Proof of Usefulness Report

Steg.AI

Analysis completed on 2/2/2026

+351
Proof of Usefulness Score
Certified Problem Solver

Steg.AI is a high-potential deep tech venture backed by $5M in seed funding (Paladin Capital) and NSF SBIR grants. Founded by computer vision PhDs and Rutgers professors, the project addresses the critical 'deepfake' and IP provenance market using proprietary Light Field Messaging technology. While the user submission contained hyperbolic claims ('everyone', 'most people'), external verification confirms strong B2B traction, including a major enterprise customer (global electronics brand) and a web platform launch in Nov 2024. The peer-reviewed CVPR research and active C2PA membership validate the technical innovation, positioning it as a serious player in forensic watermarking despite the lazy submission data.

Ready to Compete for $150k+ in Prizes?

Move this data into a HackerNoon blog draft to become eligible for your share of $150k+ in cash and software prizes

View All Reports

Score Breakdown

Real World Utility+108.0
Audience Reach Impact+40.0
Technical Innovation+85.5
Evidence Of Traction+84.0
Market Timing Relevance+45.6
Functional Completeness+6.4
Subtotal+369.5
Usefulness Multiplierx0.95
Final Score+351

Project Details

Project URL
https://steg.ai
Description
Steg.AI builds forensic watermarking tools for enterprise information security. Steg.AI watermarks enable businesses to protect their digital library against leaks and misuse. Protect and authenticate digital assets by bringing provenance into your pixels. Founded in 2019 by three computer vision PhDs, one Fortune 500 executive, and a Disney Imagineer turned serial entrepreneur, Steg.AI is headquartered in Irvine, CA and develops and applies state-of-the-art steganography technology. Steg.AI has been recognized with a peer-reviewed publication in the top computer vision journal (CVPR, impact factor: 47.8), the 2019 LDV Summit Entrepreneurial Computer Vision Competition winner, and a Small Business Innovation Research award (SBIR) from the US National Science Foundation (NSF). Steg.AI also is a contributing member to the Coalition for Content Provenance and Authenticity (C2PA), the Digital Media Licensing Association (DMLA), also a member of competitive startup accelerators including NYU NextRound, UCI Cove, Deep10, and the Nvidia Inception Program. Steg.AI is venture-backed.

Algorithm Insights

Market Position
Strong market validation with clear user adoption patterns
User Engagement
Documented reach suggests active user community
Technical Stack
Modern tech stack aligned with sponsor technologies

Recommendations to Increase Usefulness Score

Document User Growth

Provide specific metrics on user acquisition and retention rates

Showcase Revenue Model

Detail sustainable monetization strategy and current revenue streams

Expand Evidence Base

Include testimonials, case studies, and third-party validation

Technical Roadmap

Share development milestones and feature completion timeline