Startup Gimlet Labs is solving the AI inference bottleneck in a surprisingly elegant way

Zain Asgar, a Stanford adjunct professor and previously exited founder, has raised an $80 million Series A for Gimlet Labs. The round was led Gimlet Labs has built what it describes as the first multi-silicon inference cloud. The software splits AI application work across traditional CPUs, AI-tuned GPUs and high-memory systems at the same time. Asgar told TechCrunch that the system runs across whatever different hardware is available. Lead investor Tim Tully of Menlo Ventures wrote in a blog post that a single agent may chain multiple steps, each with distinct hardware demands. Inference is compute-bound, decode is memory-bound and tool calls are network-bound. No chip handles all these needs, Tully noted. Gimlet Labs claims the software speeds AI inference Gimlet launched publicly in October and reported eight-figure revenues from the start. Its customer base has more than doubled in the last four months and includes a major model maker and a large cloud computing company. The startup now employs 30 people and has raised $92 million in total.