Intelligent Automation, Predictive Analytics, Enterprise AI
Artificial Intelligence isn't future technology—it's today's competitive advantage. We build practical AI solutions that solve real business problems: automating workflows, predicting outcomes, personalizing experiences, and extracting insights from data at scale.
NLP-powered chatbots for customer service, internal help desks, and sales automation. Integration with existing systems, multi-language support, and continuous learning capabilities.
Machine learning models for demand forecasting, churn prediction, maintenance scheduling, and financial projections. Time-series analysis and real-time prediction APIs.
Image classification, object detection, OCR/document processing, quality inspection in manufacturing, and facial recognition systems.
Personalized product recommendations, content curation, and next-best-action systems. Collaborative filtering and deep learning approaches.
Robotic Process Automation enhanced with AI for intelligent document processing, email classification, data extraction, and workflow automation.
Unsupervised learning for detecting unusual patterns, fraudulent transactions, network intrusions, and equipment failures before they happen.
Challenge: Generic product recommendations resulting in low conversion rates and customer engagement.
Solution: Built deep learning recommendation engine using collaborative filtering and content-based approaches. Integrated browsing history, purchase patterns, and real-time behavior. Deployed on AWS SageMaker with <100ms latency.
Results:
Challenge: Unexpected equipment failures causing $2M+ annual downtime costs. Reactive maintenance insufficient.
Solution: Deployed ML models analyzing vibration sensors, temperature, power consumption, and historical failure data. LSTM networks for time-series prediction. Edge inference for real-time alerts.
Results:
Challenge: 15,000+ monthly support tickets, 45-minute average wait times, high customer dissatisfaction.
Solution: Built GPT-4 powered chatbot with RAG (Retrieval Augmented Generation) accessing knowledge base. Integrated with CRM, billing systems, and ticketing. Multi-language support and escalation workflows.
Results:
Challenge: Overstock/understock issues costing $5M annually. Manual forecasting inaccurate.
Solution: Gradient boosting models (XGBoost) considering seasonality, promotions, weather, holidays, and local events. Store-level forecasts updated daily. Automated replenishment recommendations.
Results:
Let's explore how AI can drive measurable business outcomes.
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