The knowledge graph that builds itself.

Every AI you use. One graph. Connections derived from your data. No ontology. No embeddings. No manual wiring. Eight MCP tools.

OpenClaw. Eight tools. Any agent. The graph derives itself.

Watch knowledge organize itself.

Qorbit creates the connections no one had to define.

Search entities

Find by name, ID, or type...

⊕ Add Document

Entities: 72

Entity Types (16)All None

What makes it different.

Zero embedding cost

At ingestion

No external embedding provider. No per-ingestion API call to encode your data. Frequency-native encoding runs 250× faster than dense embeddings.

Self-healing graph

Zero administration

Add an entity. Every connection appears. Delete it. Every connection vanishes. Re-add it. They return correctly. No stored relationships to maintain. No stale edges. No orphaned links.

Every edge explains itself

Per-feature forensics

Click any connection and see exactly which properties caused it. Shared customer ID. Matching PO number. Overlapping reference. No other system decomposes why two entities are connected.

Governed refusal

Anti-hallucination

When the evidence isn't there, the Neural Fabric returns "No information available", not a guess. Gets quieter, not wronger. Every answer traces to its source.

Cryptographic audit trail

Hash-linked provenance

Every entity carries a SHA-256 provenance chain: actor, timestamp, operation, and graph state at write time. Tampered entries are detected on read. Built for regulated industries where "trust me" isn't compliance.

Bring your own LLM

Your keys, your provider

Document extraction runs on your Anthropic, OpenAI, or compatible API key, encrypted at rest with AES-256. You control the model, the cost, and the data flow. Qorbit never stores or proxies your LLM credentials.

Eight tools. Every agent.

Connect any MCP-compatible AI tool: Claude, ChatGPT, Cursor, Claude Code. Access your entire knowledge graph through eight governed tools. No SDK. No integration code. Minutes, not months.

fabric_add

Add entities and documents. Upload a PDF. The graph extracts entities, discovers connections, and governs every write.

fabric_edit

Make partial, targeted modifications to existing entities. Change one field or many — the graph re-derives connections and governs every write.

fabric_search

Search by name, type, or natural language. Band-code narrowing reduces thousands of entities to a ranked shortlist in milliseconds.

fabric_list

List and filter entities across your graph. Get counts, types, and metadata without loading the full graph.

fabric_graph

Explore entity neighborhoods and resonance subgraphs. See how entities connect through shared frequency signatures.

fabric_read_source

Read source document content from stored files. Pull the original text behind any entity without leaving your agent.

fabric_delete

Remove entities cleanly. Tombstone semantics: connections derived from the deleted entity vanish automatically.

fabric_provenance

Inspect the cryptographic audit trail. Hash-linked entries with actor, timestamp, and tamper detection on every read.

Same eight tools in Claude, ChatGPT, Cursor, Claude Code, or any MCP-compatible agent.

How the kernel works →

Validated at scale.

10-hop graph traversal passing at every scale tested, from 211 entities to 5 million. The Neural Fabric scales linearly at ~120 bytes per entity. Spectral radius held below 1.0 at every point.

Scale ValidationAll milestones passed

Entities	Retrieval time	Memory	Max hops	Status
1,000	6.5ms	121KB	10	PASS
10,000	48ms	1.2MB	10	PASS
100,000	363ms	11.8MB	10	PASS
1,000,000	5.3s	118MB	10	PASS
5,000,000	1.9min	591MB	10	PASS

Graph traversal kernel only. Full API retrieval includes storage, indexing, and network.

5,188

entities / sec

Encoding throughput. Zero embedding API calls. Frequency-native encoding, not dense vector computation.

120B

per entity

In-memory propagation footprint. Linear scaling validated to 5M entities.

1,097×

vs dense at 10K

Sparse vs dense speedup. Dense matrix at 10K requires 800MB. Sparse requires 1.2MB.

0.998

spectral radius

Measured on real-world corpus. Constrained below 1.0 at every write. The Neural Fabric cannot drift.

Validated to 5 million entities. 99.8% candidate reduction at every scale. Multi-hop traversal verified at 10+ hops. Linear O(n) scaling confirmed.

Pricing

Predictable pricing that scales as you grow.

Feature	Free 14-Day Trial	Pro	Most popular Growth	Business	Enterprise
Price	$0	$99/mo	$249/mo	$499/mo	From $2,500/mo
Entity storage	1K	25K	75K	200K	Custom
Queries / mo	50K	500K	1M	2M	Custom
Bundled storage	500 MB	10 GB	25 GB	50 GB	Custom
Knowledge graph + visualization	✓	✓	✓	✓	✓
Entity + relationship graph	✓	✓	✓	✓	✓
Natural-language graph query	✓	✓	✓	✓	✓
Governed writes	✓	✓	✓	✓	✓
Provenance planes	✓	✓	✓	✓	✓
MCP tools	8	8	8	8	8 + custom
Edge forensics	✓	✓	✓	✓	✓
SSO / audit logs	—	—	Add-on	Add-on	Included
Support	Community	Email	Email	Priority	SLA / dedicated
Get started					Contact us

Predictable platform pricing.

Your subscription covers storage, queries, graph construction, provenance, and all eight MCP tools. No embedding API calls. No per-query metering surprises. No infrastructure fees.

Document extraction uses your own LLM API key at your provider's standard rates. You choose the provider: Anthropic, OpenAI, or any compatible endpoint. You see the cost on their bill. You switch anytime.