Endgame 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.
Endgame compared with iLang Inc.
| Detail | 
Endgame | 
iLang Inc. |
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| What it does | Context graph for AI-native revenue teams
| The native language of AI; in human terms, a protocol.
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| Stage | Established
| Startup
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| Founded | 2021
| 2026
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| Based in | Not given
| CA
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| Pricing model | Contact for pricing
| Open source
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| Pricing | Not given
| Not given
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| Key features | - One context layer connecting all GTM tools and AI agents
- Agent observability with end-to-end tracing
- Source citations for every answer
- Permission-aware answers scoped to user access levels
- Playbook grounding to enforce business semantics
- Corrections inbox for agent-generated changes
- Integration with Claude, ChatGPT, Slack, Salesforce and other tools
- Open Model Context Protocol (MCP) for any client
- SOC 2 Type II compliance and GDPR/CCPA support
- 140x faster answers via pre-compiled context
| - 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 | - 40x lower cost through pre-compiled context vs raw data processing
- 98% answer accuracy with no hallucinations through checked data
- Agent-agnostic: works with any AI tool your team uses
- Never trains on customer data with enterprise-grade security
- Set up within days with forward-deployed engineer support
| - 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) | 48 ▼ −2 (down) since last check | 38 ▲ +1 (up) since last check |
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| Trust Flow (Majestic) | 8 | 7 |
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| Citation Flow (Majestic) | 35 | 27 |
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| Referring domains (Majestic) | 323 | 66 |
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6 details filled in for both companies.
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