Miniloop

Miniloop is an AI workflow platform built to help teams move from fragile AI experiments to reliable, production-ready systems.

Most AI workflows today are held together by long prompts, chat history, and manual glue between tools. This works for quick demos, but it breaks down as workflows grow more complex. Behavior becomes inconsistent, state is hidden, debugging is difficult, and small changes can cause unexpected failures. Shipping these systems into real products or operations requires constant babysitting.

Miniloop replaces that approach with explicit orchestration. Instead of relying on a model to infer structure and sequence, you define workflows as clear, ordered steps with explicit inputs and outputs. Each step can include AI generation, API calls, data transformations, validation, and conditional logic. Because the workflow is explicit, execution is predictable and repeatable.

Every run in Miniloop is fully observable. You can see exactly what each step received and produced, inspect intermediate state, and replay executions to diagnose issues or verify fixes. Workflows are versioned and composable, so you can update individual steps safely without rewriting entire systems.

Miniloop supports multiple AI providers and lets you choose the right model for each step. Workflows can be triggered on demand, on a schedule, or via API, and integrated directly into existing tools and systems. The result is AI that behaves like software: reliable, debuggable, and ready to run in production.