Compare SaaS Products

At Lilac, we automate the person taking order at the drive thru with a voice AI. We're building this for Quick Service Restaurants (QSRs) dealing with an historical labor shortage and rising wages. Previous attempts at drive-thru voice ordering are costly to implement and have failed to deliver the accuracy and latency needed. It's now possible to build a voice interface that passes the threshold for a great customer experience. In the United States, there are 200,000 Drive-Thrus handling 6 Billion visits a year. At 3 minutes per order, that's 34,000 human years spent on taking orders annually. Per location, on average we can deliver around $100,000 of value in terms of labor savings, upsell revenue lift, and training costs.

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.