Infinity AI, a Los Altos, CA-based startup that generates automated synthetic training data, announced that it raised $5 million in seed funding.
The round was led by Matrix, with participation from founders and operators from companies like Snorkel AI, Tesla, and Google.
The funds will be used to bring the company's novel generative tools, which complement Infinity's existing self-serve API, to market.
"We want to make it easy for ML teams to start working with synthetic data," says Lina Avancini Colucci, Co-founder of Infinity AI. "The ML community has a scarcity mentality with regards to data today. Synthetic data turns this into an abundance mentality. Infinity is democratizing access to training data since this is the biggest roadblock to progress in ML today."
Infinity's platform allows engineers to upload a single real-world video and turn that into hundreds of similar and perfectly labeled synthetic videos.
Infinity AI currently works with over a dozen customers across fitness and smart facilities, including Tempo Fitness, Voxel Safety, SwRI, and Fortune 50 company. Infinity's customers have generated over 5 million synthetic data frames using the self-serve API in just six months.
Company: Infinity AI, Inc.
Raised: $5.0M
Round: Seed Round
Funding Month: December 2022
Lead Investors: Matrix
Additional Investors:
Company Website: https://infinity.ai/
Software Category: Synthetic Data as a Service
About the Company: Founded by Lina Colucci, Sidney Primas, Andrew Weitz, and Daniel Hensley, Infinity provides a platform that allows engineers to upload a single real-world video and turn that into hundreds of similar and perfectly labeled synthetic videos. The company uses a combination of physics-based simulations and generative techniques to do this. The company offers open-source synthetic datasets for both academic and commercials use, enabling engineers to build robust ML models faster with minimal bias.
Source: https://www.prnewswire.com/news-releases/infinity-ai-raises-5m-to-build-automated-synthetic-training-data-301703859.html