Tensormesh

Tensormesh develops AI inference caching software designed to reduce latency by capturing and reusing computation across large language model requests. The software eliminates redundancy and accelerates inference, offering tools to integrate with existing inference pipelines. It is compatible with inference engines and application programming interfaces for custom stacks. Founded in 2025 and headquartered in Foster City, United States, Tensormesh has raised $24.5M in Series A funding from investors including Laude Ventures, AMD, CoreWeave, Valley Capital Partners, and NVentures. The company addresses the significant computational cost and latency challenges of deploying large language models at scale by intelligently caching intermediate computations, enabling AI service providers to reduce inference costs and improve response times for repeated or similar queries without sacrificing output quality.

AI Infrastructure > Machine Intelligence Systems > Machine Learning Platforms

College Wise > Tsinghua University, Carnegie Mellon University, Peking University, University of Chicago