RAG Development: Chat With Your Business Data
RAG Development Services
Retrieval-augmented generation (RAG) lets an AI answer questions using your own documents and data. When someone asks a question, the system finds the most relevant passages from your files, sends them to the language model, and returns an answer with links to the sources.
RAG is the most practical way to make AI accurate about your business without retraining a model. The quality depends on the details: how documents are split, how search ranks results, who is allowed to see what, and how answers are checked. That's where we focus.
What we offer
- Document ingestionPDFs, Word files, web pages, SharePoint, Google Drive, Confluence, databases and more.
- Search tuningHybrid keyword and semantic search with re-ranking for better answers.
- Permission-aware answersUsers only get answers from documents they are allowed to see.
- Cited answersEvery answer links to the exact source passage.
- Evaluation and monitoringTest question sets, accuracy tracking and feedback buttons.
Common use cases
- Internal knowledge assistant for policies and SOPs
- Customer help centre that answers from your manuals
- Sales assistant that searches proposals and case studies
- Legal or compliance search across contracts
Technology
- LangChain
- LlamaIndex
- Pinecone
- Weaviate
- Qdrant
- pgvector
- OpenAI / Claude / Gemini
- Python
Business benefits
- AI answers based on your own documents,with sources cited
- Always up to dateadd or change documents without retraining models
- Permission-awareusers only get answers from content they are allowed to see
- Fewer wrong answersthan a general chatbot
Why work with Webtech Evolution
- 10+ years of delivery272+ projects for 118+ clients in 12+ countries since 2014.
- One team, end to enddesign, front end, back end, mobile, QA and DevOps under one roof, so nothing gets lost between vendors.
- Clear estimatesa written scope, timeline and price before work starts, and demos throughout the build.
- You own everythingcode, designs and documentation are handed over in full and covered by an NDA.
- Working hours that overlap with yoursMonday to Friday, 10:00–19:00 IST, with extended hours available for clients in the USA, Canada and New Zealand.
How we deliver
Discovery
agree the goal, users, data and how success will be measured.
Prototype
a working version on real examples within the first weeks.
Build and integrate
connect to your systems, add security, testing and monitoring.
Pilot
launch to a small group, measure results and improve.
Scale and support
roll out widely, with ongoing monitoring and updates.
Need people rather than a project? Hire AI developers.
Frequently asked questions
Most text-based content: PDFs, Word and Excel files, web pages, help-centre articles, wikis, tickets and database records. Scanned documents need text extraction first.
We tune retrieval, instruct the model to answer only from the provided sources, show citations, and test with real questions before launch.
Yes. New and changed documents are indexed automatically on a schedule or as soon as they change, so answers reflect the latest information.
Retrieval-augmented generation: the system first finds relevant passages from your documents, then the language model answers using only those passages.
PDFs, Word files, web pages, help-desk articles, Notion, Confluence, SharePoint, Google Drive and database records.
With an evaluation set of real questions, checking retrieval accuracy and answer correctness before and after every change.
Let's Talk!
Have a question about RAG Development: Chat With Your Business Data? Send us a message and our team will reply with next steps.
- Reply within a few hours (Mon–Fri)
- NDA available
- You own the code
Prefer to talk? Call +91-9601965456WhatsApp ushello@webtech-evolution.com
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