optiml

The control layer for production AI workflows.

4 followers

The control layer for production AI workflows.

4 followers

optiml is the control layer for production AI, letting teams deploy multi-step workflows behind a single endpoint instead of stitching together providers, routing logic, evals, and fallback infrastructure by hand. With support for text, image, voice, and vision across nine providers, optiml helps companies ship faster, stay provider and model-flexible, save money, and improve reliability with built-in versioning, experiments, streaming, eval gates, and automatic rollback.

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Launch tags:API•Artificial Intelligence•YC Application

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Render: Get up to $100K in startup creditsThe fastest way to deploy and scale apps and agents

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Maker

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I built OptiML because shipping AI in production still means too much glue code. Calling one model is easy, but real products need multi-step workflows, provider flexibility, evals, fallbacks, versioning, and safe deployment. I wanted all of that to live behind one endpoint instead of being hand-wired across different services and scripts. What started as model routing evolved into a way to deploy full AI workflows across text, image, voice, and vision, with built-in experiments, eval gates, streaming, and version rollback. The goal is simple: make production AI feel like shipping real software, not stitching together fragile infrastructure.

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8mo ago

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