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 AI agents, a business-aware Context Engine, and native integrations with Claude, Slack, and more help product teams instrument faster, diagnose issues in real time, and act with confidence

Acquisition also strengthens telecommunications expertise and accelerates global growth

Bounteous, an AI services firm, announced its acquisition of Cartesian, a specialist consulting firm focused on the global telecommunications, media, and technology industries. The acquisition builds on deep telecommunications experience at Bounteous and strengthens presence across North America and Europe, while enhancing capabilities in data, analytics, and AI. The move directly targets one of the biggest barriers to enterprise AI success: the data foundations that determine whether AI investments pay off.

“Cartesian has spent decades helping telecommunications and technology companies turn complex data into decisions that actually move their business. That is exactly what our clients are asking for right now,” said Sudarshan Mandayam, Chief Executive Officer at Bounteous. “The question we hear most from clients is: why isn’t our AI working yet? More often than not, the answer is the data. This acquisition gives us the capability to address that earlier and more completely than we could before.”

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Cartesian brings over three decades of experience combining strategic insight with rigorous analytics and practical expertise for clients worldwide. Cartesian’s deep data and analytics capabilities give Bounteous the tools to close that gap for their full client portfolio spanning key industries like financial services, technology, healthcare, retail, consumer goods, media and telecommunications. The combined organization will better serve shared clients and unlock new opportunities where advanced analytics and domain expertise are critical underpinnings to AI solutions.

“For over 35 years, we have helped global telecommunications and media companies turn complex operational and strategic imperatives into actionable results through our deep knowledge of the industry and our focus on data science-based delivery platforms,” said Jim Serafin, Chief Executive Officer at Cartesian. “Joining Bounteous means our clients now have a partner that can take their data foundations all the way through AI execution and enterprise-scale delivery.”

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Cartesian’s global footprint spans London, Boston, New York, and Paris, with several hundred experts supporting clients across key international markets, primarily in North America and EMEA. Cartesian’s leadership and client teams will continue under Jim Serafin’s direction as part of the combined organization.

The acquisition brings expanded scale and expertise to leading companies worldwide. The combined organization has more than 5,000 specialists across AI services, data, analytics, cloud, and experience design, serving a diverse portfolio of Fortune 1000 companies and global enterprises.

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.

They are tuning it out.

Not because AI lacks value, but because the way it is being marketed often fails to align with what buyers actually prioritize. For organizations making high-stakes, long-term technology decisions, the fundamentals still matter most: engineering quality, technical expertise, reliable delivery, and reduced risk.

The growing disconnect between what vendors emphasize and what buyers need is creating friction in the buying process and, in some cases, eroding trust.

The AI Messaging Overload

Right now, nearly every platform, service, and solution touts some form of AI integration. While this proliferation reflects genuine advancements, it has also created a crowded and often confusing landscape.

For buyers, the challenge isn’t access to innovation—it is clarity.

When every vendor claims to be “AI-driven,” true differentiation actually becomes more difficult. Messaging starts to sound the same across the board, leaving buyers unsure what genuinely matters versus what’s just baseline capability. In this crowded landscape, bold AI claims without clear context or proof points don’t signal innovation, they blend into the noise.

To break through, marketers can’t rely on generic AI language alone. They need to be more technically fluent and deeply informed about emerging technologies, so they can engage increasingly sophisticated buyers and craft messaging that rises above vague, cookie-cutter AI narratives.

What Buyers Actually Prioritize

Despite the emphasis on AI, B2B buyers consistently return to a core set of priorities when evaluating solutions:

1. Engineering Quality

Buyers want to know that a product is well-built, scalable, and designed to perform under real-world conditions. According to recent BIXA research of 480+ business buyer decision-makers, quality of engineering and technical expertise are statistically tied for the most important attributes they look for in a vendor.

2. Technical Expertise

Beyond the product itself, buyers assess the depth of knowledge behind it. Research shows that technical expertise and guidance are tied as the most important attributes buyers look for in a vendor. They prioritize teams that understand their industry, technical challenges, and implementation complexities. For instance, 97% of buyers say it is important that a vendor both understands and uses AI technologies in their own processes.

Expertise ultimately signals credibility: 41% of tech leaders who augment their existing teams with external engineers say certified AI experts make a vendor stand out—and that credibility directly reduces perceived risk.

3. Reliable Delivery

Execution matters as much as vision. Buyers need confidence that timelines will be met, deployments will go smoothly, and ongoing support will be dependable. Efficient delivery is a top-five priority for buyers, and it is the single most important factor for 17% of UK-based decision-makers. Overpromising, particularly in emerging technologies, can quickly erode confidence when delivery does not keep pace. Buyers are also pragmatic about how to build that confidence quickly — 47% value paid workshops specifically because they accelerate project momentum. Buyers also increasingly expect AI to reinforce that reliability through faster code generation and automated code reviews.

4. Risk Reduction

At its core, every B2B purchase is a risk management decision. Whether it’s financial risk, operational disruption, or reputational impact, buyers are evaluating how a solution minimizes uncertainty. A bold guarantee is the top determining factor for buyers, carrying 40% of the relative importance in their decision-making process. In fact, 88% of buyers would choose a vendor offering a 100% bug-free guarantee even if their price was 30% higher than competitors. Clear documentation, proven use cases, and transparent communication, such as through de-risking workshops favored by 34% of buyers, all contribute to lowering the #1 hesitation in the market: concerns over code quality and security.

These priorities are not new. What has changed is how easily they can be overshadowed by trend-driven messaging.

The Cost of Misalignment

When marketing narratives focus on AI but ignore these foundational concerns, a gap forms between expectation and reality. This misalignment leads to clear consequences:

• Longer sales cycles, as buyers seek additional validation and clarity
• Increased skepticism, particularly toward bold or vague claims
• Missed opportunities, when solutions fail to resonate despite strong underlying value

In some cases, the emphasis on AI can even distract from a company’s true strengths. A well-engineered product with a track record of reliable delivery may be far more compelling than a newer, AI-heavy offering that lacks maturity. But if the messaging doesn’t reflect that strength, buyers may never fully recognize it.

Reframing the Narrative

The solution isn’t to move away from AI, it’s to stop pretending the tools are the transformation.

The teams winning with AI aren’t the ones with the most tools. They’re the ones that changed how their engineers work. This is a people and process problem, not a procurement decision—and most vendors avoid saying it because it’s harder to sell.

The shift in messaging is simple but demanding: stop leading with what the technology is and start with what it takes to make it work. That means structured workflows, validated output at every stage, and a clear acknowledgment that AI without governance doesn’t reduce costs—it increases them. AI usage is not free; it is metered in tokens and accumulates quickly.

There’s also a risk that almost no transformation partner raises: internal resistance. AI champions inside a client organization pull ahead. Resistors create drag. If you don’t address adoption at the engineer level from day one, the transformation fails at the people layer, not the technology layer. Buyers should be asking their vendors how they handle this. Most can’t answer.

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Questions to challenge yourself and your teams:

• Is your AI architected well enough that the economics actually work?
• Do you have a structured methodology or just a capability?
• What happens when your engineers resist?

Building Trust Through Substance

Trust is the currency of B2B relationships. It is built through consistency, transparency, and proof. In a market saturated with AI claims, substance is the differentiator.

• That substance shows up in four ways:
• Clear, specific use cases that demonstrate real-world impact
• Technical depth that proves how solutions are built and maintained
• Evidence of reliability, backed by performance metrics and long-term customer outcomes
• Honest communication about capabilities and limitations

When buyers see that a company is willing to go beyond surface-level messaging, it signals confidence—and that confidence is often more persuasive than any single feature or capability.

The Opportunity Ahead

The current wave of AI enthusiasm is real, and so is the backlash forming underneath it. Buyers aren’t rejecting AI. They’re rejecting the version of AI that showed up late, overpromised, and left their teams holding the complexity.

The companies that will win this window aren’t the ones with the boldest AI narrative. They’re the ones who can answer the questions a sophisticated buyer will eventually ask: Is your AI architected well enough that the economics actually work? Do you have a structured methodology or just a capability? And what happens when our engineers resist?

Bad AI is expensive AI. Buyers are starting to do the math, and the vendors who can’t show their work are going to lose deals they don’t even know they’re losing.

The fundamentals haven’t changed. Proof, expertise, reliable delivery, and reduced risk. What’s changed is that AI has raised the stakes on all of them. The companies that understand that distinction – and can demonstrate it – are the ones that will eventually define this market.

About Vention

Vention is the premier global leader in software engineering, synonymous with technology designed for scale and the common denominator behind the world’s most successful tech-empowered enterprises, industry innovators, and startups.

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.