Cleanlab, a San Francisco, CA-based provider of an automated solution for boosting the accuracy of enterprise artificial intelligence (AI), LLM, and analytics solutions, raised $5M in Seed funding.
The round was led by Bain Capital Ventures.
The company intends to use the funds to expand operations and its business reach.
Co-founded by Curtis Northcutt, Jonas Mueller and Anish Athalye, all three PhDs from MIT, Cleanlab turns data into models and insights by automatically finding and fixing errors in both structured and unstructured datasets, such as visual, text, and tabular data. Using Cleanlab Studio, both individual data scientists and enterprise teams get value out of their data by automating the process of finding and fixing outliers, label issues, and other data issues in image, text, and tabular datasets, in order to train reliable models and derive accurate analytics and insights. Cleanlab Studio handles model training with auto-ML, requires no hyper-parameter tuning or model selection, no code, and no machine learning expertise to deliver an improved dataset, ML model, and business insights in less time. It is designed to work with most kinds of datasets including text, images, and tabular/CSV/JSON data.
The product is used by organizations like Amazon, Google, Walmart, Deloitte, Wells Fargo and many others.
FinSMEs
20/07/2023