AI Chatbot Development
Custom AI chatbot development builds an assistant trained on your own content — product docs, policies and past tickets — so it answers customer questions accurately around the clock. We deploy to your website, WhatsApp or Slack, with human handover when the bot reaches its limits.
The chatbots people dislike are the scripted decision-tree kind that trap you in a menu. A modern assistant grounded in your actual documentation is a different product: it understands the question as asked and answers from your real content.
The engineering that matters is deciding what the bot must never guess about, when it should escalate to a person, and how you review what it has been telling customers. We build all three in from the start rather than bolting them on after a complaint.
What's Included
Included in every AI Chatbots engagement.
Assistant trained on your data
The bot answers from your documentation, policies and past tickets, with citations back to the source material.
Website & WhatsApp deployment
A chat widget matched to your branding, plus WhatsApp, Messenger or Slack where your customers already are.
Human handover
Clean escalation to a real person with full conversation context when confidence is low or the customer asks.
Lead capture & qualification
Qualifying questions during the conversation, with qualified leads pushed straight into your CRM.
Conversation analytics
A dashboard of what customers actually ask, which questions the bot handles well, and where it struggles.
Content update workflow
A simple process for refreshing the bot's knowledge when your documentation or pricing changes.
How It Works
- 1
Define scope
We agree what the bot handles, what it must always escalate, and the topics it should refuse outright.
- 2
Ingest your content
Documentation, FAQs and ticket history are processed into a searchable knowledge base for grounded answers.
- 3
Build & test
The assistant is tested against real historical questions and reviewed with your team before customers see it.
- 4
Launch & improve
Deployment followed by review of real conversations, closing gaps as genuine customer questions expose them.
Technologies We Use
- OpenAI
- Claude
- RAG
- pgvector
- WhatsApp Business API
- Node.js
- n8n
Frequently Asked Questions
How is an AI chatbot different from a rule-based one?
A rule-based bot follows a fixed decision tree and fails as soon as someone phrases things unexpectedly. An AI chatbot interprets the question in natural language and answers from your knowledge base, so it handles phrasing it has never seen. It also needs grounding and guardrails, which a decision tree does not.
Can the chatbot hand over to a human?
Yes, and it should. Handover triggers on low confidence, explicit requests, or sensitive topics such as refunds and complaints. The agent receives the full conversation history so the customer does not have to repeat themselves.
How do you keep the bot from saying something wrong?
The bot answers only from your approved content rather than general world knowledge, and returns citations. Sensitive topics are blocked from generation entirely and routed to a human, and conversation logs are reviewable so anything off can be corrected quickly.
How long does it take to launch a chatbot?
A support assistant grounded in existing documentation typically takes 2 to 4 weeks. More involved builds with CRM integration, WhatsApp delivery and lead qualification usually run 4 to 8 weeks.
Ready to start your project?
Tell us what you're building and you'll get a clear scope, timeline and fixed quote — at no cost.