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Why EKOS ? What is @ekosproject EKOS is an open-source knowledge infrastructure designed to turn complex technical and operational data into structured, traceable, and reusable knowledge for AI systems. Instead of treating source data, execution history, and agent context as disposable inputs, EKOS preserves where knowledge came from, how it was derived, what evidence supports it, and how it changes over time. EKOS can ingest software repositories, SQL, legacy ETL, Git history, documentation, and other enterprise sources, then compile them into a versioned Canonical Knowledge Model backed by an append-only evidence ledger. On top of that foundation, EKOS provides a read-only MCP layer and a Web Console for exploring the resulting knowledge, provenance, relationships, evidence, and system health. The goal is simple: compile knowledge once, preserve the evidence behind it, and make it reusable across future agents, workflows, and systems. The project is also moving toward letting teams connect their own data and test EKOS with their own agents and workflows, making the knowledge layer useful beyond a single application or session. Products and capabilities currently presented by EKOS include: • EKOS Knowledge Compiler — converts code, SQL, ETL, Git history, and documentation into structured knowledge. • Canonical Knowledge Model — a normalized representation of entities, relationships, dependencies, and technical knowledge. • Evidence-backed Append-only Ledger — preserves provenance, source evidence, versions, and changes instead of silently overwriting history. • Read-only MCP Interface — gives agents controlled access to compiled knowledge through MCP. • EKOS Web Console — visualizes the ledger, knowledge relationships, evidence, health, and project state. • Provenance & Evidence Layer — allows knowledge and relationships to be traced back to their original source and location. • Agent/Workflow Knowledge Layer — provides a foundation for turning execution history, decisions, failures, fixes, and verification results into reusable knowledge. • Own-data Testing — enables teams to connect their own data and evaluate how EKOS can support their agents and workflows. The broader vision is to move enterprise AI from simply retrieving information toward systems that can preserve, verify, and continuously reuse what they learn. EKOS: Compile once. Query forever. Build on verified knowledge. ekos.dev/