Liquid AI

Liquid AI builds Liquid Foundation Models (LFMs), general-purpose AI models designed for the latency, memory and privacy constraints of running on phones, laptops and other devices. Its LEAP SDK lets developers fine-tune models, prepare them for different runtimes and deploy them on chosen hardware. The company also works with enterprises on specialized applications: a multi-year Shopify licensing agreement announced in 2025 includes a production search model that completes searches in under 20 milliseconds.

An MIT CSAIL spinout, Liquid AI was founded by Ramin Hasani, its CEO, alongside Mathias Lechner, CTO, Alexander Amini, CSO, and Daniela Rus. Its research connects model design with deployment constraints. The company’s STAR framework uses evolutionary algorithms to discover neural network architectures tailored to tasks and hardware. By encoding architectures as numerical genomes, evaluating candidates and recombining successful designs, STAR can jointly optimize model quality, parameter count, cache size and latency on target hardware.

As of August 2026, the company reported 42.2 million model downloads, 56 LFMs shipped and more than 3,300 variants. Liquid AI raised a $250 million Series A in 2024 to expand compute infrastructure, develop its models and accelerate inference and fine-tuning capabilities for edge and on-premise deployment.