Our flagship product, the Latent AI Efficient Inference Platform (LEIP), is a Machine-Learning-Operations Software-Development-Kit (MLOps SDK) that can optimize and secure neural network runtimes. LEIP is a unified SDK built specifically for machine learning engineers and AI software developers. LEIP brings AI to the edge by optimizing for compute, energy, and memory without requiring changes to existing AI/ML infrastructure and frameworks. It comes with customizable templates called Recipes that are pre-qualified to your hardware with all the maintenance and configuration reduced to a single command line call. Recipes answer questions like: "How do I train a Yolo Model on the MSCOCO Dataset and run it on a Raspberry Pi?" Because there are no worries about the target platform, the iterations and model delivery are much faster.

Roughly a year ago, Latent AI, a now three-year-old, Menlo Park, California-based startup, pitched a handful of investors during TechCrunch's Battlefield competition. It didn't win that contest, but that hasn't kept it from winning the interest of investors elsewhere. It just closed on $19 million in Series A funding in a round co-led by Future Ventures and Blackhorn Ventures, with participation from Booz Allen, Lockheed Martin, 40 North Ventures, and Autotech Ventures. The company has now raised $22.5 million altogether. Steve Jurvetson, the veteran investor and co-founder of Future Ventures, says of possible applications to think of "face-detection algorithms running locally within security cameras or appliances, or Siri-like voice interfaces working instantly," even when there's no network connectivity.