Retrieval that knows what changed five seconds ago.
Your AI should answer from what is true right now, not what was true at the last batch job. TwinGraph gives agents a live, structured knowledge layer they can query in real time so every answer is grounded in the current state of your operations.
Your AI gives confident answers based on yesterday's data. It can't tell the difference between a ticket that was resolved five minutes ago and one that's still on fire. When operational decisions depend on AI, stale retrieval isn't a nuisance, it's a risk. Teams lose trust, escalations spike, and the gap between 'what AI says' and 'what's actually happening' grows with every hour between reindexes.
TwinGraph is a live in-memory graph where nodes are documents, entities, sensors, or events, and edges carry semantics. MQTT and gRPC ingest mutate the graph in real time; state auto-persists. Agents query it directly over gRPC, or through the companion twingraph_mcp_server for MCP-native clients, so every answer is grounded in current state.
A few steps. Real infrastructure.
Model your domain
Declare entities and relationships. Nodes can be anything: docs, users, sensors, tickets.
Stream live events
MQTT, webhooks, or direct gRPC calls mutate the graph as events arrive.
Connect your agents
Query the gRPC API directly, or run the companion twingraph_mcp_server to give MCP-native clients typed access to the graph.
Agents reason on it
LLMs retrieve subgraphs and traverse relationships instead of ranking flat chunks.
- 01
Real-Time Accuracy: Answers reflect what changed five seconds ago, not what was true at the last reindex, reducing AI-driven escalations caused by stale data.
- 02
Relationship-Aware Retrieval: Agents traverse structured connections between entities instead of ranking flat text chunks, so responses carry the full context of how systems, tickets, and events relate.
- 03
Zero Reindexing Overhead: The graph mutates in place as events arrive. No batch jobs, no vector store maintenance, no drift between your AI's knowledge and reality.