About Us
Partnering for Supreme Success!
Amplify success and serenity with our AI solutions for individuals, startups, universities, and enterprises.
At ProbAI solutions, we serve as your premier AI partner, catering to individuals, budding startups, esteemed universities, and thriving enterprises alike. Our extensive expertise spans computer vision, natural language processing (NLP), and Large Language Models (LLM), enabling us to empower you with cutting-edge solutions that optimize cost-effectiveness and productivity. Whether it's creating in-house LLMs or engineering lightning-fast AI applications, we're dedicated to fulfilling all your AI requirements. Join us on a journey to unlock the potential of AI for your success.
Projects Undertaken
X-Ray Keypoint Detection in Orthodontics
We successfully collaborated with the University of Connecticut’s Orthodontics Department to deliver an advanced Computer Vision-based keypoint detection solution, revolutionizing X-Ray diagnosis. Additionally, we developed a user-friendly front-end web application that has significantly improved orthodontists’ efficiency and workflow, enhancing their diagnostic processes.
Advanced Medical Image Extraction
Building on the success of our keypoint detection project, we again joined forces with the University of Connecticut’s Orthodontics Department to tackle the intricate task of precisely extracting pertinent segments from medical images and accurately placing each of these segments. Our innovative solution seamlessly integrates both image extraction and classification into a singular, cost-effective model, marking a significant stride forward in optimizing orthodontic diagnostics and with artificial intelligence.
X-Ray Analysis Enhancement via Segmentation
Our collaborative venture with the University of Florida brought forth a remarkable project focused on advancing X-Ray analysis. The challenge at hand was to create a solution capable of marking and categorizing multiple patches within X-Ray images. In response, we engineered an image segmentation model, effectively addressing this intricate task. This undertaking represents a significant leap in the realm of medical imaging, offering enhanced capabilities for accurate patch classification in X-Ray diagnostics.