What is EKOS?

EKOS is a compiler for enterprise knowledge: it turns source code, databases, documents and binaries into a traceable knowledge layer AI agents can query.

EKOS compiles enterprise systems into structured, evidence-backed knowledge that AI agents query through the Model Context Protocol (MCP).

It observes the systems you already have — source code, Git history, SQL schemas, GitHub issues, Confluence, PDFs, Pentaho jobs, compiled .NET and JVM binaries — and runs them through deterministic compiler passes. The result is a Canonical Knowledge Model stored in an append-only ledger. Every object, relationship and conclusion in that ledger points back to the evidence it was derived from.

What you get

• A knowledge layer, not a search index. Tables, services, functions, pipelines, people and documents become typed objects with typed relationships (DependsOn, Calls, ForeignKey, Extends, …).
• Answers with receipts. Every conclusion carries evidence and provenance: file, line span, the analyzer that produced it, and the pipeline run that wrote it.
• History. The ledger is append-only, so you can ask what was true at any past time (ekos_state with at, ekos diff, EKL AS OF).
• Cheap repeated questions. Compile once, query many times. On a 2,022-file open-source repository, answering real questions from the ledger used 67–93% fewer tokens than grep-based search over the source.
• No cloud dependency. EKOS is a single Rust binary. The compiler passes need no LLM; LLM use is opt-in and limited to specific, labelled steps.

Where to go next

• New here? Read The Problem, then run the Quickstart.
• Want the vocabulary? Core Concepts.
• Want the internals? System Overview.