Intelligence Connected
Neural Fabric. The memory layer for every AI you use.
How it works
01
Write once. Recall anywhere.
Write from any MCP-connected LLM. Ask from any other. It's there, with the date, the confidence, and the source. That's the Neural Fabric.
// Write a decision
fabric_note({
notes: ["Chose Teller over Plaid, simpler API surface,
better webhook reliability."],
category: "decision"
})
// → ✓ Persisted to Neural Fabric · confidence: 0.97
// Recall from any connected LLM
fabric_query({ query: "Why did we pick Teller?" })
// → Teller was chosen over Plaid for its simpler API
surface and better webhook reliability.
// source: decision · Feb 14, 2026 · confidence 0.97
Neural Fabric
LLM Agent
-
✓ saved to Neural Fabric
AI Agent
-
✓ saved to Neural Fabric
Document
-
✓ saved to Neural Fabric
Any Agent · Later
"What do we know about this project?"
Synthesised answer · 3 sources
confidence 1.0 · 812ms
LLM
Agent
Agent
Client wants the dashboard delivered by end of March.
AI
Agent
Agent
Budget approved. Team aligned on delivery scope.
Document
Spec doc, 5 requirements connected to this project
02
What makes it different.
Zero API cost
At ingestion
No call to any embedding provider to encode your documents. 250× faster than dense embeddings. Files never leave your environment to get vectorized.
Multi-hop
Graph traversal
Answers emerge from connections across your entire knowledge graph, not from a single matching chunk. Follows chains of related entities standard retrieval can't see.
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.
03
19 tools. Every layer.
Search & Query
fabric_search
Search entities and notes
fabric_query
Grounded answers with context
fabric_graph
Graph JSON views
Write & Knowledge
fabric_note
Session notes and findings
fabric_assert
Durable facts and decisions
fabric_thread
Threaded context
fabric_task
Tasks and work items
fabric_ingest
Documents into graph entities
Entities & Relationships
fabric_entities
List entities by type
fabric_entity_detail
Inspect entity metadata
fabric_relationships
Stored relationships
fabric_relations
Relationship records
fabric_relate
Create relationships
fabric_promote
Promote couplings
fabric_reject_coupling
Reject couplings
Govern & Operate
fabric_provenance
Entity provenance records
fabric_status
Counts and index status
fabric_health
Service and pipeline health
fabric_rebuild_index
Rebuild derived indexes
Same tools in Claude.ai, ChatGPT, Cursor, OpenClaw, or any MCP-compatible agent.
How the kernel works →04
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 |
5,188
entities / sec
Ingestion throughput. Zero external API calls. 250× faster than dense embeddings.
120B
per entity
Linear memory scaling. Validated accurate to within 1.7% of formula at 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.
Early Access
Pricing
Predictable pricing that scales as you grow.
| Feature |
Free 14-Day Trial
|
Starter
|
Most popular
Scale
|
Pro
|
Enterprise
|
|---|---|---|---|---|---|
| Price | $0 | $49/mo | $149/mo | $399/mo | Custom |
| Entity storage | 1K | 5K | 20K | 50K | Unlimited |
| Queries / mo | 1K | 10K | 50K | 200K | Unlimited |
| Documents included | — | 1K (1GB) | 3K (3GB) | 15K (15GB) | Unlimited |
| Knowledge graph + visualization | ✓ | ✓ | ✓ | ✓ | ✓ |
| Entity + relationship graph | ✓ | ✓ | ✓ | ✓ | ✓ |
| Natural-language graph query | ✓ | ✓ | ✓ | ✓ | ✓ |
| Governed writes | ✓ | ✓ | ✓ | ✓ | ✓ |
| Provenance planes | ✓ | ✓ | ✓ | ✓ | ✓ |
| MCP tools | 18 | 19 | 19 | 19 | 19 + custom |
| SSO / audit logs | — | — | — | Add-on | Included |
| Support | Community | Priority | SLA / dedicated | ||
| Get started | Contact us |