Proof of Usefulness Report

Abby Health

Analysis completed on 1/3/2026

+68
Proof of Usefulness Score
You're In Business

Abby Health is a verifiable early-stage health-tech startup based in Australia, backed by Alberts Impact Ventures (Seed round, 2022). The project aims to use AI/NLP for clinical insights and offers telehealth services. However, the submission itself contains significant red flags: the traction claim 'most people have used my product' is demonstrably false and hyperbolic, and the audience reach 'everyone' is unrealistic for a niche medical product. While the underlying technology and VC backing suggest potential utility, the poor quality of the submission and lack of verifiable user metrics severely depress the score.

Ready to Compete for $100k in Prizes?

Move this data into a HackerNoon blog draft to become eligible for your share of $100k in cash and software prizes

View All Reports

Score Breakdown

Real World Utility+75
Audience Reach Impact+5
Technical Innovation+65
Evidence Of Traction+10
Market Timing Relevance+80
Functional Completeness+5
Subtotal+41
Usefulness Multiplierx1.10
Final Score+45

Project Details

Project URL
Description
Abby, our AI-powered (NLP) medical assistant, identifies clinical insights within patients' everyday language to enable the early detection of treatment toxicities, disease progression and changes in patients' mental health and motor function. By having more of the conversations patients need - and health professionals don't have the time to have - Abby derives high-quality clinical data for health professionals by converting patients' colloquial language into validated medical documentation.\n\nOur technology's potential to unlock an unprecedented quantity of high-quality patient data provides clinicians with a better understanding of the patient, their disease and treatment interactions to empower a safer and more personalised model of care.
Audience Reach
everyone
Target Users
everyone
Technologies
Health And-Wellness, Analytics, Healthcare Tech
Traction Evidence
most people have used my product

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