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Hamming automates the QA of voice agents. (both pre-deployment testing and post-deployment analytics) Making voice AI agents reliable is hard. A small change in prompts, function call definitions, or model providers can cause large changes in LLM outputs. We have a proven track record of helping enterprises win with AI. Sumanyu (CEO) previously helped Citizen (safety app) grow its users by 4X and grew an AI-powered sales program to 100s of millions in revenue/year at Tesla. Our eng team ranks #1 on https://workweave.ai/

Yoneda Labs provides software to help chemists optimise reactions. When chemists make a drug or a material, we help them figure out the best reaction parameters such as temperature, concentration and catalyst. When Jan was working at chemical labs, he experienced the struggle of spending weeks guessing reaction conditions. We then started experimenting with ML to speed up the process. Now, as a team of three friends from the University of Cambridge, we’ve spent the last month combining our domain expertise in Computer Science, Machine Learning and Chemistry to develop state of the art models for reaction optimisation. Although ML is becoming well established in other fields, current chemical models generalise poorly and require lots of programming experience. We make our models easily accessible to chemists in the lab. Finding the right conditions quickly allows pharmaceutical companies to test more drugs, and finding better optima makes manufacturing process cheaper and more environmentally friendly.