AIAgentsandCopilots
A unified context plane where structured, unstructured, and vector data live together for reasoning and action.
Fragmented context produces hallucinating agents
AI agents need real-time context to reason and act accurately. In fragmented stacks, context is incomplete, stale, or scattered across vector stores, application databases, and event streams.
One plane for vectors, time-series, documents, and live state
MonkDB provides a single context layer where structured, unstructured, and vector data coexist on live system state. Agents retrieve, reason, and act on the same continuously updated truth.
Production-grade agentic foundations
Hybrid retrieval
Vector similarity, keyword search, and SQL filters in a single statement.
Live memory
Per-agent state and shared session memory backed by the same engine.
Tool execution
Agent actions land in the same plane that holds the context, with full audit trail.
Sovereign by default
Embeddings, prompts, and memory never leave your environment.
Give your agents the live context they need.
Ver cómo MonkDB puede unificar su infraestructura de datos, con cero compromisos en soberanía, rendimiento o escala.
Reserva una demostración