

Miniloop is an AI workflow platform designed specifically for building production-ready AI pipelines and automation systems. It enables users to orchestrate AI workflows they can trust by combining AI generation with deterministic logic in production pipelines.
Key features include explicit input/output contracts for every step, automatic validation and deterministic behavior, and the ability to run workflows on schedule, via API, or through chat. The platform provides full observability with complete execution history, versioning, replay capabilities, built-in validation, retry logic, and structured outputs in formats like JSON, CSV, markdown, and HTTP.
The platform works by allowing users to define workflow logic once and run it reliably with any input. It orchestrates custom API calls, data transformations, validation, and exports in workflows that can operate on schedule or on demand. Every pipeline run is logged, versioned, and replayable with built-in validation, retries, and failure handling.
Benefits include predictable execution every time with steps running in defined order, full visibility for debugging complex workflows, and the ability to build sophisticated automations from small, reliable steps. Users gain control over AI behavior by specifying what happens at each step rather than relying on model interpretation.
The platform targets founders and engineers who want to iterate faster by skipping glue code, manual wiring, and brittle workflows. It integrates with various tools including Apollo, HubSpot, Gmail, Airtable, Slack, Google Calendar, Notion, Ahrefs, Linear, Semrush, X/Twitter, Google Sheets, and Google Docs.
admin
Miniloop is designed for founders and engineers who need to build reliable AI systems that actually run. The platform helps technical teams iterate faster by skipping glue code, manual wiring, and brittle workflows. It's suitable for organizations looking to implement production AI pipelines with explicit contracts and deterministic behavior.