Build a RAG & LLM Integration for Your Business by Amr Khaled Abd-Elmoniem Hamed Build a RAG & LLM Integration for Your Business by Amr Khaled Abd-Elmoniem Hamed
I build practical RAG and LLM integrations that connect your business knowledge, documents, and data to AI-powered search and response systems.
This service can include:
• Document ingestion and preprocessing
• Chunking and metadata design
• Embeddings and vector retrieval
• Retrieval-Augmented Generation (RAG)
• LLM and API integration
• Grounded, source-aware responses
• Structured outputs and validation
• PostgreSQL/pgvector integration
• Error handling and fallback behavior
• Testing and handoff documentation
Typical use cases include internal knowledge assistants, document search, support knowledge systems, policy and procedure lookup, and AI-powered business tools.
You will receive a tested, scoped implementation with setup documentation and a clear explanation of how the system works.
I build practical RAG and LLM integrations that connect your business knowledge, documents, and data to AI-powered search and response systems.
This service can include:
• Document ingestion and preprocessing
• Chunking and metadata design
• Embeddings and vector retrieval
• Retrieval-Augmented Generation (RAG)
• LLM and API integration
• Grounded, source-aware responses
• Structured outputs and validation
• PostgreSQL/pgvector integration
• Error handling and fallback behavior
• Testing and handoff documentation
Typical use cases include internal knowledge assistants, document search, support knowledge systems, policy and procedure lookup, and AI-powered business tools.
You will receive a tested, scoped implementation with setup documentation and a clear explanation of how the system works.