AI & Automation

RAG Chatbots

AI chatbots that answer accurately from a business's own documents.

RAG Chatbots preview on desktopRAG Chatbots preview on mobile

Project snapshot

Retrieval-augmented chatbots that answer questions from a company's own documents, policies and product data, instead of guessing, for customer support and internal teams.

Project
RAG Chatbots
Type
AI & Automation
Services
  • AI Agent Development
  • Knowledge Base Setup
  • Integrations
Tools
  • LangGraph
  • LLM
  • Vector Database
  • Embeddings
Key capabilities
  • Answers from Your Data
  • Source-grounded Replies
  • Website Chat
  • Internal Assistant
  • Human Fallback
Status
Delivered ยท private client system
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01Overview

ProjectOverview

General AI chatbots sound confident but don't know a business's products, prices or policies. These chatbots use retrieval-augmented generation: the client's documents are split, embedded and stored in a vector database, and the bot looks up the relevant passages before it answers.

The result is an assistant that answers from real company information, can be embedded on a website for customers or used internally by staff, and hands over to a person when a question falls outside what it knows. LangGraph manages the retrieval and answer steps.

02Key features

KeyFeatures

  1. Answers from your documentsReplies grounded in the client's own content, not generic AI knowledge.
  2. Vector searchDocuments embedded and searched to find the most relevant passages.
  3. Website or internal useEmbedded as a customer chat widget or used by staff as an assistant.
  4. Easy to updateAdd or replace documents and the bot's knowledge updates.
  5. Human fallbackHands over when a question falls outside its knowledge.
  6. Agent workflowLangGraph orchestrates retrieval, reasoning and response.

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