RAG Knowledge Base: AI That Answers From Your DocsMutahir Abbas
Your company already has the answers. They're just buried in files.
I turn your PDFs, SOPs, wikis, contracts, support tickets and Information into an AI that answers accurately, with citations for every answer, so your team and customers get answers they can check, not guesses.
What you get
A production RAG pipeline: ingestion, smart chunking, embeddings and a vector database
Hybrid search and reranking, so the right passage is found, not just a similar one
Grounded answers with source links (file, page, section)
Permission-aware access: people only see answers from docs they're allowed to see
Auto-sync, so new or edited docs are picked up without re-uploading
Delivered where you need it: website chat, internal tool, Slack/WhatsApp, or inside Claude and ChatGPT via MCP
Works with any source and any AI
Google Drive, Notion, Confluence, Dropbox, Zendesk, HubSpot, databases, scanned PDFs and more. Claude, GPT, Gemini, Mistral, Llama, or a private model hosted on your own servers.
Why me
I've built RAG in production over municipal zoning codes for a live AI SaaS, where wrong answers weren't an option. Every build is tested against real questions before handover.
Unlimited revisions until it answers the way you need.
FAQs
Starting at$600
Duration1 week
Tags
Claude
LangChain
MCP
OpenAI
Python
RAG
AI Chatbot Developer
Database Engineer
Knowledge Base
Service provided by
Mutahir Abbas proDubai - United Arab Emirates
- $1k+
- Earned
- 1
- Paid projects
- 5.00
- Rating
- 30
- Followers
RAG Knowledge Base: AI That Answers From Your DocsMutahir Abbas
Starting at$600
Duration1 week
Tags
Claude
LangChain
MCP
OpenAI
Python
RAG
AI Chatbot Developer
Database Engineer
Knowledge Base
Your company already has the answers. They're just buried in files.
I turn your PDFs, SOPs, wikis, contracts, support tickets and Information into an AI that answers accurately, with citations for every answer, so your team and customers get answers they can check, not guesses.
What you get
A production RAG pipeline: ingestion, smart chunking, embeddings and a vector database
Hybrid search and reranking, so the right passage is found, not just a similar one
Grounded answers with source links (file, page, section)
Permission-aware access: people only see answers from docs they're allowed to see
Auto-sync, so new or edited docs are picked up without re-uploading
Delivered where you need it: website chat, internal tool, Slack/WhatsApp, or inside Claude and ChatGPT via MCP
Works with any source and any AI
Google Drive, Notion, Confluence, Dropbox, Zendesk, HubSpot, databases, scanned PDFs and more. Claude, GPT, Gemini, Mistral, Llama, or a private model hosted on your own servers.
Why me
I've built RAG in production over municipal zoning codes for a live AI SaaS, where wrong answers weren't an option. Every build is tested against real questions before handover.
Unlimited revisions until it answers the way you need.
FAQs
$600