Context Data provides a data infrastructure layer for AI agents, offering runtime governance, caching, evaluation intelligence, and distributed tracing.
What it is
Context Data builds infrastructure designed specifically for organizations running AI agents against production data. The platform interposes between agents and underlying data stores to handle caching, governance, safety, and monitoring without requiring code changes to the agents themselves.
Key features
- Onyx: A data-access runtime that sits between agents and databases, files, and APIs to cache queries, redact sensitive information, and hold destructive writes for human approval.
- Cleanroom: Evaluation intelligence that attributes metric movements to specific dataset or pipeline changes and detects benchmark contamination.
- Chronicle: Distributed tracing that records every step, tool call, and model decision during agent runs for debugging and auditing.
- Native protocol support for the Model Context Protocol, Postgres wire protocol, and HTTP.
- Content-aware discovery that indexes documents to let agents find files based on their contents.
Who it's for
Context Data is built for engineering teams, developers, and organizations deploying AI agents in production environments that require security, audit trails, and cost control over data access.
Pricing
All products are open source and available for self-hosting, with managed options offered directly by the team. Check the official website for current pricing details on managed services.
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