Tasks
- Develop a classification model to help customers understand their spending habits.
- Create an adjustable ML model to profile credit and debit transactions.
- Build a clustering ensemble to define regular and irregular transactions.
The main challenge was to create a competitive advantage by utilizing AI to distinguish the financial app from others and to grow expertise in advanced analytics and machine learning.
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.