LLM inference and tuning
for the enterprise.

Factual LLMs. Up in 10min. Deployed anywhere.

Contact us
Precise recall with Lamini Memory Tuning.
Your team can achieve >95% accuracy with Lamini Memory Tuning, even with thousands of specific IDs or other internal data.
Run anywhere, including air-gapped.
Training and inference run on Nvidia or AMD GPUs in any environment — on-premise or public cloud.
Guaranteed JSON output.
By reengineering the decoder, Lamini-powered LLMs are guaranteed to output the JSON structure your apps require — with 100% schema accuracy.
Massive throughput for inference.
Lamini delivers 52x more queries per second than vLLM, so your users don’t have to wait.

Our Leadership

Sharon Zhou

Co-Founder & CEO
  • Stanford CS Faculty in Generative AI
  • Stanford CS PhD in Generative AI (Andrew Ng)
  • MIT Technology Review 35 Under 35, for award-winning research in generative AI
  • Created largest Coursera courses (Generative AI)
  • Google Product Manager
  • Harvard Classics & CS

Greg Diamos

Co-Founder & CTO
  • MLPerf Co-founder, industry standard for ML perf
  • Landing AI Engineering Head
  • Baidu Head of SVAIL, deployed LLM to 1+ billion users; led 125+ engineers
  • 14,000 citations: AI scaling laws, Tensor Cores
  • NVIDIA, CUDA architect - as early as 2008
  • Georgia Tech PhD in Computer Engineering