mycelo.dev — context graph infrastructure

Relevant information
about anything,
instantly.

Every AI system has the same unsolved problem: access to what actually matters, right now, without scanning everything. Mycelo is the infrastructure that solves it — a context graph that traverses to truth in milliseconds.

Without MyceloWith Mycelo
Vector Search"auth-service documentation chunk #4..." "...authentication system overview..." "...login service readme..."← similar text. not connected facts.
Graph Traversalauth-service→ owned by Alice→ depends on user-db, redis→ broke 3× this month→ changed by PR #442 (Bob)→ impacts 12,000 users
ResultAI gets similar documents.
Guesses at connections.
Hallucinates relationships.
ResultAI gets connected truth.
Zero scanning. Zero guessing.
Follows pointers directly.
01
Relevant

Not similar. Not nearby. The specific connected facts that matter for this exact question — and nothing else. Graph traversal returns only what's on the path.

02
Anything

Any entity. Any domain. No predefined schema, no ontology design, no human labeling. Send us your data — we automatically extract entities, relationships, and context.

03
Instantly

Index-free adjacency means each node holds direct pointers to its neighbors. No scanning. No joining. 10 hops = 10 pointer follows. Speed doesn't degrade as data grows.

The Gap

Every existing system fails
on at least one of the three.

Databases are fast but rigid. Vector search handles anything but returns similarity not truth. Manual knowledge graphs are relevant but require months of schema design. Nothing hits all three.

SQL Database
✓Fast
—Not relevant — returns rows not context
—Not anything — rigid schema required
Vector / RAG
✓Anything — handles unstructured data
—Not relevant — similar ≠ connected
—Not instant — scans all vectors
Manual Graph
✓Relevant — relationships first-class
✓Instant — index-free adjacency
—Not anything — months of setup
Mycelo
✓Relevant — connected truth
✓Anything — auto-extraction
✓Instant — traversal not scan

How it works

The graph doesn't search.
It walks.

Every node stores direct physical pointers to its neighbors. To find a connection, Mycelo follows the pointer. One operation per hop. Regardless of how many billions of nodes exist.

Vector / RAG — scans everything

-- "What caused the outage?"-- Step 1: embed the questionembed("What caused the outage?")-- Step 2: scan ALL vectorsSCAN 2,847,291 vectors...-- Returns: similar text chunks-- Hope the connection is in one chunk.-- Often it spans multiple docs.
Returns: text that mentions outages. Not what caused this one.

Mycelo — follows pointers directly

-- "What caused the outage?"-- Step 1: find the alert nodeMATCH (a:Alert {active: true})-- Step 2: follow CAUSED_BY pointer -[:CAUSED_BY]->(change:Change)-- Step 3: follow AUTHORED_BY pointer -[:AUTHORED_BY]->(eng:Engineer)-- 3 pointer follows. Zero scanning.RETURN a, change, eng
Returns: Bob's PR #891, changed pool settings 3hrs ago. auth-service, payments, profile all impacted.

Use Cases

The same problem across
every industry.

01
Engineering

Incident resolution in seconds, not hours

Production breaks at 2am. Instead of scanning logs and pinging people, your AI traverses the graph: alert → service → recent change → author → last incident → fix. Root cause in one query.
02
AI Agents

Agents that actually remember your world

LLM agents forget everything between sessions. Mycelo gives them a persistent, structured memory — not a text dump, but a living graph of entities and relationships that grows smarter over time. Agents that know your system as well as your best engineer.
03
Developer Tools

Impact analysis before you ship

Before changing UserSchema, your IDE asks Mycelo what depends on it. The graph returns every service, serializer, test, and external API that touches it. Silent production breaks become caught-before-commit warnings.
04
Enterprise

Org knowledge that doesn't leave when people do

When your best engineer leaves, they take years of context with them. Mycelo continuously captures decisions, relationships, and institutional knowledge into a graph. The knowledge stays even when people move on.

The API

Two endpoints.
Infinite context.

Ingest anything. Query everything. The entire product surface is two API calls. We handle the graph, the extraction, the embeddings, and the traversal.

POST/ingestSend any data, any source
POST/contextQuery → get connected subgraph
GET/graphVisualize your knowledge graph
GET/impact/{entity}What breaks if this changes?
// 1. Ingest from any source await mycelo.ingest(({ tenant: "acme", source: "github", data: commits }); // 2. Ask anything in natural language const ctx = await mycelo.context(({ query: "What caused the outage?" }); // 3. ctx.subgraph → feed any AI tool // Copilot, Claude, Cursor, LangChain. // Zero lock-in.

Pricing

Start free. Scale without surprises.

Seed

$0

Free forever

  • 1 tenant · 1 graph
  • 100K nodes
  • 10K context queries/mo
  • 5 connectors
  • Community support

Growth

$149

per month

  • 10 tenants
  • 10M nodes per tenant
  • 500K context queries/mo
  • All 50+ connectors
  • Full temporal history
  • Priority support + SLA

Forest

Custom

volume pricing

  • Unlimited tenants
  • Dedicated instances
  • Custom ontologies
  • On-prem / VPC
  • 99.99% SLA
  • Dedicated engineer

Early Access

Your AI deserves
connected truth.

First 500 teams get 6 months of Growth, free. No credit card.