The agent-native Growth OS that turns your AI agent into a disciplined growth hacker
Collaborative platform to build immersive roleplay worlds with AI characters
Stage
Not given
Startup
Founded
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Based in
US
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Pricing model
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Freemium
Pricing
Free: 1 member, 1 project, unlimited free contributors and viewers. Solo: $19.90/month for 1 member with unlimited projects. Team: $39/month for up to 3 members, then $10/month per extra member, with unlimited projects and private projects.
Free: $0/month with unlimited characters and messages using free AI models. Plus: $10/month including everything in Free, unlimited public and private worlds, $10 model credits monthly, more detailed personas, more slots, and priority support.
Key features
Complete experiment backlog with candidate ideas
Status tracking from idea to outcome
Shared experiment learnings across team and agents
ICE, PIE, RICE scoring frameworks with voting
Enforced experiment stages with mandatory results and learnings
MCP server for AI agent read and write access
Skills that teach agents the methodology
Plugin for Claude Code and Codex
Web app for team review and collaboration
OAuth security with granular permissions
World editor with visual interface for characters, backstory, and locations
Characters know each other and develop memories
Auto-vector embedding for content retrieval in chat
Advanced prompt customization for system prompts and LLM parameters
GitHub-like collaboration with world forking and change proposals
What makes it different
Agents cannot bypass the method: tests cannot close without measured results and written learnings
Enforced workflow prevents confident guesses and invented wins
Shared memory ensures experiments are never repeated and evidence is preserved
Agents read and write to the same record as teams under identical rules
Data stays in EU on Hetzner servers in Finland
Prevents AI hallucinations through interconnected world lore and character context
Complete control over prompt engineering and AI behavior customization
Private roleplay data not used for AI model training