Keewano raises $12M seed for database built for AI agents
The database exposes its event records to applications through interfaces including SQL, REST and MCP.
Preserving the context behind events
KeewanoDB keeps raw events for each entity together and adds contextual and semantic layers for machine reasoning. Developers can query these histories for real-time analysis and agent workflows without stitching records back together from separate stores, a design intended to support complex behavioral questions and large-scale queries.
Use of funds
Expand operations and development