Investigating practical AI applications, machine learning models, and intelligent automation for business. Our research transforms cutting-edge AI capabilities into reliable, production-ready solutions.
Retrieval-Augmented Generation combines the power of large language models with external knowledge retrieval for more accurate and contextual AI responses.
Vector database integration for semantic search
Document embedding and indexing strategies
Context-aware response generation
Real-time knowledge base updates
Hybrid search combining dense and sparse retrieval
Multi-modal RAG for text, images, and structured data
Building intelligent autonomous agents using Model Context Protocol (MCP), OpenAI frameworks, and MIT NANDA architecture for complex task execution.
Model Context Protocol (MCP) for agent communication
OpenAI Assistants API and function calling
MIT NANDA framework for nursing diagnosis agents
Multi-agent collaboration and orchestration
Tool use and external API integration
Memory management and context persistence