Building Enterprise AI Agents on Databricks? You Need Alation's Context Layer

The context problem with enterprise AI agents

Databricks Agent Bricks gives you the power to build sophisticated AI agents. But here's the challenge every enterprise faces: agents are only as good as the context they receive.

When agents lack context, they hallucinate. They choose deprecated datasets. They misinterpret business terms. They generate answers that sound right but are disconnected from how your organization actually defines, governs, and uses data. It’s the difference between an answer you can trust, explain, and investigate—and one you can’t. And the goal here is (of course) to ensure you can give your agents as much agency as possible.

We've seen this firsthand with customers. Enterprise AI models and agents that lack metadata context produce outputs that are often unreliable, opaque, and hard to trust. But when those same agents access governed metadata from Alation? They operate with a shared understanding of your business. And that's not a small improvement. It's the difference between an agent that hallucinates and one that delivers explainable, trustworthy answers you can actually investigate and act on.

What makes the difference: The Agentic Knowledge Layer

The answer isn't more compute or larger models. It's context. Specifically, it's the metadata and business knowledge that tells your agents:

• What datasets actually mean in your business

• Which sources are certified vs. deprecated

• Who owns what and how it's being used

• What policies govern access and usage

• How data flows through your systems

This is where Alation comes in. As the Agentic Data Intelligence Platform, Alation curates exactly this context through its Agentic Knowledge Layer. We're talking business glossaries, data lineage, quality signals, ownership, policies, and usage patterns, all governed where your data stewards and owners already work.

Now, with Alation's MCP integration in the Databricks Marketplace, Agent Bricks can access this trusted context directly.

How Databricks and Alation work together

Databricks has introduced a unified MCP (Model Context Protocol) ecosystem that removes traditional barriers to enterprise AI agents:

• Databricks Marketplace offers curated MCP servers for discovery and installation (Public Preview)

• Agent Bricks with Multi-Agent Supervisor orchestrates agent actions with these tools

• The MCP framework enables seamless integration with enterprise context providers

Alation plugs into this ecosystem as your metadata and governance layer, providing the business context and data intelligence that makes AI agents actually useful in enterprise settings.

Here's how the workflow looks:

1. Discover and install: Find Alation in the Databricks Marketplace and connect it with just a few clicks. The MCP Servers tab lets admins manage access and tokens centrally.

2. Connect your context: Link Agent Bricks to Alation's rich metadata repository, where all your business definitions, data lineage, and governance policies already live.

3. Build with confidence: Your agents can now query Alation for context before generating answers or taking actions. They'll fetch business definitions, check policies, validate data quality, and trace lineage, ensuring every response is grounded in your organization's governed knowledge.

The beauty of this integration? Alation extends and complements Unity Catalog's governance capabilities across your entire data ecosystem—not just Databricks—while leveraging Databricks for the data, compute, and AI orchestration layer. Each platform does what it does best. The best part? There’s no need to rebuild your governance framework all over again. 

What you can build with Alation + Agent Bricks

Knowledge assistants that cite the truth: Build agents that pull business definitions and certified metrics from Alation before responding to queries. Every answer includes lineage and data quality signals, so users know exactly why the agent chose that data and can trust the result.

Policy-aware automation: Before an agent executes an action, it checks ownership, usage norms, and access policies from Alation. This prevents compliance violations and misuse while keeping automation running smoothly.

Context-rich analytics copilots: Multi-Agent Supervisor workflows combine Databricks capabilities with Alation's governed context (like glossaries, certifications, and deprecation status). Your agents automatically choose the right data sources and avoid risky ones without manual intervention.

What makes Alation different

Trust at the source: Agents inherit context that's already curated and governed by your data stewards. Nothing scraped from unverified sources or reverse-engineered from schemas.

Explainability by design: Lineage, certifications, and policy references travel with every answer. Teams can always trace why an agent chose a particular dataset or metric.

Open and agent-agnostic: Whether you're using Agent Bricks, building custom agents, or mixing vendor solutions, Alation's Agentic Knowledge Layer grounds them all in the same organizational truth.

Built for the leap from pilot to production: Many organizations can prototype agents—but few can scale them. By grounding every agent in trusted, governed data, Alation turns promising proofs of concept into production-grade intelligence.

And now, with our expanding ecosystem of partners, organizations can extend that same trust beyond their walls—connecting Alation’s governed context to the broader world of enterprise AI.

Join a growing ecosystem

The Databricks MCP Marketplace is launching with an impressive ecosystem of partners, including You.com, Glean, S&P Global, FactSet, Dun & Bradstreet, and Moody's. All are focused on delivering governed, high-quality context to enterprise AI.

Alation brings the critical internal context layer: the metadata and business knowledge that makes external data meaningful within your organization.

Get started today

In Databricks: Visit Marketplace → MCP servers, enable access via the MCP Servers tab in Agents, then configure Agent Bricks to call your Alation MCP integration.

In Alation: Make sure your glossaries, lineage, and policy objects are current so agents inherit the best possible context from day one.

Want a guided walkthrough? Reach out to your Alation account team for early access details and implementation support.

The bottom line: If you're building enterprise AI agents on Databricks, you need more than powerful infrastructure. You need trusted context. Alation delivers that context, grounding every agent in your organization's definitions, policies, and lineage so answers are explainable, governed, and built on your truth.