| What it does | The native language of AI; in human terms, a protocol.
| An engine for long-running agents that rebuilds its prompt under a cap and runs on your budget
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| Stage | Startup
| MVP
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| Founded | 2026
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| Based in | CA
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| Pricing model | Open source
| Freemium
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| Pricing | Not given
| Prototype: free during beta, then from December 16, 2026 it costs $1 per 1,000 agent calls after 1,000 monthly included calls. Production: $20 a month with 20,000 agent calls included, then $1 per 1,000 calls after that. Top-ups: $1 per 1,000 calls, from $10 to $500 at a time, never expiring.
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| 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
| - Prompt rebuilt from journal under token cap at each step to keep it bounded as history grows
- Spending limits checked before each model call at token prices you declare
- Resume after crash without repeating finished actions
- Tool calls returned as actions for your code to carry out
- Proof of what ran: check prompts, re-run engine, download hash-chained journal
- Integrations with Vercel AI SDK, OpenAI Agents SDK, LangGraph, Mastra, Pydantic AI
- MCP server for Claude Code, Claude Projects and Codex
- Works with any model via bring-your-own-key
- TypeScript and Python clients for HTTP API access
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| 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
| - Bounded prompt under a fixed cap while history grows, so costs per call stop climbing on long sessions
- Every run recorded with cryptographic proof: rebuilable prompts, hash-chained journal, re-runnable engine
- Resumes from crash without repeating finished actions using stable idempotency keys
- Budget enforcement before each model call, not reactive overage billing
- No model key storage or logging; your provider bills you directly
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| Free plan | Not given
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| Open source | Not given
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| Platforms | Not given
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| Public API | Not given
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| Community votes | 0 | 0 |
| DR (Domain Rating by Ahrefs) | 38 ▲ +1 (up) since last check | Not checked yet ● no change since last check |
| Trust Flow (Majestic) | 7 | 0 |
| Citation Flow (Majestic) | 27 | 9 |
| Referring domains (Majestic) | 66 | 4 |