Treasure AI Recognized as a Leader in the IDC MarketScape Worldwide AI-Enabled Customer Data Platforms for B2C Users 2026

Real-Time Isn't a Feature. It's the Whole Point.

Every Customer Data Platform (CDP) vendor will tell you they support real-time data. Almost none of them mean the same thing by it.

For most of the category's history, "real-time" meant a profile updated within a few minutes instead of overnight. That was a meaningful improvement over batch ETL, and for a decade it was enough. We believe it’s not enough anymore. Brands are now asking their CDP to hand a live, trustworthy customer record to an AI agent that must decide something (suppress this send, surface this offer, escalate this case) in the same second a customer's behavior changes. A five-minute delay isn't a rounding error at that speed. It's the difference between a good decision and an automated mistake that already reached the customer before anyone could catch it.

That's the backdrop for the news: IDC MarketScape named Treasure AI a Leader in Worldwide AI-Enabled Customer Data Platforms for B2C Users¹.

Why we believe buyers are actually switching CDPs

IDC MarketScapes are not built around vendor pitches. Across the information gathered by IDC analysts for this evaluation, the most cited reasons buyers replace an existing CDP were “data readiness and quality, inability to demonstrate ROI, scalability or real-time performance issues, and AI features that did not work in practice.”

Read that list again and notice what it's actually describing. We believe none of those are feature gaps. They're trust gaps. A brand doesn't rip out a CDP because it's missing a connector, they rip it out because the data it produced couldn't be trusted to make a decision on, fast enough, at the volume the business actually runs at. That's the exact problem we built Treasure AI to solve, because trust is non-negotiable when it comes to customer data. Agentic AI without governance is a liability, not an innovation.

Treasure AI is Built for the Modern Customer Data Foundation

A shared model starts with the Diamond Record. Our Intelligent CDP unifies first-party, anonymous, and off-platform data into a single governed customer profile. Parent Segment architecture lets teams define an attribute, behavior, or score once and reuse it across segmentation, journeys, activation, analytics, and AI workflows. With Treasure AI Studio providing a web, desktop, mobile and CLI AI-native workspace, no team, and no agent, is ever working from a stale or duplicated copy.

Deployment meets the data where it already lives. Our composable architecture lets enterprises run compute inside their own cloud data warehouse or within the CDP itself for real-time use cases. Zero-copy capabilities let AI agents and models operate on data wherever it resides, without requiring a full migration before anything gets activated. For use cases where real-time is needed, our enterprise-grade Intelligent CDP gives brands the flexibility to

Agents work inside the flow, not around it. The AI Agent Foundry and Treasure AI Studio put purpose-built agents to work on data onboarding, audience creation, and journey design. All this is done directly inside the workflows marketers and data analysts already use, alongside the humans setting strategy, not replacing them.

Orchestration runs in the moment, not the next batch. We link live events, streaming segments, and journey logic directly to the shared customer profile, so eligibility, suppression, content, and next-best-action update the instant a customer's behavior changes.

Where we believe the IDC MarketScape says Treasure AI still have work to do

We'd rather tell you this ourselves than have you find it in the fine print. The IDC MarketScape's evaluation was fair, and it flagged three things worth being honest about.

To Treasure AI, he depth of our data model configuration can still be a learning curve for advanced use cases, even with the natural-language interfaces and AI-native Audience Studio we've already shipped. But we believe we’re closing that gap with Treasure AI Studio and our new Treasure AI Suites.

We believe closed-loop campaign optimization, the kind that corrects itself mid-flight without a human re-triggering it, is a work in progress until we believe it’s reliable and trustworthy. And while we also believe our identity resolution is competitive, the visual tooling to inspect exactly how two records got merged still needs to be clearer for both business and technical users.

None of that is a surprise to us internally. We'd rather build in the open than pretend the gaps don't exist.

Why we believe you should care about this evaluation

How Treasure AI can help your team:

• AI agent–based workflow automation
• The IDC MarketScape noted: “Organizations that want AI applied to onboarding, audience creation, analysis, and campaign workflows while maintaining governance and human oversight should consider Treasure AI.”
• Built for the Enterprise
• The report also noted that “Treasure AI is most relevant to large enterprises, especially those operating across multiple brands, regions, and lines of business in retail, CPG, automotive, and media/entertainment verticals.”
• “Treasure AI is relevant when a B2C enterprise needs a CDP to function as shared customer intelligence across multiple brands, regions, channels, and teams.”
• Hybrid Deployment Model
• The IDC MarketScape goes on to state that, “It is also relevant when buyers are assessing how a CDP would fit alongside existing warehouse, engagement, and activation investments, especially in environments where deployment preferences and the division of responsibilities between data and marketing teams are still evolving.”

We believe with the introduction of Treasure AI Studio and our Treasure AI Suites, we also can help mid-size organizations finally use the data they already have, with AI tooling built into the core of every workflow so that acting on that data happens in real time.

The thing that hasn't changed

Most platforms in this category were built to store data well. We believe they’re sitting on a wealth of customer data that lives in ten different systems, none of which talk to each other, which means every campaign is a guess and every media dollar is partially wasted.

We built ours to activate it on behalf of a human being, in the moment that behavior actually happens, in a way that still feels like the brand knows the customer rather than just logged them.

Being named a Leader by IDC MarketScape doesn't change that goal. In Treasure AI’s opinion, it's confirmation, from outside our own walls, that the goal was the right one to build toward.

Supporting Materials

• Learn more at treasure.ai.
• Treasure AI Named a Strong Performer in Customer Analytics Technologies Evaluation
• Learn more about the evolution of Treasure Data to Treasure AI from Kaz Ohta, CEO and co-founder.
• Delivering 10x Value to Marketers in 10 Minutes with Its Agentic Experience Platform
• Treasure Data Unveils Treasure Code, Bringing Agentic AI to Customer Data Operations
• On Demand Webinar: AI, Data, and the Future of Customer Engagement

*IDC MarketScape vendor analysis model is designed to provide an overview of the competitive fitness of technology and suppliers in a given market. The research methodology utilizes a rigorous scoring methodology based on both qualitative and quantitative criteria that results in a single graphical illustration of each supplier’s position within a given market. The Capabilities score measures supplier product, go-to-market and business execution in the short-term. The Strategy score measures alignment of supplier strategies with customer requirements in a 3-5-year timeframe. Supplier market share is represented by the size of the icons.

¹ IDC MarketScape: Worldwide AI-Enabled Customer Data Platforms for B2C Users 2026 Vendor Assessment (Doc #US53952526, June 2026)