Proof of Usefulness Report

Kumo AI

Analysis completed on 1/24/2026

+766
Proof of Usefulness Score
Unicorn Utility

Kumo.ai is a high-potential Series B startup ($37M+ funding led by Sequoia) founded by world-class experts from Stanford, Airbnb, and LinkedIn. The project addresses a critical enterprise need by applying Graph Neural Networks (GNNs) directly to data warehouses. While the verified external evidence indicates exceptional innovation and strong enterprise traction (customers include Reddit, Doordash, and Snowflake), the submission itself was of very low quality, containing lazy and inaccurate claims (e.g., 'most people have used my product'). The score reflects the verified high value and technological sophistication of the project, adjusted downward for the poor submission quality and claim accuracy.

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Score Breakdown

Real World Utility+247.5
Audience Reach Impact+96.0
Technical Innovation+220.5
Evidence Of Traction+180.0
Market Timing Relevance+95.0
Functional Completeness+2.5
Subtotal+841.5
Usefulness Multiplierx0.91
Final Score+766

Project Details

Project URL
Description
Query the Future: Make AI for enterprises as simple as analytics.\n\nIn just a single sitting, on the same Kumo Graph, query your future along every angle using our SQL-like language\n\nEasily deploy your model by REST API so you can continuously update your predictions over time, track model quality, data drift, etc.

Algorithm Insights

Market Position
Strong market validation with clear user adoption patterns
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