RAG Chatbots & Knowledge SystemsImad Dhin
I build intelligent RAG (Retrieval-Augmented Generation) chatbots and knowledge systems that give your AI accurate, up-to-date answers from your own data. Using vector databases (Pinecone, Weaviate, pgvector), advanced chunking strategies, and hybrid search, I create systems that understand your documents, codebase, or knowledge base — and respond with precision. Every system includes smart document ingestion pipelines, semantic search, citation tracking, and conversational memory. Whether it's customer support, internal documentation, legal research, or technical knowledge management, I deliver chatbots that actually know your business.
FAQs
PDFs, Word docs, HTML, Markdown, code repositories, Notion exports, Confluence pages, spreadsheets, and more. I build custom ingestion pipelines tailored to your content types with smart chunking that preserves context.
RAG systems ground every response in your actual data with source citations. I implement hybrid search (semantic + keyword), re-ranking, and confidence scoring to minimize hallucinations and maximize relevance.
Yes. I deploy RAG chatbots as web widgets, Slack bots, API endpoints, or embedded in your existing app. The backend is framework-agnostic and connects to any frontend.
Example work
Contact for pricing
Duration1 week
Tags
Python
AI Agent Engineer
AI Chatbot Developer
AI Developer
AI Engineer
ML Engineer
NLP
RAG
Vector Database
Service provided by
Imad Dhin maxRabat, Morocco
- $50k+
- Earned
- 29
- Paid projects
- 5.00
- Rating
- 149
- Followers
RAG Chatbots & Knowledge SystemsImad Dhin
Contact for pricing
Duration1 week
Tags
Python
AI Agent Engineer
AI Chatbot Developer
AI Developer
AI Engineer
ML Engineer
NLP
RAG
Vector Database
I build intelligent RAG (Retrieval-Augmented Generation) chatbots and knowledge systems that give your AI accurate, up-to-date answers from your own data. Using vector databases (Pinecone, Weaviate, pgvector), advanced chunking strategies, and hybrid search, I create systems that understand your documents, codebase, or knowledge base — and respond with precision. Every system includes smart document ingestion pipelines, semantic search, citation tracking, and conversational memory. Whether it's customer support, internal documentation, legal research, or technical knowledge management, I deliver chatbots that actually know your business.
FAQs
PDFs, Word docs, HTML, Markdown, code repositories, Notion exports, Confluence pages, spreadsheets, and more. I build custom ingestion pipelines tailored to your content types with smart chunking that preserves context.
RAG systems ground every response in your actual data with source citations. I implement hybrid search (semantic + keyword), re-ranking, and confidence scoring to minimize hallucinations and maximize relevance.
Yes. I deploy RAG chatbots as web widgets, Slack bots, API endpoints, or embedded in your existing app. The backend is framework-agnostic and connects to any frontend.
Example work
Contact for pricing