Most teams building AI agents hit the same wall. They start with an LLM call, add a few tools, wire up some automation and six months later they're maintaining a pile of brittle glue code that breaks in production, can't scale across tenants, and has no way to handle long-running workflows or keeping a human-in-the-loop cleanly.

Wippy is the open source runtime that replaces that pile.

It's not a chatbot builder, a no-code tool, or an LLM wrapper. Wippy is agent infrastructure, a workflow engine and execution runtime built specifically for teams deploying AI agents in production. Multi-tenant by design. Built on Temporal for durability. Model-agnostic so you're never locked to a single provider.
With Wippy, your developers stop stitching together tools on every new build and start shipping agent-powered features on a foundation that's already solved the hard problems around concurrency, lifecycle management, failure recovery, auditability, and deep LLM integration.

Who it's for:

Professional services businesses looking to encode their tribal knowledge into a production ready system. 
SaaS teams that want to embed AI features without rebuilding their stack
CTOs and engineering leads who need agent systems that hold up under real usage
Founders who want to move fast without creating technical debt they'll spend years unwinding

The many companies already using Wippy are shipping faster, running leaner, and building agent experiences their competitors can't replicate without starting over.
That's the difference between an agent demo and an agent system.
See it running at wippy.ai

Wippy AI

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