Round 1 Winners!
Proof of Usefulness Report

Synseis

Analysis completed on 3/20/2026

+104.63
Proof of Usefulness Score
Gaining Momentum

The project proposes a highly relevant technical solution for deploying ML models on edge devices (FPGAs, ASICs). However, the submission is severely lacking in verifiable evidence. Claims such as 'most people have used my product' and an audience reach of 'everyone' are highly exaggerated and diminish credibility. The revenue metric 'all time marketcap: 2500000' indicates a potential cryptocurrency token focus rather than standard business revenue. While the market timing is excellent and the technical domain is promising, the extreme lack of realistic traction metrics and poor response quality yield a low PoU score.

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+50.0
Audience Reach Impact+5.0
Technical Innovation+30.0
Evidence Of Traction+0.0
Market Timing Relevance+30.0
Functional Completeness+1.25
Subtotal+116.25
Usefulness Multiplierx0.9
Final Score+105

Project Details

Project URL
Description
Synseis is a platform designed to rapidly deploy machine learning models on edge devices, such as FPGAs, ASICs. By streamlining the deployment process, Synseis empowers businesses to harness real-time AI capabilities with unparalleled efficiency and performance at the edge.

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