WOW Design Agency

RAG Knowledge Chatbots

RAG Chatbot Development for Internal Knowledge

Secure AI assistants that search your documents, wikis, and drives and answer with citations your team can trust.

Starting at
$2,999
Timeline
4-8 weeks
Time spent searching
-75%

Overview

RAG Knowledge Chatbots that delivers results

Your team wastes hours hunting for answers buried in PDFs, Notion pages, and shared drives. Retrieval-augmented generation (RAG) lets staff ask a question and get an accurate, sourced answer in seconds.

We build private RAG pipelines with permission-aware search, so people only see content they are allowed to access, and deploy them in Slack, Teams, or your intranet.

Library shelves full of knowledge
RAG Knowledge Chatbots

100%

Answers with sources

What you get

Deliverables included

Everything in our rag knowledge chatbots service, scoped clearly before we start.

01

Knowledge source audit and ingestion

02

Chunking, embeddings and vector search

03

Permission-aware retrieval

04

Cited answers and source previews

05

Slack, Teams or web interface

06

Accuracy evaluation and monitoring

Transparent pricing

RAG Knowledge Chatbots pricing packages

Clear starting prices and defined scopes for rag knowledge chatbots. Milestone billing and 100% satisfaction guaranteed.

Assistant

1-2 weeks

A website chatbot trained on your content that answers questions and captures leads.

$999
  • Website AI chatbot
  • Trained on up to 50 pages
  • Lead capture to email/CRM
  • Brand voice tuning
  • Usage dashboard
  • 30 days of tuning
Most popular

Agent

3-5 weeks

A multi-step AI agent that qualifies leads, books calls, and works inside your tools.

$2,499
  • Custom AI agent
  • CRM & calendar actions
  • WhatsApp or web channel
  • RAG on private documents
  • Human handoff rules
  • 60 days of tuning

Enterprise

6-10 weeks

Secure automation across departments with governance, audit logs, and SLAs.

$5,999+
  • Multiple agents & workflows
  • n8n / custom orchestration
  • SSO & role permissions
  • PII redaction & audit logs
  • Evaluation test suite
  • SLA-backed support

Need something bespoke?

Results & stack

Outcomes you can measure.

Benchmarks from recent projects, built with tools our team uses every day.

  • LlamaIndex
  • Pinecone
  • pgvector
  • OpenAI
  • Azure OpenAI
  • Slack API

-75%

Time spent searching

100%

Answers with sources

SOC 2

Ready architecture

Process

From brief to launch in four steps.

  1. 1

    Discovery

    We learn your goals, audience, and competitors, then agree on the rag knowledge chatbots scope and success metrics.

  2. 2

    Strategy & concept

    You get a clear plan, early concepts, or prototypes to react to before we commit to production.

  3. 3

    Craft & build

    Our specialists produce the work in focused sprints, with a weekly demo so you always see progress.

  4. 4

    Launch & improve

    We launch, measure what matters, and keep optimising based on real results.

FAQ

RAG Knowledge Chatbots FAQs

Common questions about our rag knowledge chatbots service.

Still have questions?

We're happy to chat through your specific needs and timeline.

Book a discovery call

RAG retrieves relevant passages from your own documents and gives them to an AI model, so answers are grounded in your data rather than general internet knowledge.

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an impact?

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