Context Operating System

Your codebase,
always in context_

ContextOS is a semantic search layer for your codebase. Give every developer and AI agent instant recall of what was built, why it was built, and by whom — three API calls away.

10ms Context retrieval
100% Tenant isolated
384 dim vector search
Sources supported

Ingests context from the tools your team already uses

GitHub
Slack
VS Code
Linear
Webhooks
REST API
Jira
Confluence
GitHub
Slack
VS Code
Linear
Webhooks
REST API
Jira
Confluence
The problem

Knowledge evaporates.
Every single day.

Organizations make thousands of decisions, build intricate systems, and develop hard-won expertise — then watch it vanish into closed Slack threads, departed employees, and forgotten docs.

Tribal knowledge

Critical context lives in people's heads. When they leave, it leaves with them — and takes months of productivity with it.

Unsearchable history

Why was this decision made? Why was this code written this way? The answer exists somewhere — but nobody can find it.

AI without memory

AI agents hallucinate because they lack your organization's actual context and history. They're smart but uninformed.

Slow onboarding

New hires spend weeks reconstructing context that should be instantly available. Every hire starts from zero.

Agentic AI acting without real-time organizational context

In the age of autonomous AI, a model that doesn't know your org's decisions, constraints, and history doesn't just make one wrong call — it cascades that error across every downstream agent and system, at machine speed.

The defining challenge of 2026
How it works

The OS layer between
your knowledge and everyone who needs it

ContextOS sits underneath your existing tools and unifies them into a single, queryable context layer.

01

Ingest from anywhere

Push code commits, Slack messages, documents, and decisions via API, webhooks, or direct integration. Every byte of organizational knowledge becomes a context chunk.

GitHub webhooks Slack integration REST API Manual upload
02

Index semantically

Every chunk is embedded into a 384-dimensional vector space. No keyword matching — pure semantic understanding. Ask in plain English, get back exactly the right context.

Vector embeddings Semantic search Tenant isolated
03

Retrieve in milliseconds

Query context with a single API call. Get back ranked, relevant chunks from across your entire organizational history — scored by semantic relevance and freshness.

Sub-10ms search Ranked results Source attribution
04

Deliver to humans and AI

Context flows to developers via IDE integrations, to AI agents via the /before endpoint, and to leadership via the console. The right knowledge reaches the right recipient.

AI agent ready Developer tools Admin console
Use cases

Context for every part
of your organization

AI agents

Ground your agents in organizational reality. They query ContextOS before every task — acting on what your org actually knows.

  • Pre-task context injection
  • Agent memory persistence
  • Conflict detection

Institutional memory

When key people leave, their knowledge stays. ContextOS captures expertise as it's created, building memory that outlasts any individual.

  • Expertise mapping
  • Decision traceability
  • Knowledge continuity

Compliance & audit

Every chunk is timestamped, attributed, and tenant-isolated. Full audit trail of what your organization knew and when.

  • Immutable audit log
  • Developer attribution
  • Tenant data isolation
Live demo

Your codebase,
answering back in real time.

Semantic search on a sample knowledge base — no account, no API key needed.

Try:
Loading demo…
01 POST /context/ingest

Push any text, code, or document. Returns a chunk ID instantly.

02 POST /context/search

Semantic search in plain English. Ranked results with relevance scores.

03 POST /context/retrieve

Returns a context window ready to inject directly into any LLM prompt.

Full API docs →
Pricing

Start free.
Scale as you grow.

Free
$0/month

For individuals and small teams exploring organizational context.

  • 1 tenant
  • 10,000 context chunks
  • Core ingest + search API
  • Admin console
  • Community support
Get started free
Enterprise
Custom

For organizations that need full control, compliance, and private deployment.

  • Private deployment
  • Unlimited everything
  • Custom integrations
  • SLA guarantee
  • SSO & SAML
  • Dedicated support
  • Audit & compliance
Contact us
FAQ

Common questions

Yes, completely. Every context chunk, embedding, and query is scoped to your tenant ID at the database level. No cross-tenant data leakage is architecturally possible — your vectors are never mixed with another organization's data.

No. ContextOS runs its own self-contained embedding model (BAAI/bge-small-en-v1.5) baked into the backend. There are no third-party AI dependencies or keys required to ingest and search context.

Generate a one-time invite link from the tenant console and send it to your developer. They click the link, enter a label for their key, and receive their API key instantly — no admin involvement needed after that.

A context chunk is any single ingest — a commit message, a Slack thread, a document paragraph, an architecture decision. Each chunk gets embedded as a vector and becomes searchable. Chunks can be up to ~8,000 characters.

Yes. The /context/before endpoint is designed specifically for AI agents — call it before any task and get back ranked ingests, past agent runs, and persistent agent memory all in one response. Any agent framework that can make HTTP calls works.

Yes — that's the Enterprise plan. We deploy ContextOS into your own AWS account or VPC, giving you full data residency control, no external calls, and your own infrastructure. Contact us to discuss requirements.

Your codebase,
always in context.

Free tier is instant — no credit card, no waiting list. Connect your first repo in under 5 minutes.

Includes 1 repo · 500 API calls/day · MCP server for Claude Code & Cursor