Informatica Headless + Oracle Select AI: Enterprise-Wide Business Context for Oracle Database Customers
Table Of Contents
Table Of Contents
Informatica Headless can now provide Oracle Select AI with a rich understanding of customers’ business semantics — enabling accurate and trusted results with AI-ready data.
AI adoption is accelerating rapidly, but behind the scenes, data leaders are hitting a hard reality: 76% of organizations report that data governance is falling behind AI adoption, and 50% cite reliable data as the single greatest barrier to scaling agentic AI, according to Informatica’s 2026 CDO Insights report. While enterprises are eager to deploy autonomous agents, these systems are only as smart and safe as the data context feeding them.
As a consistently recognized leader in database technology, Oracle AI Database is trusted by over 90% of the world’s largest enterprises for mission-critical workloads. With Oracle Database 26ai, Oracle embeds advanced AI capabilities directly where enterprise data lives. At the center of this movement is Oracle Select AI. Select AI is built directly into Oracle Autonomous AI Database and allows teams to query complex enterprise data using plain language, leveraging the specified AI model to perform reasoning and execution orchestrated by the database. But for AI to make more dependable, real-time decisions, it needs to be grounded with clear, standardized business definitions, not raw, ungoverned tables.
Informatica is a strategic partner for enterprise cloud data integration, data governance, and master data management (MDM) for data warehouse and lakehouse solutions on Oracle Cloud Infrastructure (OCI). To help bridge this AI trust gap, Informatica is proud to announce the expansion of our Oracle capabilities by making Informatica’s Headless Data Management Catalog Discovery MCP available as a trusted semantic source directly within Oracle Select AI. Both organizations will be showcasing the innovation live at Oracle AI World in Las Vegas (Oct 26–28).
Unlike point solutions that merely pass along localized business definitions, Informatica provides deep, enterprise-wide semantics and context from a single catalog to feed rich, unified metadata directly into Oracle Select AI. Bringing this governed catalog context into your AI profiles unlocks multiple key advantages:
- Consistent answers. The same term resolves to the same result for every user and agent, with less variation.
- Faster path to trusted AI. Less manual prompt and schema engineering to get usable results.
- Governance that keeps pace with AI. Closes the data gap highlighted in our recent CDO Insights report.
- Transparency. Teams can inspect the context and SQL behind an answer, so results can be validated and audited, enabling “human in the loop” oversight
- Lower risk. Less ambiguity, no more guesswork. Agents work from approved definitions and compliance tags.
This integration bridges the gap between database capability and business meaning across your entire organization.
How It Works
Informatica Data Catalog now connects to Oracle Select AI as a semantic source. Here's how it works:
- Governed definitions stay in the catalog. Data stewards keep ownership of business terms, measures, and asset description within Cloud Data Governance and Catalog (CDGC)
- Select AI pulls that context at prompt time. It combines the catalog context and glossary definitions with database metadata, so the LLM knows both what the data is called and what it means.
- Customers stay in control. Choosing which catalog context applies to which AI profile.
Take a column like SUPPORT_STATUS. On its own, it doesn't explain what an "at-risk customer" is. The catalog does, so a request like "List at-risk customers by region" uses the definition your organization approved.
Chief Data Officers and data leaders can scale AI with built-in governance, while data stewards can define a term once and reuse it across AI workloads. Business analysts and line-of-business users can ask questions in plain language and trust the answers, enabling Oracle Database Admins and AI developers to spend less time translating business meaning into prompts.
Before and After: The Difference Governed Context Makes
Consider this prompt:
"List at-risk customers by region."
Without catalog context
Select AI sees column names like CUSTOMER_ID, REGION, and SUPPORT_STATUS. It provides table metadata such as the table definition and relies on the LLM to infer what "at-risk" means. The SQL the LLM generates may be valid, but due to LLM non-deterministic behavior, it can return a different query, which may produce different results. As a result, your customer success team reports may differ.
With Informatica Data Catalog as a semantic source
Oracle Select AI also retrieves your approved business definition of "at-risk customer" and the descriptions of the tables and columns involved. The LLM can use this information to generate SQL that reflects your organization's definition, and the same question is much more likely to return the same answer for users and agents.
Teams can use Select AI's built-in actions to see the context and SQL behind each answer. Run the same prompt with and without the catalog source and compare the results. It's the quickest way to see the value.
Getting Started
You don't need to govern everything on day one. Start small:
- Pick one term that causes confusion. Choose a metric or definition where teams regularly disagree, such as "active customer" or "net revenue".
- Make sure it's defined and governed in Informatica. Capture the business term, its owner, and the assets it applies to.
- Connect the catalog to Oracle Select AI. Attach it as a semantic source to your AI profile. Oracle’s [technical blog] guides you through the step-by-step setup.
- Test and validate. Run your prompts with and without the catalog context and compare the SQL and results. Expand. Add more terms, domains, and data sets as confidence grows.
Learn More
Agentic AI delivers value only when it's built on data you can trust. Oracle brings the AI capabilities inside the database. Informatica brings the governed business context that tells the agents what your data means. Together, Informatica and Oracle help joint customers move from AI experiments to production agents they can rely on.
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