KanwasTurn scattered team knowledge into shared intelligence that humans and AI can actually use

Kanwas

Kanwas is your team's shared context brain—a collaborative workspace where product teams and AI agents create, edit, and compound knowledge together. Stop fragmenting insights across Claude chats, local folders, Obsidian, VS Code, and scattered docs. Everything lives in one place that gets smarter with every decision you make.

Product Highlights

• Shared Context Canvas: Work with teammates and AI agents over the same spatial board where evidence, ideas, and trade-offs stay transparent to everyone
• Compounding Knowledge Base: Every PRD, decision, and outcome automatically builds on what came before—no more starting from scratch
• Sharp Deliverables: Generate structured, execution-ready outputs like stakeholder updates and product requirements in minutes, not hours
• Agent with Your Rules: Configure Kanwas with your workflows, skills, and instructions so it works your way, not generically
• No Lock-In: Every document is a plain .md file with Git-backed version history—your files stay yours
• Terminal-Grade Power, No Terminal: Powerful agentic capabilities without forcing your team into command-line interfaces

Use Cases

• Product Strategy Alignment: Bring user calls, investor conversations, and positioning into one shared space to build pitch decks and iterate with stakeholders—one team closed €4.6M pre-seed in a week using Kanwas
• Cross-Functional Collaboration: Replace dead whiteboard sessions with living shared context that product, engineering, and design teams can continuously reference and build upon
• AI-Augmented PM Work: Offload convergent tasks (status updates, spec formatting, meeting notes) to agents while focusing human judgment on divergent decisions like what to build and why
• Knowledge Continuity: Preserve product context when team members join or leave—accumulate institutional memory instead of letting it walk out the door

Target Audience

Kanwas is built for product managers, founders, and product teams who need to make high-stakes decisions with incomplete information—people who recognize that AI has infinite diligence but need a system to supply the specific context and taste that makes reasoning actually useful.