Tasks
- Build machine learning (ML) pipelines for OTT screen classification
- Develop neural networks for TV channel recognition and detection
- Create image classification models for classifying video games on TV screens in real time
Optimizing the algorithms while considering constraints and working with a highly complex set of CV and other algorithms. The solutions had to be executed on Smart TV platforms with significant MIPS constraints.
Successfully deployed a secure and compliant AI agent that recommends content, manages schedules, and engages clients in personalized conversations via the fitness-tech platform.
Reduced manual intervention in forecasting and reporting workflows with an AI agent capable of handling real-time price predictions, executing analysis, and sending back KPI reports.
Enabled fast, accurate detection and escalation of non-compliant procedures, reducing human oversight burden by deploying a real-time sterility monitoring system.
Digitized and structured all course materials from PDF-documents and videos based on defined business logic, reducing time spent searching by over 70%.
Achieved a 70% reduction in time spent on supply chain operations with low-latency OCR optimized for edge devices. Eliminated manual entry errors with a dual-validation mechanism.
Developed a generative AI-powered interface for IBC and ASCE queries, enabled iterative refinement, integrated design standards, and optimized mobile/desktop usability.