Proof of Usefulness Report

Caspar.AI

Analysis completed on 1/17/2026

+372
Proof of Usefulness Score
Certified Problem Solver

Caspar.AI is a legitimate, venture-backed (Series A, ~$12M funding) company co-founded by notable Stanford researchers (including David Cheriton). The technology—ambient home sensing for elderly care without wearables/cameras—is highly innovative and protected by 7 patents. However, the project submission itself was of extremely low quality, containing false claims ('most people have used my product') and missing data. While the technology and market utility are exceptional, the score is constrained by the niche B2B reach and the abysmal quality of the provided input.

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Score Breakdown

Real World Utility+22
Audience Reach Impact+3
Technical Innovation+18
Evidence Of Traction+17
Market Timing Relevance+9
Functional Completeness+0
Subtotal+70
Usefulness Multiplierx1.05 (Scale adjustment for Deep Tech)
Final Score+372

Project Details

Project URL
caspar.ai
Description
The number of people in the United States over the age of 55 is expected to double by the year 2050. The number of younger people who will be needed to provide service and care for their elders is not growing at the same pace. Great strides in technology will be required to bridge the gap – and Caspar.AI is taking the lead.\n\nCaspar is an edge AI platform in the home that provides health insights for better \u0026 more efficient care. Caspar AI technology, with seven patents granted, does not require cameras or wearables – yet it produces medical \u0026 behavioral data inside the home that no one else can.
Audience Reach
everyone
Target Users
everyone
Technologies
Analytics, Health And-Wellness, Healthcare Tech
Traction Evidence
most people have used my product

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