V7, a London, UK-based data engine to build and improve AI for computer vision, announced that it raised $33 million in Series A financing.
The round was co-led by AI-focused Radical Ventures and Temasek, with participation from existing investors Air Street Capital, Amadeus Capital Partners, and Partech.
The funding round also included participation from machine learning pioneers Francois Chollet (Keras creator), Oriol Vinyals (DeepMind), Jose Valim (Elixir creator), and Ashish Vaswani, who co-created Transformer models while at Google Brain.
This funding will allow V7’s further expansion into the US market, growing its team in its biggest market.
V7 automates the labeling process, allowing companies to solve data labeling tasks ten times more quickly. The company’s unique “programmatic labeling” workflows use AI models and minimal human steering to apply labels to data at scale.
“The next generation of software won’t run on code, it will run on models fueled by training data. We let our clients easily turn human knowledge into AI models, improving the safety and accuracy of AI. This is incredibly powerful, and in the right hands, can literally save lives. If we want to build software that tackles unsolved frontiers in human health, or our climate, this is the only way”, said CEO of V7 Alberto Rizzoli
V7’s growth trajectory is unabated despite a macroeconomic downturn. In 2022, the business grew ARR by 3x, organic traffic to the V7 website increased by 100x, and the team's headcount increased by 5x to meet significant market demand for the product.
Company: V7 Ltd.
Raised: $33.0M
Round: Series A
Funding Month: November 2022
Lead Investors: Radical Ventures and Temasek
Additional Investors: Air Street Capital, Amadeus Capital Partners, Partech, Francois Chollet, Oriol Vinyals, Jose Valim, and Ashish Vaswani
Company Website: https://www.v7labs.com/
Software Category: AI Data Engine
About the Company: Founded in 2018 by Alberto Rizzoli and Simon Edwardsson, V7 is the training data engine for machine learning teams developing accurate AI. V7 offers a complete toolkit for your training data engine: automated labeling tools, models in the loop, annotation services, and a powerful API. Within half a year of implementing V7, customers report a 33% faster release of models and a 25% reduction in errors on average. The platform now handles over 1 petabyte of AI training data, making it one of the largest libraries of human knowledge applied to images spanning radiology, engineering, and biopharma in existence. With 300+ clients including GE Healthcare, Paige AI, and Siemens, V7’s customers are deploying AI technology to support the faster release of AI models in mission-critical applications.
Source: https://www.v7labs.com/news/v7-raises-33m-series-a