GLEAN - AI Chatbot for Eyecare
Driving earlier detection through AI‑powered eye screening
OpenCV
YOLO
Iris Extraction
Feature Segmentation
LLAMA 2
Transformer Attention Models
Python
Jupyter
Colab
HuggingFace
Reinforcement Learning
Supervised Learning
Unsupervised Learning
Medical Chatbots
Eye Disease Screening
Overview
An AI Platform For Remote Eye Disease Screening
BHSoft developed GLEAN, an intelligent healthcare chatbot designed to improve eye disease screening, patient interaction, and medical accessibility through artificial intelligence. By combining computer vision, natural language processing, and vision-language models, the platform enables users to receive AI-assisted eye health assessments, interact with healthcare information, and access personalized support through a conversational interface.
Designed for both healthcare professionals and patients, GLEAN helps bridge the gap between traditional diagnostic processes and accessible digital healthcare services. The platform delivers timely guidance, automated image analysis, and seamless communication, helping improve early detection and patient engagement in eye care management.
The Challenge
Medical Accuracy • User Personalization
As BHSoft developed GLEAN, the goal was to create an intelligent healthcare assistant capable of supporting eye disease screening while delivering an intuitive experience for both doctors and patients. The platform needed to process multiple forms of medical data, provide reliable insights, and maintain fast response times despite the computational demands of AI models.
Key challenges included:
- Processing and interpreting multiple data types including images, text, voice, and time-series data
- Ensuring medical insights remained accurate, consistent, and relevant
- Optimizing compute-intensive AI models for real-time performance
- Delivering personalized interactions without overwhelming users
The Solution
Vision AI • Conversational Intelligence
Vision-language model integration for image-based diagnosis and recommendations
Medical image analysis using YOLO, segmentation, and iris extraction models
Multimodal data processing across text, images, voice, and time-series data
Voice interaction and chatbot customization settings
Highlights
Highlights
Business Value Delivered
Faster access to preliminary eye health assessments
Increased accessibility for remote and underserved users
Support for multiple user roles through personalized experiences
Strong foundation for expanding into additional medical specialties
More Work From BHSoft
More Work From BHSoft
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