Interactive worlds for people and AI to build, learn and solve problems together
AI model of your product's business logic accessible to people and AI agents
Stage
Not given
Not given
Founded
Not given
Not given
Based in
Not given
GB
Pricing model
Free
Freemium
Pricing
Not given
Free: 10,000 starting credits plus 1,000 per month. Engineering: $29 per active developer per month with 30,000 pooled credits each month. GitMir Vibe: $9 per person per month. Cloud Compute: $99 per project per month. MeetAI: $49 per project per month. GoBots: $99 per venture per month. Market: $49
Key features
Photo to brick set conversion with 3D preview and parts list
Workbench for collaborative brick-by-brick editing
MCP server integration with Claude Code, Codex, Cursor and more
Build structure checking and validation
OAuth sign-in with no token storage
Offline build access with local browser storage
Export digital manuals and wanted parts lists
Interactive environments for AI training
Consent-based human demonstration recording
Builds features, rules and customer paths and keeps them current with every push
Shows what each commit changed in the business logic, not only in the code
Provides change impact analysis before merge showing what could break
Checks PRDs and specifications against the product
Delivers understanding to AI agents over MCP
Runs locally on your machine with GMM Local
Finds risky patterns and problems in the product
Enterprise deployment inside your security boundary
Integrates with Claude Code, Cursor, Codex and VS Code
MCP access for agents with 1-10 credits per answer
What makes it different
Checked outcomes - part connections and build validity are verified by software before delivery
Real objects from photos - converts pictures into buildable brick sets with actual parts that exist
People and AI work on the same design simultaneously within the workbench
Measurable AI learning with transfer testing across different worlds
Nearly 3× fewer errors on Benchmark 001 compared to alternatives
8.4K tokens per question instead of 27.4K for competitors
Results published and measurable; method is proprietary
Reduces AI cost per completed agent action from $0.35 to $0.08
GitMir