Enterprise RAG / Private Knowledge AI

Enterprise RAG Development India

Your company has 50,000 documents — policies, contracts, manuals, SOPs, compliance circulars — that your team can't search effectively. XPndAI builds a private AI that answers any question from your internal knowledge base, on your own infrastructure. No data leaves your environment.

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10xResearch speed
50K+Documents indexed
PrivateNo data leaves your org
4-6 wksBuild time

Enterprise RAG Services

Every RAG system is built on your private infrastructure — your data never goes to a public API.

Legal & Compliance

  • Contract Search AI
  • Legal Research Assistant
  • Compliance Document AI
  • RBI/SEBI Circular Assistant
  • Policy Search Bot
  • Clause Extraction AI

BFSI Knowledge AI

  • Banking Knowledge Assistant
  • Loan Policy Assistant
  • Credit Policy RAG
  • Internal Audit AI
  • Compliance RAG
  • KYC Policy Assistant

Healthcare

  • Medical Knowledge Assistant
  • Hospital SOP Assistant
  • Clinical Document Search
  • Doctor Reference AI
  • Medical Research RAG

Manufacturing

  • Machine Manual Assistant
  • Maintenance Knowledge AI
  • Factory SOP Bot
  • Quality Control Docs AI
  • Technical Documentation AI

Enterprise Internal AI

  • Company Wiki AI
  • HR Policy Assistant
  • Employee Knowledge Bot
  • Finance SOP AI
  • IT Helpdesk Knowledge AI

Security & Access Control

  • On-premise RAG
  • VPC AI Deployment
  • Air-gapped AI
  • Role-based Knowledge AI
  • Permission-aware RAG
  • Private LLM Hosting

Industries We Build For

Law FirmsBFSI / BankingNBFCInsuranceHospitalsManufacturingEnterprises (100+ employees)Government / PSUConsulting Firms

How XPndAI Delivers

Fixed price · 4–6 weeks · You own all code · On-prem or cloud

Step 1

Document Audit & Ingestion

We audit your document corpus — PDFs, Word docs, SharePoint, Confluence, Google Drive — and build an ingestion pipeline. Documents are chunked, embedded, and indexed in your private vector database.

Step 2

Retrieval Architecture

We design the retrieval strategy — hybrid search (semantic + keyword), re-ranking, context window management — tuned to your specific document types and query patterns.

Step 3

Access Control Layer

Role-based access — a junior analyst cannot access board documents, an HR bot cannot surface payroll data. Permission-aware retrieval ensures each user only sees what they are authorised to see.

Step 4

Private Deployment

Deployed on your AWS, GCP, Azure, or on-premise servers. No document or query leaves your infrastructure. We hand over all infrastructure-as-code at the end.

Pricing

Fixed price per project. No monthly SaaS. No per-seat fees. No surprises.

Department RAG
₹12–20L
One team, up to 10K documents
Enterprise RAG
₹25–60L
Multi-team, 50K+ docs, role-based access
Air-gapped Private AI
₹60L+
On-premise, private LLM, air-gapped

Frequently Asked Questions

What document formats does XPndAI's RAG system support?

PDF, Word (.docx), Excel (.xlsx), PowerPoint (.pptx), plain text, HTML, Confluence pages, SharePoint documents, Google Drive files, and scanned documents (via OCR). The ingestion pipeline handles mixed document libraries without manual pre-processing.

How does the RAG system handle scanned PDFs and old documents?

XPndAI uses a high-accuracy OCR layer for scanned documents before embedding. Layout-aware OCR preserves table structures, headers, and multi-column formats — important for legal and financial documents where layout carries meaning.

Can the system answer questions that require reading multiple documents?

Yes. XPndAI builds multi-document retrieval — the AI can read across 5–10 relevant document chunks in a single response, synthesising information from multiple sources. It cites the specific document and page for every claim.

Is the data secure — can we deploy without sending data to OpenAI or Anthropic?

Yes. XPndAI can deploy with a private LLM — Llama 3, Mistral, or Qwen — running on your own servers. No query or document content goes to any external API. For clients with less strict requirements, we use Anthropic/OpenAI APIs with zero-retention data agreements.

How do you keep the knowledge base updated as new documents arrive?

XPndAI builds an automated ingestion pipeline — new documents dropped into a designated folder or SharePoint library are automatically processed, embedded, and indexed within minutes. No manual reindexing required.

What is the difference between this and a simple document search tool?

Search finds documents that contain keywords. XPndAI's RAG system understands questions — "What is our policy on vendor payment terms for international suppliers?" — and synthesises an accurate answer from the relevant policy documents, with citations. It handles synonyms, context, and multi-part questions that keyword search cannot.

Your internal knowledge should answer questions, not just sit in folders.

Free 45-min discovery call. We'll assess your document corpus and propose an architecture. Fixed price.

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