DigiBoffins

RAG KNOWLEDGE ASSISTANT: RAG Knowledge Assistant Development for Accurate Answers From Your Own Data

DigiBoffins provides RAG development services that turn scattered documents into a secure AI knowledge base. Using retrieval augmented generation, our RAG knowledge assistants answer questions in plain language with citations from your policies, manuals, wikis and databases, respecting permissions and keeping answers current without retraining.

Book a Discovery Call
RAG SERVICES

RAG Solutions We Build.

Whether you need an internal knowledge assistant, a customer help assistant or AI search across thousands of documents, we design each RAG solution around your content, users and security requirements.

Request a RAG Estimate
  • 01

    Enterprise Knowledge Assistant

    An enterprise knowledge assistant that answers employee questions about policies, processes and products from SharePoint, Confluence, Google Drive and more, with citations.

  • 02

    Customer Help Assistant

    A RAG chatbot for your website or app that answers customer questions from help articles, product documentation and FAQs, reducing support tickets.

  • 03

    Document AI Assistant

    A document AI assistant that searches, summarises and compares contracts, reports, manuals and scanned PDFs, so teams find key details in seconds.

  • 04

    Enterprise AI Search

    Enterprise search AI that combines keyword and semantic search across all your tools, returning precise results and AI-generated answers in one place.

  • 05

    Private GPT for Your Company

    A private GPT deployed in your own cloud or on-premise, using enterprise or open-source models so sensitive data never leaves your control.

  • 06

    RAG Pipeline Optimisation

    Improve an existing RAG system with better chunking, hybrid retrieval, re-ranking, evaluation and monitoring to raise answer accuracy and reduce cost.

01 / 02
OUR PROCESS

Our RAG Development Process

  1. 01 of 6

    Knowledge Source Audit

    We map your documents, wikis, PDFs, intranets, databases and tools, identify owners and access rules, and define the questions the assistant must answer well.

  2. 02 of 6

    Data Preparation and Ingestion

    We extract, clean and structure content, including scanned PDFs and tables, and set up automatic syncing so the knowledge base stays current.

  3. 03 of 6

    Retrieval Architecture

    We design chunking, embeddings, hybrid keyword and vector search, re-ranking and metadata filters, tuned for accuracy on your content.

  4. 04 of 6

    Assistant Development

    We build the assistant with a leading LLM, cited answers, permission-aware retrieval and an interface in your web app, Slack, Teams or intranet.

  5. 05 of 6

    Evaluation and Accuracy Testing

    We test against a benchmark of real questions, measuring answer correctness, citation accuracy, hallucination rate and response time.

  6. 06 of 6

    Launch and Knowledge Operations

    We roll out to users, track unanswered questions and feedback, and keep improving content coverage and retrieval quality.

WHY DIGIBOFFINS

Why Choose DigiBoffins for RAG Development?

We combine data engineering, search expertise and LLM development, so our RAG knowledge assistants return answers people can verify and rely on. RAG knowledge assistants are part of our AI & Generative Tech services. Learn more about DigiBoffins or contact our team to discuss your project.

Get Free Consultation
Retrieval Engineering Expertise01 / 06

Retrieval Engineering Expertise

Hybrid search, re-ranking and smart chunking deliver noticeably better answers than basic vector search alone.

KEY FEATURES

Knowledge Assistants Your Team Can Trust.

Every enterprise knowledge assistant we build includes the capabilities needed for accurate, secure answers at scale.

Get Free Consultation

  • Cited, Verifiable Answers

    Each answer shows its sources with links to the original document and page.

  • Multi-Source Connectors

    Connect Google Drive, SharePoint, Confluence, Notion, websites, databases and PDFs.

  • Permission-Aware Retrieval

    Respects existing access rights so users only see what they are allowed to.

  • Hybrid Search and Re-Ranking

    Keyword plus semantic search with re-ranking for precise, relevant results.

  • Automatic Content Sync

    New and updated documents are indexed automatically, keeping answers current.

  • Document and Table Understanding

    Handles scanned PDFs, tables, slides and spreadsheets, not just plain text.

  • Private Deployment Options

    Run in your own cloud or on-premise with private or open-source models.

  • Usage and Gap Analytics

    See what people ask, what goes unanswered and where content is missing.

TECH STACK

Technologies Behind Our RAG Knowledge Assistants.

We choose embedding models, vector stores and LLMs based on your data volume, accuracy targets, privacy requirements and cost.

Get Free Consultation
01

Language and Embedding Models

5 tools
  • OpenAI GPT and Embeddings
  • Anthropic Claude
  • Google Gemini
  • Cohere Embed and Rerank
  • Open-Source Models (Llama, Mistral)
02

Vector and Search Databases

5 tools
  • Pinecone
  • Weaviate
  • Qdrant
  • pgvector (PostgreSQL)
  • Elasticsearch and OpenSearch
03

RAG Frameworks

4 tools
  • LlamaIndex
  • LangChain
  • Haystack
  • Unstructured and document parsers
04

Knowledge Sources

5 tools
  • Google Drive
  • SharePoint
  • Confluence
  • Notion
  • Databases and APIs
05

Cloud and Deployment

4 tools
  • AWS Bedrock
  • Azure OpenAI
  • Google Vertex AI
  • Docker and Kubernetes
BUSINESS IMPACT

Why Invest in a RAG Knowledge Assistant for Your Business?

Your organisation's knowledge lives in policies, manuals, contracts, wikis, tickets and shared drives, and employees spend hours every week searching for it. A RAG knowledge assistant lets anyone ask a question in plain language and get an accurate, cited answer in seconds, whether they are a support agent, a salesperson, an engineer or a new hire.

Retrieval augmented generation grounds AI answers in your own approved content instead of the model's general training, which dramatically reduces hallucinations and keeps answers current without retraining. Built as a secure AI knowledge base or private GPT for your company, it respects existing permissions, works across all your tools and becomes the fastest way for teams and customers to find the right information.

Get Free Consultation
01 / 05
Without RAG

Hours lost searching for information

Answers are buried across drives, wikis and inboxes.

With RAG

Answers in Seconds

Ask in plain language and get a precise, cited answer.

CLARITY FIRST

RAG Knowledge Assistant Questions, Answered.

What businesses ask before building a RAG knowledge assistant.

Retrieval augmented generation is a technique where an AI system first searches your own documents for relevant information, then uses a language model to write an answer based only on what it found, usually with citations.

A RAG knowledge assistant is an AI assistant connected to your organisation's content, such as policies, manuals, wikis and databases, that answers questions in plain language with links to the source documents.

Fine-tuning changes a model's behaviour or style through training. RAG keeps the model unchanged and supplies fresh, relevant information at question time, which makes answers easier to update, verify and control. Many solutions use RAG alone or combine both.

Google Drive, SharePoint, OneDrive, Confluence, Notion, websites, PDFs, Word and Excel files, helpdesk articles, CRMs, SQL databases and custom APIs.

Yes. We build permission-aware retrieval so each user only receives answers from documents they already have access to.

Great digital products are built in partnership. Tell us where you want to take your business, and we will help you get there.

Tell us what you’re building.

Share a few details and we will come back to you to plan the next step.

What happens next

  1. 1

    You share your idea

    A few lines on your goals, users and timeline are enough to start.

  2. 2

    We talk it through

    We discuss your goals on a call and suggest an approach.

  3. 3

    You get a proposal

    We follow up with a proposal and clear next steps.

Project details

Fields marked * are required. We never share your details.

Chat with DigiBoffins

Hi! Click on the WhatsApp icon below to reach our team instantly.

Our team typically replies within a few minutes.

DigiBoffins

Support Team