Local-first AI for private work.
A map, a boundary, and a memory.
Mission Canvas is a local-first reasoning system for sensitive work.
You ask a question. It classifies the problem, retrieves the right local context, applies the right governance rules, and records the path it took.
Private workflows can stay on your machine. When external research or cloud models are enabled, Mission Canvas routes through explicit gates: sensitive patterns are sanitized or blocked before anything leaves, and external responses are checked before they return.
The result is not just a chat answer. It's a local decision trail: what was asked, what context was used, what boundary applied, and what changed.
Run Mission Canvas locally with Ollama. Your questions are classified, routed, and answered on your machine. The system records a local decision trail so your work compounds over time.
Perfect for students, researchers, independent professionals, or anyone working where privacy is non-negotiable.
Install in 60 seconds →Add the governance bundle as a system prompt. Your AI tool gets a problem map, routing rules, privacy instructions, and a decision-trail format. It adds structure, routing, and audit trails to what you already pay for.
Works with: Claude, Cursor, Codex, Gemini CLI, Kiro, or any AI tool that accepts a system prompt.
Download the Governance Bundle →Connect your own providers: Ollama for local inference, or add one API key through OpenRouter for access to 400+ models including Claude, GPT, Gemini, and Llama.
Governed execution loop · 312-node ontology · 31 domains · 556 health checks · 1169 tests · Apache 2.0
Get Started →Mission Canvas becomes a governed AI operating layer around your domain knowledge, terminology, workflows, and compliance rules. Expand only after the first workflow works.
Contact →Local-first by design. Private workflows can run on your machine with local models. No cloud required for the core system.
Governed before reasoning. Mission Canvas classifies the problem and applies boundaries before building context. This is not a post-reasoning filter — it's a gate on what the model sees.
External research is controlled. When web research is enabled, sensitive context is sanitized or blocked before it leaves. External responses are checked before they return.
Decisions are traceable. Every query creates a local path record: classification, context, route, boundary, and result. Not a chat log — a decision trail.
Everything you type on this page runs as public origin: no profile, no memory, forgotten when you close the tab. By architecture — not by policy.
Install locally and Mission Canvas starts to learn how you work — on your terms. It builds an operator lens: a small, evidence-backed picture of your patterns, stored as a plain file on your machine. The model can propose an update; only a deterministic validator can write one. You hold the pen.
The longer you use it, the better it gets — and it's always yours to take, edit, or delete.
Pick your platform. The setup wizard handles everything — including local model installation.
Open http://localhost:7891 → the onboarding wizard walks you through connecting a local model and running your first governed query.
Mission Canvas gives local AI a map, a boundary, and a memory.
Open source · Apache 2.0 · GitHub