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Circleback helps teams get the most out of every conversation with best-in-class AI-powered meeting notes, action items, automations, and search. For example, Circleback can automatically identify feature requests that come up in product demo calls and create Linear tasks for each of them, or update your CRM with customer details after a sales call. Before Circleback, Ali led the first integration of LLMs into the Stripe support product and Kevin worked on predictive analytics at Tableau as a senior software engineer.

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.