Proof of Usefulness Report

Quaisr

Analysis completed on 1/28/2026

+263

Proof of Usefulness Score

Gaining Momentum

Quaisr is a verified, high-potential deep tech spinout from Imperial College London and the Alan Turing Institute, backed by $3.1M in seed funding (Crane VC) with partners like BAE Systems. The platform ('SimOps') solves critical efficiency problems in heavy industry by integrating digital twins, AI, and simulations. However, the submission input quality is extremely low, containing verifiable falsehoods (e.g., claiming 'most people have used my product' and 'everyone' as the audience). The final score reflects the project's high technical merit and confirmed external traction, heavily penalized for the inaccurate and lazy submission data.

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Score Breakdown

Real World Utility+22.5

Audience Reach Impact+2.0

Technical Innovation+17.1

Evidence Of Traction+12.25

Market Timing Relevance+8.5

Functional Completeness+0.25

Subtotal+62.6

Usefulness Multiplierx1.05

Final Score+263

Project Details

Project URL

quaisr.io

Description

Quaisr is a cloud integration service for digital twins. Our product helps engineers, data scientists, operators and experimentalists to integrate simulations, machine learning and real-world data; fostering faster decision-making under uncertainty, rapid prototyping, collaboration and standardisation. We are a B2B platform, initially focusing on the energy and fast-moving consumer goods (FMCG) sectors.

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