Open-source AI agent orchestration platform for incident response and automation
Long-term memory for AI agents that organizes itself and corrects itself
Stage
Not given
MVP
Founded
Not given
Not given
Based in
Not given
SE
Pricing model
Open source
Free
Pricing
Not given
Personal: Free during early access. Unlimited memories, all agents with separate memories, no card required. Enterprise: On request, set up by the team for departmental organization with cross-department sharing and direct support.
Key features
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
Self-correcting memory that updates when facts change
Historical memory queries with time-based retrieval
Automatic topic organization and hierarchy
Separate memory for each agent with controlled sharing
Multi-agent support via MCP, REST API, or LangGraph
AES-256 encryption at rest and in backups
OAuth 2.1 authentication and API key management
Data export and deletion capabilities
37 MCP tools with automated verification on every code change
What makes it different
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
Understands what changed, when it was true, and where it belongs - beyond vector database similarity
Never contradicts itself by automatically replacing outdated facts
Fully GDPR aligned with built-in privacy by design
Two-minute integration with Claude, ChatGPT, Cursor and any MCP client
Data stays in Europe on AWS eu-north-1 and never used for model training
Ryph