LLMs generate plans.
Ripple coordinates them.
Ripple doesn't run your AI — it tracks state and routes work. When a task is ready, Ripple fires an event. Your agent executes and posts results back. Ripple advances the graph. The same model works whether the next step goes to Claude, GPT, a human, or a vendor.
The missing layer between generation and completion
State
Ripple knows what happened, what's active, what's blocked.
Dependencies
Tasks activate automatically when their prerequisites complete.
Deadlines
Slips propagate through the graph so nothing is surprised.
Persistence
The workflow lives for as long as the work takes — days, weeks, months.
Franchise research
"Research 50 HVAC franchises I could buy."
A single prompt turns into a multi-step workflow with AI and human tasks in sequence. Each step activates when the previous one completes — no copy-paste, no app-switching, no follow-up emails.
Product launch
"Launch our new product in 6 weeks."
A single prompt turns into a multi-step workflow with AI and human tasks in sequence. Each step activates when the previous one completes — no copy-paste, no app-switching, no follow-up emails.
Content pipeline
"Publish 4 high-quality articles per week."
A single prompt turns into a multi-step workflow with AI and human tasks in sequence. Each step activates when the previous one completes — no copy-paste, no app-switching, no follow-up emails.
A workflow operating system for mixed human-and-agent organizations
The long-term vision: you tell ChatGPT “help me acquire a company.” ChatGPT calls Ripple. A workflow appears: find candidates, analyze financials, get legal review, negotiate terms. This may take months. Claude handles the research. GPT drafts the report. A human approves. A broker handles negotiations. Ripple tracks all of it.
Nobody needed to know which model was doing what. Ripple managed execution state. The AI companies provided intelligence. That's the cleanest boundary — and the most defensible position. When OpenAI ships a better model, Ripple becomes more valuable, not less, because there are more capable executors to route to.
Building something with agents?
The Ripple MCP server gives any AI the primitives to create workflows, assign tasks, and coordinate long-running execution.