For developers building AI agents and RAG applications, Weaviate is an open-source vector database that combines vector and keyword hybrid search, giving agents fast, relevant retrieval over your own data at scale.
Presence & Market Position
Tracked · below panel floor — earned mentions are accruing toward the next scored window.
Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →
Weaviate is positioning itself as the open-source retrieval and memory layer for AI agents, combining vector and keyword search over application data. Its conversation footprint is quieter but technically focused, clustering around managed-cloud availability, the MCP server, and practical retrieval patterns for multimodal data and multi-agent memory. Product communication extends that position through hybrid search, a query agent, and new memory capabilities, while deployments range from self-hosted databases to Weaviate Cloud and managed partner infrastructure. Weaviate is building beyond vector storage toward the data-access and persistence layer agents use to retrieve context and maintain state.
LanceDB
Convex
Qdrant
Neon
PineconeCisco, Intuit, Bosch, HPE, Bumble, Akamai, NetApp, Deel, FactSet, Scribd
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Business Profile
Founded in 2019, Weaviate is an independent, 104-person infrastructure company that has raised $67.7 million. It reported $12.3 million in 2024 ARR and a $200 million valuation in October 2025. The business pairs an open-source database with a managed-cloud motion, using developer adoption to seed paid infrastructure and enterprise deployments. Recent expansion through a free Weaviate Cloud tier and managed availability through infrastructure partners widens access while preserving the core model: open software underneath, with hosted operations and support around it.
Agent Readiness
Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
Weaviate exposes agent-ready access through REST, GraphQL, and gRPC APIs, official client SDKs, and an MCP server that runs alongside the database API. The MCP layer can inspect schemas, run vector or hybrid searches, and modify objects when write access is enabled, with existing authentication and authorization controls governing each action. That gives agents a direct path to retrieval, memory, and governed data operations.
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