iLang Inc. vs RELAI
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
iLang Inc. compared with RELAI
| Detail | 
iLang Inc. | 
RELAI |
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| What it does | The native language of AI; in human terms, a protocol.
| The continual learning engine for AI agents
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| Stage | Startup
| Not given
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| Founded | 2026
| Not given
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| Based in | CA
| Not given
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| Pricing model | Open source
| Freemium
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| Pricing | Not given
| RELAI Free: $0. RELAI Enterprise: Custom pricing.
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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
| - Capture signals from code, requirements, and production traces
- Build and maintain EvalsWiki as versioned behavioral knowledge
- Find missing eval coverage and unclear expectations
- Generate complete evals with scenarios, environments, and evaluators
- Optimize harness across prompts, tools, workflows, and code
- Multi-objective optimization for quality, cost, latency, and KPIs
- Model selection, migration, and routing with evaluation
- Regression-controlled improvement with evaluation evidence
- Versioned storage in repository with pull requests
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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
| - Turns failures into replayable learning environments
- Prevents regressions by keeping previous evals in the loop
- Integrates with existing observability stacks and traces
- Preserves business intelligence versioned in repository
- Adapts harness to model changes without redefining use cases
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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
| Not given
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 38 ▲ +1 (up) since last check | 23 ● no change since last check |
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| Trust Flow (Majestic) | 7 | 13 |
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| Citation Flow (Majestic) | 27 | 25 |
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| Referring domains (Majestic) | 66 | 79 |
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4 details filled in for both companies.
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