ProblemX.AI
AI team with 10 years of experience building production-ready solutions that reached 150+ million users. Our proprietary mobile-first AI algorithms power major medical, consumer and financial apps.
Remote patient monitoring has emerged as a critical component of modern healthcare, but it faces a fundamental challenge: how do you maintain the quality and safety of medical care while scaling physician oversight across hundreds or thousands of patients? At Next Step Care, we're solving this problem with an innovative agentic AI system that acts as an intelligent medical assistant, creating a seamless bridge between physicians and patients while maintaining the highest safety standards and regulatory compliance.
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AI Research at Harvard Medical School. Smartphone-Based Orthopedic Diagnostics
In an era where healthcare accessibility remains a global challenge, groundbreaking artificial intelligence solutions have been developed that could fundamentally change how we diagnose common foot deformities. Through two innovative studies published in 2024, researchers have demonstrated that smartphone technology combined with advanced AI algorithms can provide accurate, accessible, and cost-effective diagnostic tools for orthopedic conditions that affect millions worldwide.
Building a RAG-Powered Medical Documentation System for Mass General Hospital
We've been working on revolutionizing medical documentation through AI-powered solutions. Recently, we had the opportunity to build a sophisticated Retrieval-Augmented Generation (RAG) system for InterSystems and Mass General Hospital, leveraging InterSystems' vector embedding database technology to transform how medical histories are captured, stored, and retrieved.
Revolutionizing Medical Imaging: From Two Phone Photos to 3D Diagnostic Models
In the world of medical imaging and orthopedic assessment, precise 3D measurements have traditionally required expensive specialized equipment, controlled clinical environments, and trained technicians. We set out to change this paradigm entirely—developing a breakthrough AI algorithm that could create accurate 3D models of human feet and spines using nothing more than a smartphone camera and two simple angles. Patented US11816806B2
Securing Digital Banking: AI-Powered Identity Verification at Scale
In the rapidly evolving world of digital banking, identity verification stands as the critical first line of defense against fraud while simultaneously serving as the gateway to financial services. When one of Europe's major neobanks approached us with the challenge of automating their identity verification process, we were tasked with replacing a system that required 200 full-time employees with an AI solution that could maintain security while dramatically improving efficiency.
Style Transfer and Stable Diffusion. From Research to 150M Users
The journey from academic research paper to mass-market application is rarely straightforward, but few technologies have made this transition as dramatically as neural style transfer and diffusion models. What began as fascinating computer vision research would eventually power applications reaching over 150 million users worldwide, fundamentally changing how people interact with and create visual content.
The Art of Invisible Enhancement: Redefining Beauty Filters with AI
In a world saturated with obviously artificial beauty filters that make people look like plastic dolls, we set out to solve one of mobile photography's most challenging problems: how to enhance human beauty while maintaining complete authenticity. The result was a revolutionary approach to beauty filtering that became so convincing, photos appeared completely unaltered—even to trained eyes.
Semantic Segmentation. From Pixels to Understanding
Back in 2018, when most computer vision applications were still confined to powerful GPU desktops and cloud servers, we embarked on an ambitious journey that would reshape how mobile devices understand and manipulate visual content. Our project centered around semantic segmentation—the task of classifying every pixel in an image—but with a specific focus that would prove to be years ahead of its time: real-time portrait segmentation optimized for selfie photography.