BUILDS AND EXPERIMENTS

Problem: Lack of real-time visibility into machine status and performance hindered operational efficiency and led to unexpected downtime.

Approach: Built a real-time monitoring dashboard, streaming sensor data through a Flask API to a custom frontend interface for instant analytics.

Results: Automated data collection, enabling instant insights, predicting maintenance needs, and significantly improving factory throughput.

Problem: Fragmented supply chain data and manual fleet tracking caused inefficiencies and delayed decision-making processes.

Approach: Developed a comprehensive ERP system, applying data-driven backend logic and API integrations to unify global supply chain metrics.

Results: Centralized inventory forecasting and fleet tracking into a single command center, optimizing operational efficiency.

Problem: Organizations struggle to match internal talent capabilities with evolving role requirements, leading to skill gaps.

Approach: Utilized NLP and machine learning to analyze user skills and profiles against industry job descriptions.

Results: Provided highly accurate career path recommendations and multidimensional skill mapping to bridge talent gaps.