AI model of your product's business logic accessible to people and AI agents
Stage
Established
Not given
Founded
2021
Not given
Based in
Not given
GB
Pricing model
Contact for pricing
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
One context layer connecting all GTM tools and AI agents
Agent observability with end-to-end tracing
Source citations for every answer
Permission-aware answers scoped to user access levels
Playbook grounding to enforce business semantics
Corrections inbox for agent-generated changes
Integration with Claude, ChatGPT, Slack, Salesforce and other tools
Open Model Context Protocol (MCP) for any client
SOC 2 Type II compliance and GDPR/CCPA support
140x faster answers via pre-compiled context
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
40x lower cost through pre-compiled context vs raw data processing
98% answer accuracy with no hallucinations through checked data
Agent-agnostic: works with any AI tool your team uses
Never trains on customer data with enterprise-grade security
Set up within days with forward-deployed engineer support
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