Round 1 Winners!
Proof of Usefulness Report

One Fact Foundation

Analysis completed on 3/21/2026

+50.03
Proof of Usefulness Score
You're In Business

The project demonstrates strong technical innovation and real-world utility through ClinicalBERT and impactful university partnerships. However, the submission severely lacks verifiable traction metrics, providing exaggerated claims ('everyone', 'most people have used my product') without specific active user data. This results in heavy penalties for reach, traction, and response quality.

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Score Breakdown

Real World Utility+20.00
Audience Reach Impact+1.00
Technical Innovation+12.75
Evidence Of Traction+1.25
Market Timing Relevance+8.00
Functional Completeness+0.50
Subtotal+43.5
Usefulness Multiplierx1.15
Final Score+50

Project Details

Project URL
Description
We transform healthcare access and efficiency using open-source artificial intelligence. OUR NONPROFIT STRUCTURE Our nonprofit structure allows our partners, such as the National Institutes of Health and Harvard Medical School, to grant access to the health data needed to build, train, and deploy our AI engine, ClinicalBERT. Releasing and conducting research using this open-source AI means we can require enterprises using our tech to validate their deployments of our model against state-of-the-art health equity metrics. PAYLESS.HEALTH Payless.health is a search tool for hospital pricing, negotiated rates, and health outcomes in the United States, supported by a grant from Brown Institute (Columbia & Stanford) to parse newly available but incomplete hospital pricing data. Payless Health will help citizens and businesses save money on healthcare and negotiate with providers/insurers. CLINICALBERT ClinicalBERT is a healthcare-focused AI engine developed in a research paper co-created by our founder and collaborators at Stanford and New York University. It is cited 450+ times and used at multiple academic medical centers to conduct research and build novel technology in biomedical research, life sciences, and pharmaceutical areas. DATA THINKING Data Thinking is a set of open-source courses and industry symposia we're building with our Ivy League and international partners to increase access to artificial intelligence, machine learning, and data science education around the world, such as the skills to use GPT and other large language models to accelerate their learning. CHILDFX ChildFx is an AI tool to accelerate and support pediatric radiology; based on our founder's research paper, Detecting Pediatric Upper Extremity Fractures With Deep Learning Based Object Detection, the One Fact Foundation has worked with Columbia University Medical Center to pilot and test.

Algorithm Insights

Market Position
Growing utility with room for optimization
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