Metadata as AI Superpower: Our Vision For Agentic Data Management

When Deepesh Chourey, SVP of Engineering at Alation, took the stage at revAlation Chicago, he opened with a confession: "Our job is to generate outcomes, instead of releasing product and features."

It’s not about the technology. Alation's platform has been collecting metadata, powering catalogs, and enabling governance for years. But something fundamental was missing—the connection between technical capabilities and business outcomes. "I used to think about everything as technical aspirations, technical outcomes," Chourey admitted. "It has fundamentally changed. We now need to be thinking about business superpower. That is what the job of the technologist and technology has to be."

That shift in mindset has defined Alation's last 12 months—a period Chourey called "unprecedented" and "the most ambitious, product-centric year in our history." 

The result? Seven new products, a 91% improvement in engineering resolution SLAs, and a 30% increase in speed to resolution. More importantly, a reimagined platform architecture where AI agents take the first pass at everything—from catalog search to data quality checks to building custom workflows.

But the real story isn't just about what Alation built. It's about why—and how metadata has become the secret weapon for making AI actually work in the enterprise.

Why metadata matters more than ever

Here's the uncomfortable truth about enterprise AI: most organizations are drowning in data but starving for context. Large language models arrive with impressive world knowledge but zero understanding of your business. They don't know that "SLA" at your company means delivery within five days, not same-day. They don't know which datasets are trusted, which joins are valid, or which metrics matter to your CEO.

"Metadata is the key to trusted AI," Chourey emphasized, a theme that analyst firms like Forrester, Gartner, and IDC are now echoing. But Alation has been living this reality with customers for years. The difference now is scale and application.

Alation's platform unifies catalog, governance, quality, and AI applications in one place—capturing business knowledge once and reusing it across chat interfaces, agent builders, and SDKs. Access control and governance aren't bolted on as an afterthought; they're baked into the foundation. And critically, the platform meets customers where they are—no forced migrations, no vendor lock-in.

"We don't ask you to move to our platform," Chourey said. "We meet you where you are."

This year's re-architecture takes that philosophy even further. Agents now power everything—from the chat interface to catalog search to custom automations. And because Alation uses the same agent framework internally that it exposes to customers, there's no black box. "Our AI is your AI," Staff Software Engineer Laurel Orr explained during her live demo.

Data products: The missing link between data teams and business outcomes

One of the most compelling moments came when Chourey reframed what it means to be a data company. "In the last four years, all of us—different organizations, in different verticals, with different problem statements—have become data companies. We may call DTNA [Daimler Trucks North America] an organization that builds trucks, but at the heart of it, they are a data company."

The challenge? Making that data consumable, discoverable, and trusted at scale.

Enter Alation's Data Products Marketplace and Data Products Builder, two products designed to package data in a way that's both technically robust and business-friendly. Think of data products as containers for business knowledge—narrow, highly curated slices of data tied directly to business outcomes.

During her demo, Orr walked through the experience of building a data product for Daimler Truck North America vehicle lifecycle use case—identifying trucks that missed their delivery SLAs so account executives could proactively reach out to customers. Starting from an existing dashboard (what Orr called "a gold mine of information"), the Data Products Builder mined the catalog, analyzed lineage, and auto-generated a first draft of the data product in seconds.

But here's where it gets interesting: everyone knows AI-generated outputs aren't perfect. That’s why the platform includes AI readiness checks—a series of validations to ensure the data product is high-quality enough for agents to consume. These include compliance checks (Does it have an owner? A description?), data quality checks (Are there too many nulls? Are joins valid?), and critically, verified questions.

Verified questions are demonstrations that teach the AI how your business works. In Orr's demo, she asked: "Which vehicles delivered in Q2 missed their delivery SLAs?" The model's first attempt was reasonable but wrong—it flagged any truck delivered after its expected date. But Daimler's SLA is five days, not zero. Orr corrected the model, and it instantly adjusted.

"Every business is kind of a snowflake," Orr explained. "You need to teach AI about this."

These verified questions do triple duty: they help users gain confidence, they're used for continuous evaluation, and they automatically fix mistakes in the data product over time. It's a feedback loop that makes AI smarter with every interaction.

Agent Studio: No-code to full control

Once a data product is published, it becomes fuel for AI agents—and this is where Alation's flexibility shines.

For business users and data admins who want speed and simplicity, there's Agent Studio —a no-code interface for creating custom agents on top of trusted data products. During the demo, Orr showed how she'd built a "Vehicle Lifecycle Analyst" agent tasked with monitoring delivery data and filing ServiceNow tickets when trucks were late. The entire setup (defining the task, selecting data products, configuring tools, and customizing the system prompt) took minutes.

"All you need is a clear mind and a clear definition of outcomes," Chourey said.

But some customers need more control. For developers and AI engineers, Agent SDK (available in Agent Studio) is an alternative to the no-code path—an open-source framework with no lock-in to platforms, LLMs, or proprietary systems. You can use OpenAI, Anthropic, or your own on-prem model. You can write custom tools, hook into external APIs, or deploy agents wherever they're needed.

"Innovation takes lots of different forms," Chourey said. "We understand, and that's why we have Agent SDK."

The SDK uses the same tools and agent framework that power Alation's native experiences—so whether you're building in the UI or in code, you're leveraging the same trusted metadata, governance rules, and context.

Trust at scale: Governance, quality, and evaluation

One of the keynote's quieter but most important themes was trust—both in data and in AI.

Alation's embedded Data Quality capabilities ensure that quality signals appear at the point of consumption, not as a separate workflow. Users don't have to leave their dashboards or chat interfaces to validate data; the trust signals are right there. And because quality checks are integrated into data product readiness, they become a gatekeeper for AI—ensuring agents only consume vetted, reliable data.

But trust doesn't stop at launch. Once agents are deployed, evaluation becomes critical. Orr demonstrated Alation's evaluation page, which continuously monitors agent performance using the verified questions created during data product setup.

"Once they're deployed, you need to be able to continuously monitor and understand behavior," Orr explained. "It's pretty much impossible to understand how your AI is performing without some ability to run a fixed set of evaluations."

This is especially important for debugging systematic failures versus one-off issues—and for maintaining confidence as agents scale across the organization.

Metadata for mission-critical governance: Introducing CDE Manager

If metadata is the foundation for trusted AI, Critical Data Elements (CDEs) are where that trust is proven. At revAlation London, Alation unveiled CDE Manager—a breakthrough capability that agentically governs the data that matters most to your business.

CDE Manager empowers organizations to govern data based on the business outcome they want to achieve, uniting business, risk, and data teams with purpose-built AI agents that translate business policies like “Customer email must be valid and protected” into enforceable technical controls, and then continuously monitors them across your data landscape. No more chasing stewards or reconciling spreadsheets.

With CDE Manager, organizations define what “trusted” means once, and agents do the rest: tracking compliance, verifying data quality, and generating real-time, auditable proof for regulators and executives alike. It’s governance that runs itself, built directly on the metadata fabric already powering your catalog, data products, and AI agents.

As Chourey noted, Alation’s goal isn’t to release more features—it’s to deliver outcomes. CDE Manager does exactly that: turning governance from a manual, reactive process into a living, intelligent system that enforces trust automatically, at scale.

Why it matters

The AI hype cycle is littered with demos that dazzle but don't deliver. What makes Alation's approach different is its foundation: years of aggregated metadata, governance frameworks customers have already built, and a platform designed for trust at scale.

"If you haven't started on that journey of aggregating that metadata, now is the time," Chourey urged. "If you've done that for a long time and have had amazing success with it, now is the time to unlock the potential of it."

The message is clear: metadata isn't just infrastructure. It's the competitive advantage that makes AI agents reliable, data products consumable, and business outcomes measurable.

As enterprises move from experimenting with AI to deploying it at scale, the winners won't be the ones with the fanciest models. They'll be the ones who solved the trust problem first—and that starts with metadata.

Want to see Agent Studio in action? Request a demo or explore the documentation at docs.alation.com.