Open-source AI agent orchestration platform for incident response and automation
Stage
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Founded
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Based in
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Pricing model
Freemium
Open source
Pricing
Free plan with 10,000 monthly credits; Starter at $50/month with 40,000 credits; Pro at $500/month with 400,000 credits; Enterprise with custom pricing. Additional pay-as-you-go credits available. Pricing based on a credit system where 1,000 credits equals $1.25.
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Key features
Agentic OCR parsing with semantic understanding for complex document layouts
Support for 130+ file formats including PDFs, Office docs, images, and spreadsheets
Structured data extraction with schema-based, LLM-powered agents
Document classification and splitting based on natural language rules
Enterprise-grade RAG indexing and retrieval pipeline
Handwritten text parsing and structured extraction
Table and chart extraction with structured row and column relationships
Cloud SaaS or VPC deployment with flexible data residency options
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
What makes it different
4x cheaper than frontier labs, 5x more accurate than other APIs
Auto-correction loops with recursive checks that detect and fix errors automatically
Task-specific specialist agents that route content to the right expert
HIPAA, GDPR, and SOC2 compliant with enterprise-grade security
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
Ryph