Kanwas
Kanwas is a context-first AI workspace that acts as a shared brain for product teams and agents. It combines a spatial canvas, a compounding knowledge graph, and model-agnostic AI agents that learn a team’s rules, workflows, and history. Instead of scattered chats, static docs, and forgotten whiteboards, Kanwas pulls code, tasks, research, conversations, and decisions into one Git-backed space where humans and agents reason over the same context. It targets product managers, founders, and cross-functional product teams that want sharper strategies, PRDs, and roadmaps without losing the human taste that makes those decisions distinct.
Make a decision about Kanwas
- Already use it? Add Kanwas to Stack Autopsy — check cost, overlap and safe cancellations.
- Thinking about buying it? Ask AI Advisor — compare fit, alternatives and trade-offs.
- Want to leave it? Find a replacement — see feature losses and migration risks.
Pricing
- Open-source edition: The core Kanwas code is available on GitHub for teams comfortable self hosting, making the software itself effectively $0.00 per month, excluding infrastructure and maintenance costs.
- Hosted workspace (cloud): A managed Kanwas service is accessible through the main website, although specific per-month or per-seat pricing is not clearly published and likely handled through early access or direct contact.
Features
- Context-aware AI agents: Agents read boards, notes, tasks, and connected tools to draft strategies, specs, and research that reflect actual product history.
- Canvas for real work: Code, docs, tickets, embeds, and iframes live together on a spatial board so thinking, discussion, and AI automation happen in one place.
- Compounding context graph: Boards, notes, tasks, and decisions feed a graph that makes future recommendations and drafts progressively better aligned with prior choices.
- Model-agnostic stack: Teams can plug in Claude, GPT, Gemini, and other models while keeping the same workspace, prompts, and workflows.
- Git-backed markdown storage: Every document is a plain .md file with version history, which supports audits, portability, and local editing.
- Real-time collaboration: Multiple teammates and agents can work live on shared boards with fast sharing links and permission controls.
- 1,000+ connections and CLI: Integrations and a CLI bring context in from existing tools, so Kanwas becomes a hub rather than yet another silo.
Use cases
- Product Managers and Product Leads: Centralizing discovery notes, PRDs, decision logs, and metrics while AI agents keep specs and roadmaps current.
- Startup Founders and Leadership Teams: Turning investor feedback, customer calls, and strategy memos into a living context brain for the company.
- Design and UX Research Teams: Connecting research artifacts, insights, and design explorations so AI can surface relevant evidence during key product decisions.
- Engineering and Platform Teams: Linking code, technical constraints, and incident learnings directly to the boards that define product priorities.
- Uncommon Use Cases: Used by fractional product leaders working across multiple companies; adopted by AI agent builders who need a shared canvas and context store for autonomous agents.