Miloop AI is built around a simple standard: automation that holds up under real use, not just in a demo.

Miloop AI designs and ships production AI systems, from multi-agent pipelines that handle end-to-end content workflows to retrieval-augmented systems and custom-tuned models built for a specific brand voice. Every system includes its own evaluation layer, built into the pipeline itself rather than added on afterward, so accuracy is verified, not assumed.

Speed only counts when accuracy comes with it.

That standard shapes every system Miloop AI builds, from the first prototype through production deployment.

If a process is costing you more time than it should, or you have an AI system you are not fully confident in yet, that is exactly the kind of problem Miloop AI takes on.

---

Founder

Miloop AI was founded by Yingying Sun. Her technical career began at a Fortune 500 technology company, where she spent years managing large-scale programs and standardizing reporting across cross-functional teams. That experience shaped how she thinks about building systems that hold up at scale, not just in a demo.

That foundation carried into her AI engineering work. She has automated high-stakes editorial workflows, including translation, fact-checking, and formatting, and built multi-modal voice AI systems for elderly, bilingual users, where reliability was not a nice to have. It was the point.

She graduated from the University of Michigan with a Master of Applied Data Science, and brings a background in visual storytelling as well. Both disciplines rely on the same core skill: building something a person can actually trust.

(Miloop is named after her cat. Moral support, mostly.)