Langfuse vs iLang Inc.
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Langfuse compared with iLang Inc.
| Detail | L
Langfuse | 
iLang Inc. |
|---|
| What it does | Open Source Agent Evals & Observability
| The native language of AI; in human terms, a protocol.
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| Stage | Established
| Startup
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| Founded | Not given
| 2026
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| Based in | DE
| CA
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| Pricing model | Freemium
| Open source
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| Pricing | Not given
| Not given
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| Key features | - Hierarchical traces capture every LLM call, tool invocation, and retrieval step
- LLM-as-a-judge, heuristic functions, or human review evaluations
- Prompt management with one-click deployments and rollbacks
- Playground to test prompts on real production inputs and compare models
- Experiments with test cases and side-by-side comparison
- Human annotation and collaborative human-in-the-loop workflows
- Cost and latency monitoring with dashboards and alerts
- REST APIs and Query SDK for data access
- Langfuse Assistant to automate the AI engineering loop
| - 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
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| What makes it different | - MIT licensed open source platform with no data lock-in
- Enterprise scale architecture handling billions of monthly events
- Works with any language and framework with no framework lock-in
- Async by default so tracing never blocks your application
| - 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
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| Free plan | Not given
| Not given
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| Open source | Not given
| Not given
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| Platforms | Not given
| 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) | 80 ▲ +1 (up) since last check | 38 ▲ +1 (up) since last check |
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| Trust Flow (Majestic) | 35 | 7 |
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| Citation Flow (Majestic) | 54 | 27 |
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| Referring domains (Majestic) | 6114 | 66 |
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6 details filled in for both companies.
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