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
US
GB
Pricing model
Freemium
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
Search people by title, function, seniority, location, company size, tech and industry
Search and enrich companies by domain, headcount, industry, tech stack and hiring signals
Scrape careers pages and company homepages for open roles, products and pricing
Match reasons and freshness dates on every record
Works with Claude, ChatGPT, Cursor and any MCP client
REST API with TypeScript and Python SDKs
Field-level checked_at and verified_at dates
Source and data-rights metadata on every field
Free SKILL.md playbooks for GTM workflows
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
Flat monthly pricing with no per-record charges or credits
Fair-use limits visible in every API response, not hidden behind a dashboard
Records count only when data is returned, empty searches use no records
First useful result in under five minutes, no lengthy onboarding
Opt-out honored and suppression data managed by the company
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