Steg.AI develops a matched pair of machine‑learning models that embed and detect nearly invisible, robust watermarks customized to each image. Their approach is designed to survive common transformations such as resizing, compression, screenshots and re‑encoding, and can be scanned from displays or printouts. The team traces its work to a 2019 CVPR paper and years of academic research by co‑founders Eric Wengrowski and Kristin Dana, and the company received Phase I and II SBIR government grants. Use cases the company targets include stock photography, social media, pre‑release movie assets, confidential documents and integrations with digital asset management platforms. Steg.AI has found early traction with customers that value leak prevention, including consumer electronics brands, and is positioning its product as an enterprise SaaS integration. Financially, the company previously raised NSF grants and angel investment totaling $1.2 million and has announced a new seed round.

Total raised

$5M

Funding rounds

1

Latest round

Seed

Latest activity

Aug 2023