Web infrastructure that translates your site into an AI-readable version approved by you and served to agents at the edge
Open-source AI agent orchestration platform for incident response and automation
Stage
Not given
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Founded
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Based in
AE
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Pricing model
Freemium
Open source
Pricing
Free eight-week pilot including onboarding and model costs. Three paid plans after pilot: Pay as you go (self-serve, usage-based), Subscription (self-serve, monthly or annual flat fee), and Managed (done by company, pricing quoted per site). All plans quoted per individual site based on page count,
Not given
Key features
AI agent rebuilds pages into semantic HTML, FAQs, and structured data
Vision pass captures facts locked inside images
Sifted pages use roughly 90% fewer tokens than originals
Served from edge, humans and search crawlers see original site unchanged
Before-and-after audit score for every page
Measures citations and AI referrals from sifted pages
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
Only AI agents see sifted pages; humans and Google crawlers see original site unchanged
Every claim traces 1:1 to original pages; AI never fabricates or adds content
90% fewer tokens per page while carrying 37% more readable content
Human in the loop approval for every page before serving to agents
Measures results with before-and-after comparison on your traffic
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
SiftServe
Ryph