RAG Development: AI That Answers From Your Company's Own Knowledge
Your organisation's knowledge sits in PDFs, shared drives, SOP manuals, contracts, tickets, and databases that nobody can search properly. Stacklyn builds retrieval-augmented generation systems that let staff and customers ask plain-language questions and get answers drawn from those sources — with citations to the exact document and respect for who is allowed to see what.
Why RAG projects succeed or fail
A demo that chats with ten PDFs takes an afternoon. A production knowledge assistant over tens of thousands of documents that answers accurately, cites correctly, and never shows an employee a file they should not see is a real engineering project. Quality is decided by unglamorous work: cleaning and chunking documents sensibly, extracting tables and scanned pages, combining keyword and semantic search, re-ranking results, enforcing permissions at retrieval time, and measuring answer accuracy against a test set. Most disappointing RAG deployments skipped those steps.
Handling the documents Indian organisations actually have
- Scanned and photographed documents
Much of the paperwork in Indian offices is scanned or photographed. We include OCR and layout extraction so those pages become searchable rather than silently ignored.
- Mixed English and Malayalam content
Circulars, notices, and customer correspondence often mix languages. We index and test retrieval across both.
- Tables in tender and finance documents
Tender documents, rate contracts, and financial statements are table-heavy. We extract tables as structured data so figures are retrieved accurately.
- Role-based access for hierarchical organisations
Permissions are enforced at search time by department, branch, and role, matching how Indian enterprises and institutions restrict information.
What RAG & Private Knowledge Base AI Can Do for Your Business
Internal policy and SOP assistant
Let employees ask how a process works and receive the answer with a link to the governing SOP clause.
Contract and tender analysis
Query obligations, deadlines, penalties, and eligibility criteria across large sets of contracts and tender documents.
Technical manual search for field teams
Give engineers and technicians instant answers from equipment manuals and service bulletins on mobile.
Customer-facing product knowledge
Power website and WhatsApp assistants with accurate answers drawn from product documentation.
Legal and compliance research
Search regulations, circulars, and past case notes with citations for faster first-pass research.
Sales enablement
Find the right case study, specification, or pricing precedent in seconds during client conversations.
What You Get From Stacklyn
Document ingestion pipeline
Connectors for Google Drive, SharePoint, file servers, email, and databases with OCR, table extraction, and scheduled re-sync.
Hybrid retrieval
Semantic vector search combined with keyword search and re-ranking for accuracy on both concepts and exact terms.
Cited answers
Every answer links to source passages so users can verify and trust what the assistant says.
Permission-aware search
Access controls enforced at retrieval so users only receive answers from documents they are authorised to see.
Evaluation and quality monitoring
Test sets of real questions scoring retrieval and answer accuracy, plus feedback loops from users.
Deployment options
Cloud, private cloud in Indian regions, or on-premise deployment with open-weight models where data cannot leave your network.
From Idea to a Measured, Working System
- 1
Discovery on your real data
We review sample conversations, documents, or workflows and confirm feasibility before you commit to a build.
- 2
Pilot with measured accuracy
A working pilot on a slice of real data, scored against an evaluation set agreed with your team.
- 3
Build, integrate, and harden
Production build with integrations, guardrails, monitoring, and human handover or approval steps.
- 4
Launch, monitor, and improve
Supervised launch, weekly quality reviews in the first month, and ongoing improvement from real usage.
Models, Platforms, and Tools We Use
RAG & Private Knowledge Base AI — Frequently Asked Questions
More AI & Automation Solutions
Engineering Services Behind It
Find out what RAG & Private Knowledge Base AI can do for you.
Share your use case and a few real examples. We will tell you honestly what AI can and cannot do for it, and send a scoped proposal within 48 hours.