AINRA vs Ryph
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
AINRA compared with Ryph
| Detail | 
AINRA | 
Ryph |
|---|
| What it does | The identity layer for autonomous AI
| Open-source AI agent orchestration platform for incident response and automation
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| Stage | Startup
| Not given
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| Founded | 2026
| Not given
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| Based in | Not given
| Not given
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| Pricing model | Open source
| Open source
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| Pricing | Not given
| Not given
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| Key features | - Offline verification in milliseconds
- Cryptographic passports for agents
- Revocation under 60 seconds
- Authority classes and assurance tiers
- No central authority calls required
- Local registrar lifecycle
- Request signing with short-lived keys
- Public conformance testing
- Fail-closed HTTP gating
- Appeal mechanism for revocation
| - Incident response with agent investigation and pull request generation
- Automated workflows triggered on schedules or webhooks
- Agent summoning from GitHub, GitLab and Radicle with /ryph command
- Semantic memory system for shared and persistent agent learning
- Credentials kept behind gateways with no access in sandbox
- Customized environments per repository with cached dependencies
- Browser use for agent interactions with live watching
- Artifacts and pages for reports and overviews
- Deployment options from laptop to Kubernetes
- Tool proxy with allowlisted MCP server integrations
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| What makes it different | - Neutral non-profit root barred by charter from issuing credentials or computing scores
- Fully open standard with published conformance vectors and reproducible releases
- Verification runs offline without phoning home to any authority
- Four independent implementations agreeing on all conformance vectors
- Public recorded ceremony to establish the root across independent custodians
| - Agents work without holding real credentials or keys
- Changes ship as patches that require review before merge
- Runs on your own infrastructure from laptop to cloud
- Semantic memory learns across runs with deduplication and contradiction handling
- Built-in safety assuming agents can be manipulated or exploited
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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) | Not checked yet ● no change since last check | Not checked yet ● no change since last check |
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| Trust Flow (Majestic) | 0 | 0 |
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| Citation Flow (Majestic) | 0 | 0 |
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| Referring domains (Majestic) | 0 | 0 |
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4 details filled in for both companies.
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