Nishanth Narayanan

• Created LLM-powered SLA monitoring with time-series forecasting via LangChain, integrated with IT systems, cutting SLA violations by 35%. • Built a production RAG system on internal SLA with an ML lifecycle, deploying a Streamlit app for natural-language queries, cutting manual analysis by 40%, and boosting response accuracy for operational queries. • Applied AI governance and security best practices aligned with the EU AI Act and DORA when developing AI-enabled analytics and monitoring workflows.

• Integrated SAP S/4HANA with Power BI using dbt models, increasing reporting efficiency by 15% and aiding market analysis for supply chain and finance teams. • Built 2 dynamic dashboards with DAX and Power Query, accelerating procurement and cost decision-making by 30%. • Automated financial and operational reporting with Python, SQL, and Airflow, cutting manual effort by 40% and improving delivery reliability.

• Built and optimized forecasting and computer vision models using PyTorch and OpenCV, improving model accuracy by ~15% across validation benchmarks. • Applied supervised and unsupervised learning with targeted feature engineering, reducing feature noise and improving model convergence time by ~30%. • Supported NLP-driven automation of reporting workflows, reducing manual reporting effort by 25% and accelerating insight delivery.

Grade = 2.4/5

Grade = 1.8/5