Everything Your AI Needs Already Exists. It's Just Not Connected.
The problem was never a lack of data. It's that ontology, glossary, lineage, catalog, and policy were never built to talk to each other; so every team, and every AI agent, ends up working from a different version of the truth.
AI Pilots Never Reach Production
Without trusted business context, AI works in demos but struggles to deliver reliable, repeatable results in production.
AI Answers Without Business Context
LLMs understand language, not your business. Without definitions, lineage, policies, and relationships, they confidently generate incorrect answers.
Multiple Versions of the Truth
Different teams define the same business concepts differently, leading to conflicting reports, decisions, and AI outputs.
Analytics Gets Rebuilt Again and Again
Analysts spend more time finding, validating, and recreating existing work than delivering new insights.
How the Enterprise Context Graph Is Built
Every enterprise already has the knowledge needed for trusted AI. OvalEdge agents continuously discover, validate, and connect it from three trusted sources.
What your systems run on
Business logic lives in your systems. OvalEdge agents parse and analyze source code to uncover what's really happening.
Your existing documentation
Agents read and understand your documentation to capture definitions, policies, and knowledge, and file it where it can be found.
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The knowledge no one wrote down
When context is missing or unclear, agents ask the right questions to the right people.
