Open-source AI agent orchestration platform for incident response and automation
Stage
Growing
Not given
Founded
2022
Not given
Based in
US
Not given
Pricing model
Paid
Open source
Pricing
Pay-per-token for language models, per-minute for audio, per-image for image generation, and per-hour for GPU rental. No long-term contracts or upfront costs.
Not given
Key features
100+ machine learning models
Developer-friendly APIs
Text generation models
Image generation with Flux
Automatic scaling
Custom model deployment
Zero data retention policy
SOC 2 and ISO 27001 certified
Dedicated GPU clusters
Multi-GPU setups with SXM connections
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
Own cutting-edge inference-optimized infrastructure with secure US-based data centers
Zero retention policy with SOC 2 and ISO 27001 certification for data privacy
No long-term contracts or hidden fees with simple pay-as-you-go pricing
100+ production-ready models covering all major AI use cases
Customizable inference solutions tailored to cost, latency, throughput or scale priorities
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