Unitary, a London, UK-based company that builds contextual AI to automate content moderation, raised $8 million in funding.
The round was led by Ian Hogarth at Plural Platform, with participation from strategic angels, including technology marketing leader Carolyn Everson, who also joined Unitary’s board.
The funds will be used to grow the team developing its AI technology, accelerate partnerships and continue its open-source work to keep everyone safe online.
Sasha Haco, co-founder and CEO at Unitary, said: “At Unitary, we’re committed to making the internet a safer place for everyone and with the support of investors like Plural, who understand the complexity of developing and scaling deep tech, we can see a clear route to making an impact on this snowballing problem that affects us all.”
Unitary is developing computer vision models to understand online content and make the internet safer.
Since its inception, the company has grown a remote team across five countries, working in partnership with social networks, ad tech companies, and media businesses to enable them to highlight video content that could be unsafe for particular users, platforms, or advertisers.
Company: Unitary Ltd
Funding Month: March 2023
Lead Investors: Ian Hogarth
Additional Investors: Carolyn Everson
Company Website: https://www.unitary.ai/
Software Category: Contextual AI
About the Company: Founded in 2019 by Sasha Haco and James Thewlis in London, Unitary AI is an artificial intelligence company providing a contextual platform for understanding and moderating video content. They build context-aware AI to detect harmful content and keep brands and platforms safe. Its technology is used by leading social networks and ad tech businesses so they can understand every piece of content in detail and with context. Unitary’s contextual AI to remove unsafe but legal video content. Its tech can process 25,000 video frames in a single second and watch 3 billion images a day. The company’s mission is to make the internet safer by understanding content accurately, swiftly, and at scale.