VisionXGen
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AI Chatbots

Customer support that never sleeps — powered by your knowledge, not generic answers.

Generic chatbots hallucinate or say 'I don't know' because they're trained on the public internet, not your business. We build RAG-powered AI chatbots trained on your documentation, support history, and product knowledge — deployed across WhatsApp, Slack, web, and internal portals — so they resolve 70%+ of routine questions autonomously while routing edge cases to humans with full context.

Ideal for

SaaS companies, e-commerce & enterprise support teams drowning in repetitive tickets

Delivery

3–6 weeks

Engagement

Fixed-scope build with knowledge-base setup

Tech Stack

The tools and frameworks we use to deliver this service.

OpenAI
Claude
LangChain
Pinecone
Vector Databases
FastAPI

What's Included

Custom knowledge-base training on your documentation
Multi-channel deployment (web, WhatsApp, Slack, Teams)
Intelligent escalation with human handoff
Conversation analytics and resolution dashboards

Proof, Not Promises

Real engagements where this service delivered measurable results.

71%
Self-resolution rate

RAG Chatbot for SaaS Onboarding: 71% Self-Resolution, 60% Cost Reduction

A RAG chatbot trained on 800 support tickets and full help docs resolved 71% of SaaS onboarding questions autonomously — cutting support costs 60% in 90 days.

Read case study

Frequently Asked Questions

How is this different from a basic ChatGPT widget?

A basic widget answers from general knowledge. A RAG chatbot retrieves answers exclusively from your approved documentation — your help centre, product specs, internal wiki, and resolved support tickets — so it gives accurate, brand-consistent answers instead of hallucinating. The difference in accuracy is the difference between a chatbot users trust and one they abandon.

What data do you need from us?

We work with whatever structured knowledge you have: help centre articles, product documentation, FAQ pages, and ideally a corpus of resolved support tickets (the gold standard for capturing institutional knowledge that formal docs miss). If your documentation is thin, we help you build it as part of the engagement.

How do you prevent the chatbot from giving wrong answers?

Three layers: (1) Retrieval grounding — the chatbot can only answer from documents you've approved; (2) Confidence thresholds — low-confidence responses trigger 'I'm not sure' instead of guessing; (3) Escalation logic — billing, legal, and complex queries route to humans with full conversation context.

Ready to Get Started?

Let's discuss your project and how ai chatbots can help you achieve your goals.