V7 Raises $33 Million To Automate Dataset Curation For Companies
V7 has raised $33 million in a Series A funding round today. They offer tools for automated data labelling and dataset management.
Created on November 28|Last edited on November 28
Comment
Computer vision is used by countless companies today in various industries and use cases. However, in many cases, just using a pre-built ML model isn't sufficient, so they must either train their own model from scratch or fine-tune an existing one.
Accurately labeled data is the foundation of training CV models, but many companies don't have the required data ready and prepared for use.
🚀 We’re thrilled to announce our $33m Series A funding round!
— V7 (@V7Labs) November 28, 2022
👇 Find out how we raised the 2nd biggest Series A round in Europe this month:https://t.co/vLJrOd3wj1 pic.twitter.com/jk6kZP0BxY
V7 helps to fix this very problem; By taking pre-trained computer vision models and providing only 100 human-collected samples of what to look for, V7's models sniff like a bloodhound through entire databases of images to automatically label anything it's certain is an instance of what it was told to look for (when it's not certain, it flags them for human interpretation). This is the underlying tech that lives behind their broader application for dataset management, including features for object classification, segmentation, and more.
Who's funding V7, and where's the money going?
V7 today raised $33 Million thanks to a Series A funding round led by Radical Ventures and Temasek, with additional participation from Air Street Capital, Amadeus Capital Partners, and Partech; Numerous high-profile individual investors also pitched in.
They plan to use the money to continue growing their team and continue expansion through the US market.
Find out more
Add a comment
Tags: ML News
Iterate on AI agents and models faster. Try Weights & Biases today.