization.

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“Co-sell is the highest-leverage motion in modern channel management and the engine of every serious partner ecosystem management strategy — and yet, until today, it has been the most manually executed motion in the entire partner lifecycle. Spreadsheets, email threads, and CRM workarounds were never going to scale to the velocity that enterprise channel programs and partner ecosystems now require, especially when account privacy is non-negotiable. ZINFI’s AI-native Partner Co-Selling Management application is the first co-sell platform purpose-built for both manufacturing channel partners and modern technology partner ecosystems — with privacy-first match-and-reveal, multi-persona orchestration, and unified analytics scoped to every role. As enterprise companies move from program-led to AI-led co-sell over the next twenty-four months, the platforms that orchestrate match, reveal, and credit attribution at machine speed will define the winners.”

— Sugata Sanyal, Founder and CEO, ZINFI Technologies

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

Meta projected that 10% of its 2024 revenue came from scams and banned goods, Reuters reported, with the social media giant internally estimating that its platforms show 15 billion scam ads a day. Meanwhile, our analysis of more than 100 million clicks found invalid click rates running about 50% higher than what Google reports. Both cases demonstrate the conflict of interest in fighting fraud.

The current model – where the platform giants act as both ad salesman and fraud policeman – is broken. In this new landscape, supercharged by increasingly autonomous bots, advertisers should no longer outsource fraud detection to the platforms that profit from it.

The ad fraud conflict of interest

At this point, fraud is more of a feature than a bug in digital advertising. Remember that most ad networks operate on a volume-driven revenue model in which every click, regardless of authenticity, contributes to the platform’s bottom line. Aggressively eliminating fraud would mean admitting their reach is smaller than marketed. These publicly traded companies face pressure to maintain traffic metrics and billable inventory. As a result, we’re more often seeing platforms catch the most obvious bots while sophisticated invalid traffic persists.

Meta’s leaked documents offer valuable insight into the inner workings. Internal memos revealed that enforcement teams track fraud but operate under strict guardrails on how to act on it. One review found the company ignored or rejected 96% of valid user reports flagging scam ads and the threshold for actually banning an advertiser required 95% certainty of fraud. Otherwise, anyone below that just got charged higher ad rates and kept running.

And actions against fraudulent advertisers were capped at 0.15% of revenue. This tells us that fraud is flagged but the bottom line matters in deciding what to do with it.

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The problem with self-reporting

A similar dynamic plays out with invalid clicks. For example, Google reports an average invalid click rate of 11.4%. Our independent analysis across 43,000 accounts, however, finds a rate of 17.8%. Adding to the issue, invalid click rates have doubled since 2010 thanks to the increased sophistication of AI-driven bots and ad fraud malware.

Since then, it’s become much harder to differentiate between human and bot engagement. This is because bad actors are using artificial intelligence and machine learning to create bots that pause on content and simulate scrolling, thereby mimicking human viewing behavior and making detection far more difficult. Additionally, they’re using malware to infect user devices, secretly drive traffic to scammer-controlled domains, and make it unclear whether ad clicks are coming from users or “ghost click farms”. In turn, ad fraud is only growing and marketers are losing about one in five dollars.

And downstream, bad data means autobidding starts chasing bot patterns and retargeting non-existent users. Google’s Smart Bidding, Performance Max, and automated campaigns start learning from signals that increasingly include traffic that isn’t real. The result is inflated cost per action (CPA), distorted return on advertising spend (ROAS), and budget being allocated to interactions that never convert. Data poisoning like this makes up look like down and down look like up.

The fact of the matter is that ad platforms have skin in the game. Right now, these corporations are essentially grading their own ad fraud homework with little incentive to accurately report the true scale and scope. It’s time for marketers to stand up for themselves and start treating every click as a security event worthy of independent verification.

How we restore accountability

We need to stop taking platform-reported analytics as gospel. Instead, the status quo demands due diligence with closer monitoring of user verification, behavioral analytics, and fraud scoring.

For example, teams can and should keep a closer eye on inflated CTRs without corresponding conversions, as well as on traffic spikes from unusual countries, to better understand actual performance. This foundation is then strengthened with independent fraud detection tools that analyze traffic patterns, device fingerprints, IP behavior, and engagement signals. These complementary solutions go a long way to creating an independent source of marketing truth.

Armed with this information, teams can better push back on the sophisticated invalid traffic they miss. And, by partnering with platforms that enable real-time metric monitoring, it’s also possible to block bad traffic before it enters the funnel and corrupts bidding, targeting, and forecasting data.

Practitioners need to go the extra mile to keep the tech giants honest. This way, we can refund more questionable clicks, show the platforms we’re watching, and better protect the integrity of campaign data.

About Fraud Blocker

Fraud Blocker, is a leading click fraud prevention software.

KYBER1 enables retailers and data-rich organizations to transform first-party commerce signals into privacy-safe audiences that can be activated beyond owned channels. Its approach emphasizes governed access, interoperability, and closed-loop measurement tied to business outcomes, without requiring partners to build full retail media networks.

KYBER1 announced its launch with a focus on helping a broader set of retailers and data owners turn first-party commerce data into scalable media and audience opportunities.

As commerce media grows, most activation remains concentrated among a small number of large networks with the scale and infrastructure to bring their audiences to market. Many other organizations hold valuable first-party data—including customer identity, transaction behavior, and product insights—but lack a practical, measurable path to activation.

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KYBER1 was built to address that gap.

The company enables retailers and data-rich organizations to transform first-party commerce signals into privacy-safe audiences that can be activated beyond owned channels. Its approach emphasizes governed access, interoperability, and closed-loop measurement tied to business outcomes, without requiring partners to build full retail media networks.

“Commerce media does not stop with owned channels, but most activation models do,” said Phil Guay, Founder and CEO of KYBER1. “A much broader set of organizations should be able to participate in this growth. Many already have the data. What they need is a practical way to bring it to market.”

KYBER1 focuses on the “middle” of the market—organizations with strong data assets but limited access to scalable activation and buyer demand. At the same time, brands and agencies face increasing fragmentation when trying to access high-quality commerce audiences beyond major platforms.

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The company’s commerce-first, agentic-designed model supports more coordinated and repeatable activation workflows, helping partners move from data to activation and from activation to measurable revenue.

KYBER1 is entering the market through pilot programs with select partners, focused on assessing data readiness, defining activation-ready audiences, and testing off-site use cases designed to demonstrate clear business value.

“We believe many data owners are closer than they think,” said Luc Cormier, VP Marketing and Customer Success at KYBER1. “They don’t need to rebuild their entire stack to get started. They need a credible first use case and a way to prove results.”

KYBER1 is also a founding member of AgenticAdvertising.org, supporting the development of open standards such as the Ad Context Protocol (AdCP), which aims to enable more interoperable activation and measurement across the advertising ecosystem.

The company is now opening discussions with retailers, commerce media teams, and data owners interested in exploring new audience and revenue opportunities.