The native language of AI; in human terms, a protocol.
AI model of your product's business logic accessible to people and AI agents
Stage
Startup
Not given
Founded
2026
Not given
Based in
CA
GB
Pricing model
Open source
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
AI-native communication protocol with 88 verbs and two syntaxes
AI See: give any AI model vision by pasting i.ilang.ai URLs
Zero installation required, pure text format
Works across ChatGPT, Claude, Gemini, DeepSeek, Qwen and other models
Loader available via pip and npm for automatic protocol injection
Prompt compression: 67% reduction in tokens for typical instructions
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
First protocol to formally map Greek mathematical symbols as primitive verbs for AI-to-AI communication
Computable vector space for AI judgment using 11 dimensions and fuzzy mathematics instead of binary classification
Open source and MIT licensed with no royalties or approval required
Operates at the instruction and behavioral layer, complementary to MCP and A2A protocols
Tested and benchmarked with public conformance results and DOI-registered research
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
iLang Inc.
GitMir