GoodMem vs Ryph
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
GoodMem compared with Ryph
| Detail | 
GoodMem | 
Ryph |
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| What it does | Memory layer for AI agents that saves tokens, improves itself, and enforces access control
| Open-source AI agent orchestration platform for incident response and automation
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| Stage | Startup
| Not given
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| Founded | 2024
| Not given
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| Based in | US
| Not given
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| Pricing model | Freemium
| Open source
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| Pricing | Self-hosted: Free for commercial use. GoodMem Cloud: From $15/mo with usage-based pricing, 14-day free trial. Enterprise: Custom pricing.
| Not given
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| Key features | - Automated retrieval stack optimization
- Multimodal document processing with page images
- Granular access control and permissions
- Hybrid search with dense and sparse embedders
- Support for multiple LLM providers
- Multi-language SDKs and APIs
- Flexible deployment options
- ISO/IEC 27001 certified security
- SLSA Build L3 provenance
| - 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 | - Achieves frontier model quality at 1/35 of the cost using small self-hosted models
- Automatically optimizes retrieval stack for your data on real queries
- Never locks you in with proprietary storage
- Runs on-premises with full data control
| - 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) | 44 ▲ +1 (up) since last check | Not checked yet ● no change since last check |
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| Trust Flow (Majestic) | 10 | 0 |
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| Citation Flow (Majestic) | 32 | 0 |
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| Referring domains (Majestic) | 70 | 0 |
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4 details filled in for both companies.
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