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Fiverr Pro
English
$
USD
I will build a rag application for accurate ai answers in your private knowledge base
Yousaf K
About this gig
Tired of AI giving inaccurate answers? I build RAG (Retrieval-Augmented Generation) solutions that connect AI to your data for accurate, reliable, and source-backed responses.
What I Build
Document Q&A Systems
AI that answers questions from PDFs, Word files, Excel sheets, and internal documents with source citations.
Website Knowledge Bots
Train AI on your website content, products, services, and FAQs.
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Database-Connected AI
Connect AI to SQL/NoSQL databases for real-time, data-driven responses.
Private & Secure RAG
On-premise and private deployments for healthcare, legal, finance, and other sensitive industries.
Enterprise RAG Solutions
Scalable systems with authentication, logging, dashboards, and multi-user support.
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Tech Stack
- GPT-4 Claude LLaMA Mistral
- LangChain LlamaIndex Haystack
- Pinecone ChromaDB Qdrant FAISS
Deliverables
- Fully functional RAG application
- Vector database setup & indexing
- Clean source code
- Chat interface or web app
- Deployment guide
- Source citations in responses
- 7-day support
Message me with your data source and use case, and I'll recommend the best RAG architecture for your project.
Get to know Yousaf K
Yousaf K
Senior Full Stack Engineer
- FromPakistan
- Member sinceJun 2026
- Avg. response time1 hour
Languages
Urdu, Punjabi, English, Hindi
I am a top talent passionate about solving real-world problems—not just writing code. I have delivered a wide range of applications, including AI-powered platforms, helping clients improve productivity, automate operations, and accelerate growth. I focus on impact, adaptability, and results.
Other AI Development Services I Offer
FAQ
What types of files can the RAG system process?
PDF, Word (.docx), Excel (.xlsx), PowerPoint, plain text, HTML, Markdown, CSV, and web-scraped content. I can also connect to SQL databases (MySQL, PostgreSQL), MongoDB, and REST APIs.
Will my private data be sent to OpenAI?
Only the relevant retrieved text chunks (not your full documents) are sent to the LLM per query. For complete privacy, I can use a locally hosted open-source LLM (LLaMA, Mistral) so NO data ever leaves your server.
How is RAG better than ChatGPT file uploads?
ChatGPT file uploads have size limits and no persistent memory. RAG builds a permanent, scalable vector database that handles thousands of documents, persists across sessions, and cites its sources in every answer.
Can multiple users access the system at once?
Yes! The Premium package includes multi-user support with role-based authentication. Standard is suitable for single-user or small team use.
Can I add new documents to the system later?
Absolutely. I build an ingestion pipeline so you can continuously add new files — no code required. The system updates its knowledge base automatically.
