Managed Vector Storage for Agent Knowledge
Give AI agents access to organizational knowledge through managed vector storage. Ingest, index, and retrieve documents so agents can ground responses in real data instead of general training.
Agents That Know Your Organization
General-purpose models know a lot, but they do not know your policies, procedures, or operational context. Vector storage lets teams give agents access to organizational knowledge so responses are grounded in real documents instead of generic training data.
The managed vector database handles ingestion, indexing, and retrieval so teams can focus on the knowledge itself rather than infrastructure.
Ingest Knowledge from the Sources You Already Use
Connect documents from Google Drive, internal wikis, policy databases, and other knowledge sources. The platform handles chunking, embedding, and indexing so content is searchable by agents at query time.
Updates to source documents can be re-ingested to keep agent knowledge current without manual intervention.
Contextual Retrieval During Live Interactions
When an agent needs to reference organizational knowledge, the vector database retrieves the most relevant content based on semantic similarity. This grounds agent responses in real data and reduces hallucination.
Retrieval is integrated into the agent runtime so knowledge access happens within the same operational and security boundaries as the rest of the platform.
Ready to Give Your Agents Real Knowledge?
Managed vector storage integrated into the trusted neutral platform.