Edge-first agent serving framework for cloud, OpenWrt, and device deployment
AI model of your product's business logic accessible to people and AI agents
Stage
Not given
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Founded
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Based in
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GB
Pricing model
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Freemium
Pricing
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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
Deploy agents across cloud, OpenWrt nodes, and custom runtimes with unified SDK
Discover agent capabilities and route calls based on live state, identity, and policy
Agents operate authorized computers and phones securely
Team token management with project-scoped access and attributable usage
Adaptive API pool connecting multiple providers with health, quota, and cost selection
Enterprise OpenWrt router with policy routing and audit trails
Self-hosted Community edition under Apache 2.0 license
Organization-level access control and tenant management
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
Single unified network connecting agents across cloud, edge, and devices
OpenWrt router for private network agent discovery and policy routing
Secure device operations with audit trails through cloud interfaces
Both self-hosted Community and managed Enterprise Cloud options
Adaptive API failover with multi-provider capacity pooling
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