• AI Use Case Prioritization for a Telecom


    Identified and ranked over 20 AI opportunities by impact and feasibility. Helped executives focus budget on 3 high-ROI initiatives for immediate value.

  • AI Business Case Development for Retail Expansion


    Crafted a business case for AI-driven demand forecasting and supply chain optimization across multiple stores.

  • C-Suite AI Enablement Workshop for Manufacturing Leadership


    Ran strategic AI visioning sessions to align executives on competitive opportunities, change management, and internal capability building.

  • Fraud Detection Model for Fintech


    Built and deployed a real-time machine learning model that flagged suspicious transactions with 95% accuracy, reducing fraud losses by 40%.

  • Chatbot with Sentiment Analysis for Customer Service

    Developed a multilingual AI chatbot with NLP-based intent recognition and emotion detection, reducing agent load by 60%.

  • Demand Forecasting with External Data for FMCG


    Integrated weather, promotions, and sales history into a forecasting engine. Helped optimize production planning and reduce waste.

  • AI Upskilling Bootcamp for Business Teams


    Delivered customized training for non-technical staff to identify and co-create AI use cases. Sparked 14 AI initiatives from within business units.

  • Executive AI Literacy Series


    Ran short, high-impact sessions to educate C-Suite on AI trends, risks, and strategy alignment — improving top-down support.

  • AI Champions Program Across Global Divisions


    Identified and trained domain-specific AI advocates within each department to drive adoption locally and serve as change agents.

  • Multi-Plant AI Deployment for Predictive Maintenance

    Standardized and scaled a pilot AI model across multiple manufacturing sites using a centralized AI Ops framework.

  • Scaling NLP Models Across Languages

    Optimized and deployed sentiment analysis models in 7 languages for a global brand, increasing insights across diverse markets.

  • Performance Tuning of Recommendation System


    Refactored algorithms and infrastructure for an e-commerce recommender, cutting latency by 50% and reducing compute cost by 30%.