Steg.AI puts deep learning on the job in a clever evolution of watermarking

Steg.AI, a company specializing in deep learning, has developed a nearly invisible watermarking technique that can be embedded into images, making it more robust against common countermeasures such as resizing and resaving. The watermark, which can be easily applied and detected, is customized to the image by a pair of machine learning models. The encoding algorithm identifies the best places to modify the image in a way that is imperceptible to humans but can be easily detected by the decoding algorithm.

The company has found traction among enterprises where leaked information is a concern, such as consumer electronics brands. Steg.AI plans to offer its watermarking technology as a SaaS integration with digital asset management platforms. The company has recently raised a $5 million A round led by Paladin Capital Group, with participation from Washington Square Angels, the NYU Innovation Venture Fund, and several angel investors.

Key takeaways:

Steg.AI is developing a deep learning approach to watermarking digital assets, allowing creators to embed a nearly invisible watermark that is robust against transformation and re-encoding.
The watermarking process involves a pair of machine learning models that customize the watermark to the image, making modifications that are imperceptible to humans but easily detectable by the decoding algorithm.
The company's approach has found traction among companies where there is a strong consumer appetite for leaked information, such as consumer electronics brands, and they plan to provide enterprise-level SaaS integrations.
Steg.AI recently raised a $5 million A round led by Paladin Capital Group, with participation from Washington Square Angels, the NYU Innovation Venture Fund, and angel investors.

Steg.AI puts deep learning on the job in a clever evolution of watermarking | TechCrunch

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