RAG 

RAG is a powerful approach that blends large language models (LLMs) with your private knowledge base to generate context-rich, accurate, and up-to-date responses. Instead of relying only on pre-trained data, RAG retrieves information from trusted sources (documents, databases, APIs) and combines it with AI-generated language.

With my expertise in LLMs, vector databases, and custom pipelines, I design and deploy business-ready RAG systems for:

• Smart Chatbots & Virtual Assistants – that understand your domain and answer with precision.

• Knowledge Management Systems – making your internal data instantly searchable and conversational.

• Customer Support Automation – delivering accurate responses that reduce manual workload.

• Enterprise Insights – empowering decision-making with contextual, real-time knowledge.

✅ Accurate, real-time, and context-aware responses
✅ Scalable architecture with vector databases (e.g., Qdrant, Pinecone, Weaviate, FAISS)
✅ Secure integration with your existing workflows
✅ Enhanced user experience and trust in AI solutions