Control plane for agentic AI security on the endpoint
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
Kirin: Free ($0/mo) for individual developers and small teams (1-5 users), Team plan at $15/mo per user for growing teams (5+ users), Enterprise plan with custom pricing. AgentMesh: Free ($0/mo) with 300 items per category, Premium at $15/mo per user, Pro at $850/mo per user for unlimited API access
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
Policy enforcement before agent execution
Blocks prompt injections and rogue agent actions
Real-time detection of malicious behavior
MCP server scanning and blocking
Shadow AI discovery across organization
Secrets detection and prevention
Skills and extensions vetting
Dangerous artifacts rejection
Support for Cursor, Claude Code, GitHub Copilot, Windsurf
Minute-level deployment
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
Visibility into shadow AI across enterprise systems
Unified control plane for multiple coding agents and IDEs
Supply chain threat discovery before components run
Secure coding enforcement with threat modeling
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
Knostic
GitMir