Proof of Usefulness Report

Arya.ai

Analysis completed on 1/13/2026

+417
Proof of Usefulness Score
Certified Problem Solver

Arya.ai is a verified, legitimate enterprise AI company founded in 2013 and acquired by Aurionpro Solutions in April 2024 for ~$16.5 million. While the project submission contained significant inaccuracies (wrong name 'StarBlade', exaggerated reach claims like 'most people', and lack of data), external validation confirms a high-utility platform ('Vega') used by 95+ financial institutions including HDFC and ICICI Bank. The score reflects the strong real-world traction and successful exit, heavily penalized by the poor quality of the submission data.

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Score Breakdown

Real World Utility+27
Audience Reach Impact+12
Technical Innovation+12
Evidence Of Traction+21
Market Timing Relevance+9
Functional Completeness+0
Subtotal+81
Usefulness Multiplierx1.02
Final Score+417

Project Details

Project URL
arya.ai
Description
Arya.ai is an enterprise Deep learning platform to automate the complex data science tasks involved while building Neural Network based application or predictive models. \n\nVEGA as the workbench is designed to reduce the product development cycles and automate the complex data science tasks. The platform is optimized for autonomous applications which can learn and re-learn in live without any human input. Using Vega framework \u0026 Network debugging tools, researchers can build complex deep learning systems quickly through visual design of NNs. Vega is being deployed for multiple use cases in fortune 500 companies for use cases like - Claims Automation, Fraud Detection, IoT, Trade Finance etc. \n\nVega provides a single click option to deploy on Arya's cloud or enterprises can choose to scale on private data centers via provisioning layer. Through Vega, continue monitoring your application and scale as required. Vega's hardware recommendations include optimal combinations of CPUs and GPUs.
Audience Reach
everyone
Target Users
everyone
Technologies
Software Development, Robotics, Automation
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