Round 1 Winners!
Proof of Usefulness Report

Tetricus Labs

Analysis completed on 3/18/2026

+40.23
Proof of Usefulness Score
You're In Business

The project targets a legitimate real-world problem in psychiatric care utilizing neuroscience and machine learning, which yields a high utility and timing score. However, the submission suffers from highly exaggerated and unsubstantiated claims (e.g., claiming 'everyone' as the audience and stating 'most people have used my product'). These statements contradict the specialized B2B nature of the platform, resulting in heavy penalties for traction, audience reach, and response quality. Without verifiable user metrics, the project fits firmly in the minimal traction category.

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Score Breakdown

Real World Utility+20
Audience Reach Impact+1
Technical Innovation+9
Evidence Of Traction+0
Market Timing Relevance+7
Functional Completeness+0.25
Subtotal+37.25
Usefulness Multiplierx1.08
Final Score+40

Project Details

Project URL
Description
Tetricus was founded in 2022 by Lindsay Dow, Dr. Philip Corlett, and Dr. Sean McCurdy to leverage breakthroughs in neuroscience & machine learning to revolutionize the patient journey from diagnosis to treatment and recovery. Tetricus’ software platform supports leading psychiatric hospitals and providers to comprehensively assess incoming referrals, match patients with the right type and level of treatment, and monitor patient outcomes to refine and optimize care over time.

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