Gimlet Labs is building what it calls the first "multi-silicon inference cloud" — software that allows AI workloads to run simultaneously across diverse hardware types including CPUs, GPUs, and specialized accelerators. Its platform automatically disaggregates agentic workloads into component stages and maps each to the most suitable chip without requiring code changes. Rather than optimizing for a single chip vendor, Gimlet treats the entire heterogeneous data center fleet as one unified compute pool — addressing the problem that existing hardware runs at only 15 to 30 percent utilization. It partners across Nvidia, AMD, Intel, ARM, Cerebras, and d-Matrix, positioning itself as the VMware of AI inference rather than a chip-specific stack.

As AI moves from experimentation to production deployment across enterprises, the need for robust operational infrastructure and tooling is growing rapidly, directly driving demand for Gimlet Labs' solutions.

Gimlet raised an $80M Series A led by Menlo Ventures, bringing total funding to $92M, with angels including Intel CEO Lip-Bu Tan and former VMware CEO Raghu Raghuram. The company launched publicly in October 2025 with eight-figure revenues out of the gate and has since more than doubled its customer base across frontier AI labs and major cloud providers.