Nirmal Purohit

• Developed an automated GenAI system for new product marketing using OpenAI and LangChain.
• Reduced manual content generation time by 80%.
• Enabled multilingual support for rapid market adaptation.
• Designed a video analytics pipeline using YOLO and Video Swin Transformer.
• Enabled classification of 5+ road defects over 65,000 km.
• Deployed on edge devices with GPS-tagging for real-time inspection.
• Built NLP pipeline with BERT to extract and cluster complaints.
• Flagged potential product quality issues 3 months earlier.
• Achieved >85% clustering accuracy on real consumer feedback.
• Developed ML models to predict failures of key components in real-time.
• Reduced unplanned downtime by 30% across pilot plants.
• Improved maintenance scheduling using anomaly detection.
• Implemented demand forecasting with ML and optimized truck routing.
• Improved forecast accuracy by 18% and reduced logistics cost by ₹2.1 Cr annually.
• Integrated model with SAP for real-time tracking.
• Built price sensitivity models using BSTS and Bayesian regression.
• Simulated impact of pricing scenarios on revenue.
• Adopted by 3 business units for strategic pricing decisions.

• Streamlined data collection methods to minimize analysis errors.
• Automated repetitive tasks using scripting languages such as Python or R, saving time during the analytical process significantly.
• Created and implemented new forecasting models to increase company productivity.
• Utilized advanced querying, visualization and analytics tools to analyze and process complex data sets.

Implemented demand forecasting with ML, and optimized truck routing.

Improved forecast accuracy by 18% and reduced logistics costs by ₹2.1 Cr annually.

Integrated model with ERP for real-time tracking.

Intent Detection Using Domain-Specific Keyword Optimization

Developed an intent classification framework, leveraging keyword-based search optimization and domain-specific feature engineering, to extract actionable insights from unstructured business text data.

• Developed custom algorithms to optimize data mining, increasing the effectiveness of analytical insights.

• Conducted comprehensive audits of existing systems, identifying areas for improvement and potential risks.
• Collaborated with cross-functional teams to establish a unified approach to managing data quality.
• Standardized documentation practices for better knowledge sharing across teams and departments.
• Trained team members in the use of various software tools, increasing overall productivity and efficiency within the department.