Most AI tools optimize a single model's context. We asked a different question: what if every AI you connect shared the same business knowledge? That question became the Neural Fabric.
Qorbit is the governed knowledge graph for multi-agent business knowledge. Not a plugin you add to one tool. Not a vector database you query from one model. A shared source of truth that every AI agent you connect can query, write to, and trace.
Today, when you ask Claude something, it knows what it was trained on. Close the window and everything it learned is gone. Open Cursor, ChatGPT, or any other tool and each one starts from zero. They share nothing.
The Neural Fabric changes that at the infrastructure level. Any connected agent calls its eight MCP tools to query, write, or trace knowledge. Every call returns sources, confidence, and a timestamp. Every write is validated before anything lands on the graph. Every write is recorded in a provenance chain. It is the business knowledge layer your AI tools were missing: one graph, one truth, shared by every agent you connect.
A connected agent calls a Fabric tool. The Neural Fabric retrieves what matters, validates before writing, and returns an answer traceable to the exact facts that produced it. Every cycle makes the next one sharper.
Validated on reproducible synthetic corpora at 60,000+ entities with zero steady-state errors. Identity recall 1.0 across 124,000+ verified pairs. No embeddings. No re-ranker.
Layer 1 is model context: the prompt, files, and messages in front of the model right now. It is fast, useful, and temporary. When the window fills or the session ends, it disappears.
Layer 2 is conversation continuity: preferences, summaries, and facts a tool carries from prior chats. It helps one interface feel continuous, but it still belongs to that tool's conversation stream.
Layer 3 is different. The Neural Fabric is a governed graph of entities and mathematically derived relationships. It does not depend on one model, one chat, or one client. Every connected agent can query the same structure, write through the same governance layer, and trace answers back through the same provenance chain.
That is why the third layer matters.
Relationships are derived, not manually maintained. Writes are validated before they persist. Provenance is recorded at the graph level. Models become interchangeable clients of a shared knowledge layer, not the place knowledge has to live.
Because the Neural Fabric is model-agnostic, any MCP-compliant tool connects with nothing but a config file. No SDK. No plugin. No install.
Any MCP-compliant tool connects over stdio or HTTP · Streamable HTTP endpoint on Cloud Run · Bearer token auth · 60 req/min