Round 1 Winners!
Proof of Usefulness Report

Alchemai

Analysis completed on 3/17/2026

+30.16
Proof of Usefulness Score
You're In Business

The project targets a highly relevant B2B enterprise problem (supply chain risk management) with a conceptually strong solution involving machine learning and network science. However, the submission is severely undermined by exaggerated and highly improbable claims, such as stating the audience is 'everyone' and that 'most people have used my product' for a specialized enterprise tool. These red flags, combined with a lack of verifiable user metrics despite a 2017 launch and 30-person team, result in low quality factor multipliers across traction, audience reach, and response quality, placing the project in the minimal traction category.

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Score Breakdown

Real World Utility+17.5
Audience Reach Impact+1.0
Technical Innovation+3.75
Evidence Of Traction+1.25
Market Timing Relevance+8.0
Functional Completeness+0.25
Subtotal+31.75
Usefulness Multiplierx0.95
Final Score+30

Project Details

Project URL
Description
Our mission is to enable enterprises to preempt supply chain risk. Combining state-of-the-art machine learning with network science, Alchemai EDGE is a software tool designed to enhance supply chain managers’ decision-making capabilities by providing them with the best possible version of their true supply chain network and its dynamics. By leveraging the wealth and diversity of data collected in a supply chain, the solution becomes the primary tool for informing supply chain managers, thus dramatically reducing cost overruns, identifying vulnerabilities and adversarial manipulations in real-time, and increasing profit margins. Alchemai EDGE provides a powerful supply chain visualization platform, an exploratory and interactive infrastructure for risk assessment in the supply chain network, and a characterization of risk cascades that are induced by high-risk suppliers. It also allows supply chain managers to interrogate a supply chain to see the side effects of a company that disrupts the supply chain network. The solution integrates both internal and external data sources to generate a multi- dimensional risk score that is used to assess the quality, robustness, and vulnerability of a supply chain. Alchemai EDGE thus gives an interactive tool for assessing the diversity of risks. This is an innovative and new approach to supply chain management: the use of machine learning to synthesize diverse data, including real-time timing, inventory, and transportation data, to produce a composite risk assessment of supply chain vulnerabilities and robustness. CMMC management and implementation.

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