Regular updates on the latest AI deals in venture. Follow along to stay up to date!
Genialis, a Boston-based computational precision medicines company, raised $13M in Series A funding. Taiwania Capital and Debiopharm Innovation Fund led the round, with First Star Ventures, Aedalpine Venture Partners, and others participating.
Problem to be Solved
Pharma companies need to model fundamental biology using human data to validate targets, predict biomarkers, and optimally position novel drugs. Current methods are slow and expensive.
How They Use AI
Genialis does not use any of the “hype” AI that ChatGPT and Dall-e 2 are built on (nor should they, given their use-case). Instead they take a more traditional machine learning approach to build in-house predictive models for various biological and drug experimentation tasks. Specifically, they use ML algorithms to predict biomarkers, inform clinical trial design, and predict high-impact experiments, and predict patient diagnosis and prognosis.
Business Model
Unclear. Genialis hasn’t publicly announced pricing, but it is likely that they sell solutions to pharma companies and other healthcare businesses on a per-seat or usage-based SaaS model.
Deep Render, a London-based AI video compression platform, raised $6M in Series A funding at a $30M valuation. IP Group and Pentech Ventures led the deal.
Problem to be Solved
Sending terabytes of video data over a network can be slow and unreliable due to the limitations of internet bandwidth. Deep Render wants to develop a fundamentally new way of compressing data to get significantly better image and video compression ratios (Pied Piper anyone?).
How They Use AI
Deep Render has posted blog articles detailing some of the algorithms they have developed to accomplish video compression. There seems to be three buckets of models: generative models (e.g. GANs), models to fit image distributions (to improve image decompression), and non-neural-network models for low-cost applications. Their core product probably uses AI like stable diffusion or Dall-e 2 to reconstruct noisy images into their original state.
Business Model
TBD. The startup is pre-revenue, but founder Chri Besenbruch claims it has paid proofs-of-concept and pilots lined up with three big tech companies with market caps of over $300B.
Reeco, a Tel Aviv-based hospitality procurement marketplace, raised $10 in Seed funding. Net Capital Ventures and Joule Ventures led the round.
Problem to be Solved
Buyers at hotels and other hospitality businesses spend a lot of time manually finding the optimal suppliers. These purchasing departments are neglected, according to founder Henrik Shimony, despite them owning most of the industry’s expenses. Reeco claims to use AI to match buyers and suppliers in real time.
How They Use AI
There are no details on how Reeco uses AI other than blanket statements such as “to save buyers money” or “to connect customers to suppliers”. It does not appear that they are using any cutting-edge AI. If they are, then it has been kept under wraps. VCs should beware of the old “add shiny buzzword to the pitch, raise $10M” trick.
Business Model
As a two-sided marketplace, Reeco generates revenue by charging a commission on transactions made through its platform. The platform facilitates payments, and Reeco likely takes a commission there too.