Snap2Find
XOvation Solutions LLC
See it. Snap it. Shop it. Snap2Find it.
Use your smart devices to find and buy anything you see on TV and streaming media with Snap2Find in seconds.
Snap2Find revolutionizes your search and shop experience like Shazam relolutionized the way you buy music.
Mahasti Pourdastan: Co-Founder and CEO
She has over 20 years of experience developing and implementing complex systems for Fortune 100 companies and federal and state governments. Her experience extends to Machine Learning (ML) and other AI-enabled technologies.
David Lease, PhD: Co-Founder and President
Dr. Lease has over 25 years of experience successfully designing, developing, and implementing complex computing solutions for Fortune 100 companies and the federal government. His experience includes full P&L responsibility for over $60 million. His expertise extends to agentic AI, LLMs, and ML.
Brian Quinn
Is an AI and mobile computing architect and streaming media metadata analyst.
Amir Zamani
Is a Software Engineer with AI, LLMs, ML, and UX expertise.
Snap2Find is an easy, fast, and reliable interactive search and shop experience with price comparisons and no interruption of your viewing experience.
55% Faster Purchasing Time
Point (or activate) your smart device while viewing TV or streaming media.
Snap2Find provides search results in seconds
Save Up to 30% Per Purchase
Compare prices, discounts, reviews, and delivery times.
No interruption to the viewing experience (as requested by 94% of Internet purchasers).
33% Lower Cart Abandonment
Make your purchase with one tap and enjoy!
Our Approach
Not just shopping!
Snap2Find is an agentic AI search and purchasing tool for businesses and consumers.
Snap2Find is an agentic AI system for capturing, processing, extracting features, identifying relevant content, and providing reliable, real-time results to Users.
Snap2Find uses a next-generation User Device-Initiated Metadata Extraction (MEX) Engine. The MEX Engine is a modular, agent-oriented reasoning (agentic AI) architecture integrating Large Language Models (LLMs) and Machine Learning (ML) models, such as convolutional neural networks for video and audio spectrogram analysis. The MEX Engine is designed to analyze video-based media captures, User interaction, agentic LLM orchestration, and personalization. It functions as an agent-based reasoning system that combines User context, live feature extraction, distributed research, and memory to provide actionable, structured metadata.
The MEX Engine architecture is extensible, domain-adaptable, and optimized for applications in mobile, Augmented Reality / Virtual Reality (AR / VR), and multimedia discovery interfaces. Snap2Find essentially recognizes entire audiovisual experiences, making it a powerful tool for discovering content and providing useful targeted purchasing experiences.
Snap2Find offers consumers and businesses a unique (patent-pending) interactive search and purchase experience that solves consumers’ pain points:
--Real-time, reliable search results
--Searches streaming media and still images
--Purchase options with price comparisons
--No interruption of the viewing experience