Real-world implementations showcasing our expertise in traditional machine learning and generative AI solutions across industries
Proven machine learning implementations delivering measurable business outcomes across diverse industries
Implemented real-time surge pricing for a ride-sharing platform using XGBoost to predict demand spikes based on weather, events, and historical patterns.
Deployed K-means clustering to identify traffic congestion patterns across urban intersections for a smart city initiative.
Built an automated inventory tracking system using SVM-based object detection to identify and count products on warehouse shelves.
Developed a loss prevention system using YOLO and custom classifiers to detect suspicious behavior and unscanned items at self-checkout stations.
Implemented defect detection on production lines using convolutional neural networks to identify microscopic flaws in electronic components.
Implemented alternative credit scoring using non-traditional data sources and ensemble methods for underserved populations.
Deployed real-time transaction monitoring using anomaly detection algorithms to identify fraudulent patterns.
Developed patient risk scoring models using electronic health records to identify high-risk individuals for preventive interventions.
Combined Google Maps API with gradient boosting to predict optimal retail locations based on foot traffic, demographics, and competitor proximity.
Integrated Google Places API with clustering algorithms to optimize ambulance positioning based on historical emergency calls and traffic patterns.
Developed a power grid load forecasting system using LSTM networks to predict hourly electricity demand 72 hours ahead.
Built time series models using Random Forest to predict equipment failures based on sensor data patterns.
Created ensemble models combining ARIMA and XGBoost to forecast short-term stock price movements using technical indicators and market sentiment.
Implemented reinforcement learning algorithms to optimize robotic arm movements in automotive assembly lines.
Deployed gradient boosting models to predict component demand across multi-tier suppliers, incorporating seasonality and market trends.
Built isolation forest models to detect anomalies in sensor networks across oil refineries.
Created automated tumor detection system for MRI scans using deep learning segmentation techniques.
Built ensemble models to predict 30-day readmission risk using patient demographics, clinical data, and social determinants.
Built customer retention models using support vector machines to identify at-risk accounts 60 days before churn.
Developed cash demand forecasting for ATM networks using seasonal decomposition and machine learning.
Deployed YOLOv8-based system for autonomous vehicle safety, detecting pedestrians, vehicles, and obstacles in real-time with sub-50ms latency.
Cutting-edge AI implementations leveraging large language models and multimodal AI for business transformation
Comprehensive evaluation framework for Fortune 500 company reduced model selection time by 70% while improving accuracy by 15% through systematic benchmarking and bias detection.
End-to-end MLOps infrastructure for financial services firm achieved 99.9% uptime and reduced deployment time from weeks to hours with automated monitoring and CI/CD.
Domain-specific fine-tuning for healthcare AI improved diagnostic accuracy by 25% while reducing inference costs by 40% through optimized model architecture.
Deployed LLM-based system to help managers write comprehensive, unbiased performance reviews by analyzing employee achievements.
Built conversational AI to handle HR queries, policy explanations, and benefits enrollment using RAG architecture.
Deployed CLIP-based visual search allowing customers to find products using photos or sketches.
Built conversational commerce bot using GPT-4 to provide personalized product recommendations and answer complex queries.
Developed secure speech-to-text system for physician notes maintaining full HIPAA compliance with on-premise deployment.
Deployed voice AI handling customer calls in 15 languages with natural conversation flow and emotion detection.
Implemented retrieval-augmented generation system indexing company documents, wikis, and communications.
Deployed graph-based RAG to analyze complex legal contracts and identify risks, obligations, and dependencies.
Implemented text analysis on job descriptions and employee profiles to identify organizational skill gaps and recommend training programs.
Created dynamic product description generator using fine-tuned language models that adapt tone and content based on customer segments.
Implemented semantic analysis to automatically categorize and route support tickets to appropriate teams.
Deployed LLM-powered system to draft initial responses for common support queries while maintaining brand voice.
Built real-time sentiment monitoring to identify frustrated customers and trigger proactive interventions.
Developed semantic search system using transformer models to match candidates with job requirements beyond keyword matching.
Created voice-based AI interviewer conducting initial screening calls to assess communication skills and basic qualifications.
Built AI tool to rewrite job postings removing gender and cultural bias while optimizing for diverse candidate attraction.
Built hands-free voice interface for factory workers to access procedures, report issues, and control equipment.
Built RAG system for software documentation allowing developers to ask natural language questions about APIs and codebases.
Built HIPAA-compliant conversational AI to handle appointment scheduling, medication reminders, and basic health queries.
Implemented federated learning approach for AI-powered diagnostic suggestions without centralizing patient data.
Built AI-powered surveillance system using DeepSORT and YOLOv5 to track objects across video frames with precise timestamps for security applications.
Integrated Stable Video Diffusion with open-source LLaMA model to generate training videos from text descriptions for corporate learning platforms.