Compile enterprise intent into governed, deterministic SQL.
Colrows sits between users, AI agents, and your data systems. It resolves business meaning at compile time, proves every join, and runs dialect-perfect SQL inside a policy-shaped subgraph - so what executes is exactly what was authorized.
Start here
Introduction
Why enterprise AI needs a runtime layer below copilots. Read the thesis, the architecture, and what makes Colrows different.
Read the introduction →Quickstart
Sign up, connect a datasource, and compile your first governed query in under ten minutes.
Open quickstart →Core concepts
Compile-then-execute, the semantic graph, join path proof, multi-vector embeddings, and metrics-as-state.
Learn the concepts →System architecture
A technical deep dive into the four computational domains: parsing, semantic resolution, planning, and physical execution.
View architecture →The Colrows runtime
Every request follows the same compile-then-execute pipeline. Ambiguity is resolved at compile time, not at runtime - and policy shapes the plan before any database is touched.
What Colrows does
- Versioned semantic graphEntities, metrics, events, concepts, constraints, policies and personas - modeled as typed nodes with point-in-time reproducibility.
- Compile-time governanceRBAC, ABAC, and row/column-level predicates shape the allowed subgraph. Unauthorized plans are never generated.
- Join path proofEvery multi-entity query is solved as a constrained graph traversal - ambiguous paths fail compilation rather than silently producing wrong numbers.
- Autonomous maintenanceDrift detection, conflict detection, and schema evolution run continuously. The graph keeps itself current as the enterprise changes.
- Multi-vector embeddingsEach concept carries definition, usage, and combined vectors - recall stays accurate as language and context evolve.
- Dialect-perfect SQLOne semantic plan, many backends. Snowflake, Databricks, Postgres, ClickHouse, Trino, Oracle, SQL Server, and more.
Build with Colrows
Consensus
The Consensus semantic layer - entities, metrics-as-state, autonomous agents, drift detection.
Colrows AI
Conversational analytics that grounds every answer in the governed semantic graph.
SQL Editor & Dashboards
Author, version, and share queries; build dashboards on a single source of truth.
Datasources
Connect Snowflake, Databricks, Postgres, ClickHouse, Trino, Oracle, SQL Server and more.
Access Control
Compile-time RBAC + ABAC, fine-grained row/column predicates, and zero-trust data access.
APIs & SDKs
Embed the semantic execution layer in your applications and AI agents over REST or JDBC.
Further reading
- Breaking the 20-year deadlock in data modeling - why traditional semantic layers fail under AI load.
- The rise of autonomous semantic systems - what self-maintaining semantics look like in practice.
- Multi-hop query understanding - how Colrows resolves intent across multiple hops without hallucination.
- Semantics for enterprise AI agents - building agents on a shared, governed business context.
- From metric stores to knowledge machines - why metrics belong in a graph, not a YAML file.
- The death of manual documentation - autonomous curation in the semantic layer.