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Show HN: Ktx – Open-source executable context layer for data agents

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Why This Matters

Ktx introduces an open-source, self-improving context layer that enhances data agents' ability to query data warehouses accurately by automatically learning from company knowledge and organizing data relationships. This innovation reduces manual upkeep and improves query precision, streamlining data operations for organizations. Its integration of semantic understanding and automated mapping offers significant efficiency gains for the tech industry and data consumers alike.

Key Takeaways

The context layer for data agents

Quickstart · CLI Reference · Agent Setup · Slack

ktx is a self-improving context layer that teaches agents how to query your warehouse accurately - from approved metric definitions, joinable columns, and business knowledge it builds and maintains for you.

Note Run ktx with your own LLM API keys or a Claude Pro/Max subscription. No extra usage billing from ktx.

Why ktx

General-purpose agents struggle on data tasks. They re-explore your warehouse on every question, invent their own metric logic, and return numbers that don't match approved definitions.

Traditional semantic layers don't fix this. They demand constant manual upkeep and don't absorb the rest of your company's knowledge.

ktx does both, automatically:

Learns from company knowledge. Ingests wiki content, organizes it, removes duplicates, and flags contradictions for human review.

Ingests wiki content, organizes it, removes duplicates, and flags contradictions for human review. Maps the data stack. Samples tables, captures metadata and usage patterns, detects joinable columns, and annotates sources so agents write better queries.

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