This project focuses on building an AI-powered customer support chatbot using Azure Bot Service, Azure Language Understanding, and Azure OpenAI. The solution handles customer queries, performs intent detection, provides contextual responses, and integrates with a knowledge base for accurate answers. Security, scalability, and responsible AI practices are implemented to reflect real-world enterprise support systems used by global organizations.

This project involves developing an automated document processing solution using Azure Form Recognizer, Computer Vision, and Text Analytics. The system extracts structured data from invoices and reports, analyzes sentiment and key phrases, and stores results for downstream business workflows. The project mirrors enterprise automation scenarios used in finance and operations departments.

This project focuses on creating a semantic and vector-based search solution using Azure AI Search and Azure OpenAI embeddings. It enables users to search large volumes of unstructured documents with natural language queries. Relevance tuning, indexing strategies, and performance optimization are applied to simulate real-world knowledge management systems.