RAG Development
RAG Development Services for AI That Answers From Your Own Data
Xcrino Business Solutions is an AI-first software development company in New Delhi, India. We build retrieval-augmented generation (RAG) systems: AI assistants that find the right passages in your documents and databases and answer from them, showing where each answer came from.
Since 2016 we have served 560 clients in 26 countries, and 94% of our projects have been delivered on time and on budget. RAG projects start with a fixed-price proof of concept from $3,000 (about ₹2.7 lakh).
- RAG
- LLMs
- Vector search
- Citations
- 560
- clients served
- 26
- countries
- 69+
- developers
- 94%
- projects on time and on budget
Quick answer
What is RAG (retrieval-augmented generation)?
RAG is a way of building AI assistants that first look up relevant information in your own sources, such as documents, policies, product data or support tickets, and then generate an answer from what they found, usually with citations.
Because answers come from your current content rather than the model's memory, they stay accurate and up to date, and your team can check the source. RAG is usually faster and cheaper to build than fine-tuning a model, and many solutions combine the two.
What we build
What RAG solutions does Xcrino build?
- Internal
Internal Knowledge Assistants
Assistants that answer staff questions from policies, manuals, wikis and past projects, with links to the source.
- Customers
Customer Support Assistants
Assistants that answer customers from your help centre and product data, and hand over to a person when needed.
- Documents
Document Search and Q&A
Ask questions across contracts, reports and technical documents instead of searching them one by one.
- Languages
Multilingual RAG
Assistants for English, French, Japanese or Arabic users, tested on real content from each language and market.
- Agents
RAG Inside AI Agents
Retrieval that gives AI agents accurate company knowledge before they act.
AI agents - Quality
Evaluation and Monitoring
Test sets built from real questions, accuracy and citation checks before launch, and quality monitoring afterwards.
Process
How does Xcrino build a RAG system?
- 01
Choose sources and questions
Agree which documents and data the assistant may use, and collect real questions it must answer well.
- 02
Check and prepare the data
Our AI lead reviews whether the content can support good answers. We then clean, split and index it, with access rules.
- 03
Proof of concept
A working assistant on your real content in 2–4 weeks, from $3,000 (about ₹2.7 lakh).
- 04
Evaluate
Test accuracy and citations against the real questions, and fix gaps before anything goes live. The AI lead signs off before launch.
- 05
Launch and monitor
A first production release, usually in 1–2 months from $5,000 (about ₹4.5 lakh), then ongoing monitoring and content updates.
FAQ
RAG development: questions answered
What is RAG, and when should I use it?
RAG (retrieval-augmented generation) lets an AI model answer using your own documents and data, usually with citations. It suits knowledge assistants, support, and policy or product Q&A where answers must reflect current, company-specific information.
Should I use RAG or fine-tuning?
Use RAG when answers must come from documents that change. Use fine-tuning when you need consistent style, format or domain behaviour. Many solutions combine them, and we recommend an approach after discovery and testing.
How much does RAG development cost?
At Xcrino, a RAG proof of concept starts from $3,000 (about ₹2.7 lakh) and a first production release from $5,000 (about ₹4.5 lakh). The final price depends on how much content there is, how clean it is, and the systems the assistant must connect to.
Can a RAG assistant show where its answers come from?
Yes. We design RAG assistants to cite the documents or records each answer is based on, so your team and customers can check it.
Is my data used to train AI models?
Before any build, we agree in writing which providers process your data, where it is stored, and whether it may be used for training. If your rules require it, we scope a private or dedicated deployment.
Who owns the RAG system Xcrino builds?
You do. All source code, prompts and other assets transfer to you once the project is paid in full. Xcrino signs an NDA whenever you ask for one.
Turn Your Documents Into Answers
Tell us which content your team or customers search most, and the questions they ask. We will show you what a RAG assistant could answer and what a proof of concept would cost.
Company details
Xcrino Business Solutions
RAG Development • AI Agent Development • AI Proof of Concept • Machine Learning • Custom Software • ERP
New Delhi, India | Serving clients in 26 countries
E-523, Top Floor, Sector 7, Dwarka, New Delhi 110075 • +91 99539 20493 • info@xcrino.com