Client: Advy
Industry: Biotechnology & In Vitro Diagnostic (IVD) Manufacturing
Core Technologies: Computer Vision, YOLO Object Detection, Deep Learning Convolutional Neural Networks (CNN)
Executive Summary
Advy, an indigenous and innovative pioneer in the development of polyclonal antibodies, native human antigens, and finished reagents in the IVD industry—supported by dedicated goat farms and expert veterinary teams—faced critical bottlenecks in manual cell plate analysis. By partnering with SunBio IT Solutions, Advy integrated a state-of-the-art computer vision pipeline to automate biological sample evaluation, eliminate analysis variances, and streamline telemetry tracking.
The Challenge
Manual Cell Plate Sample Analysis & Growth Tracking Bottlenecks
Traditional microscopic evaluation methods created significant operational roadblocks across biotechnology workflows:
- Subjective Counting Discrepancies: Manual counting introduced high analysis variances across 15- and 45-cell plate layouts.
- Intensive Livestock Oversight: Managing animal immunization and plasmapheresis cycles demanded excessive manual tracking and operational oversight.
- Lack of Digital Intelligence: Complex biological workflows suffered from fragmented data management, missing automated growth forecasting and centralized insights.
The Solution
AI-Driven Cell Plate Analytics and Computer Vision Pipeline
SunBio IT Solutions implemented a tailored deep learning architecture integrating advanced computer vision models to digitize and optimize biological sample evaluation:
- Multi-Layout Support: Seamless capability to process complex 15- and 45-cell plate sample configurations with high precision.
- CNN & YOLO Models: Advanced Convolutional Neural Networks featuring precise bounding box annotation and YOLO object detection for accurate morphological density and sample size evaluation.
- Automated Telemetry Reporting: Instant analytics generation empowering veterinary teams to track animal health trajectories and growth predictions in real time.
Results & Impact
Optimized Precision & Operational Efficiency
| Metric | Before Automation | After SunBio Solution | Improvement |
| Sample Counting Accuracy | 78% | 98% | 25% |
| Manual Analysis Time | 45 mins/plate | 5 mins/plate | 88% |
| Growth Forecasting Variance | $\pm20\%$ | $\pm3\%$ | 85% |
| Reporting Turnaround | 24 hours | Real-time | 100% |
Through this implementation, Advy achieved higher consistency in polyclonal antibody yields, drastically reduced manual counting effort, and established reliable predictive health telemetry across their specialized veterinary farms.
Next Phase
Advanced AI Diagnostics & Scalable Integration
- Predictive Immunization Modeling: Enhanced machine learning forecasting for optimized reagent production cycles.
- Expanded Layout Support: Integrating high-density multi-well plate automation for broader enterprise scaling.
Conclusion
The successful deployment of SunBio IT Solutions’ AI-driven computer vision and YOLO architecture marks a transformative milestone for Advy in the IVD and biotechnology sector. By eliminating subjective counting variances, slashing manual processing time from 45 minutes down to just 5 minutes per plate, and automating animal health telemetry, the solution bridges the gap between complex biological workflows and scalable digital intelligence.
Ultimately, this case study underscores how advanced image analytics and deep learning can revolutionize specialized veterinary and agricultural ecosystems, ensuring peak operational efficiency, reproducible antibody yields, and future-ready diagnostic capabilities