Galileo, a new startup founded by Google, Apple, and Uber veterans, has emerged from stealth with $5.1 million in seed funding. With an aim to create data intelligence tools for unstructured data practitioners, Galileo gives data scientists the ability to inspect, discover and fix critical ML data errors 10x faster across the entire ML lifecycle – from pre-training to post-training to post-production. The platform is currently in private beta with the Fortune 500 and startups across multiple industries.
The funding round was led by The Factory, with participation from Anthony Goldbloom (co-founder and CEO at Kaggle) and other angel investors. Company advisers include Amy Chang (Disney, P&G board member) and Pete Warden (one of the creators of TensorFlow).
The company plans to use the funding to hire across all departments and accelerate research and development to meet the demand of the industry for a purpose-built product to find and fix ML data blind spots across the workflow.
It is common for data scientists to use spreadsheets and Python scripts to inspect and fix their training unstructured data. Doing this ‘data detective work’ consumes more than 50% of a data scientist’s time, is ad-hoc, manual, error prone and leads to poor data transparency across the organization, causing avoidable mispredictions and biases in production models.
But with just a few lines of code added by the data scientist while training a model, Galileo auto-logs the data, leverages some advanced statistical algorithms and then intelligently surfaces the model’s failure points with actions and integrations all within one platform. This reduces the time taken to proactively find critical errors in ML data across training and production models from weeks today to minutes with Galileo.