AI chatbots
AI Chatbot Development for Websites and Customer Support
An AI chatbot can answer common customer questions at any hour, but only if it answers from facts you approved and knows when to hand over to a person. I design and build AI chatbots for websites and support teams, using LangChain and language models, with the guardrails that keep answers accurate and on-brand.
What a business chatbot should and should not do
The most useful chatbots are narrow. They answer questions about your services, opening hours, delivery, returns and how pricing works from content you have approved, and they say so plainly when they do not know. A chatbot that guesses is a liability, because it can state a wrong price or promise something you do not offer. So the first design decision is scope: which questions it handles, which it refuses, and when it passes the conversation to a person.
A chatbot is also not an agent. A chatbot mainly converses, while an agent takes actions across tools. Many businesses need a chatbot first and a handful of simple actions later, such as capturing a lead or checking an order status. If you are unsure which you need, my guide on AI agents, chatbots and workflows explains the difference.
How I build chatbots that stay accurate
I start with your content: service pages, FAQs, policies and product information. For each question the chatbot looks up the relevant passages and answers from them instead of from memory, and it shows a safe fallback when nothing relevant is found. I build the conversation flow with LangChain, choose the language model by quality, cost, speed and your privacy needs, and test the bot against real customer questions before launch.
Guardrails matter as much as the model. I set limits on topics, block requests the bot should not handle, keep a record of conversations so you can review them, and add a clear route to a human by form, email or messaging. No chatbot is perfect, so the system is designed to fail safely.
Where chatbots fit in your business
The common uses are website enquiries, product and service questions, support triage, booking and lead capture. A chatbot can collect a visitor's name, need and contact details and pass a clean summary to your team, which saves time and stops leads going cold overnight. I also build chatbots into larger systems: my AI E-Commerce Store Manager includes a customer support agent alongside product research, SEO, listing generation and analytics for Shopify stores.
Where the chat appears depends on your channel: a widget on your website, or a messaging channel if its provider allows it. Messaging platforms have their own approval rules and costs, so I check what is feasible with you before promising a channel.
What is included in a chatbot project
Scope and conversation design
We define what the chatbot answers, what it refuses and when it hands over to a person.
Knowledge from your own content
Answers are drawn from the documents and pages you approve, with a fallback when nothing matches.
Website chat integration
A chat widget on your site, built to match your brand and work on phones.
Lead capture and human handover
Visitor details are collected and passed to your team by email, form or messaging.
Testing and guardrails
Real customer questions are used to test accuracy, with limits on topics and behaviour.
Review and improvement
Conversation logs help you see what customers ask and improve the bot over time.
How a chatbot project runs
- Define the scope. We list the questions it should answer and the ones it should never touch.
- Prepare the content. You approve the information the chatbot may use, and I structure it.
- Build and test. I build the bot and test it on real customer questions, fixing weak answers.
- Launch and review. It goes live with logging, and we review real conversations together.
Frequently asked questions
How much does an AI chatbot cost?
It depends on scope, the amount of content, the channels you need and how many conversations it handles. I quote after a short call, and I explain the running costs of the language model separately from the build.
Will the chatbot give wrong answers?
Any language model can be wrong. I reduce the risk by answering only from approved content, adding fallbacks and testing on real questions, and you can review conversations after launch.
Can the chatbot hand over to a human?
Yes. Handover is part of the design, by contact form, email or a message to your team.
Can it answer in more than one language?
Many language models handle several languages. I test the languages you need on your own content before launch.
Need a chatbot your customers can trust?
Tell me what customers ask most and where the bot should appear, and I will outline how it would work and what it would take.
Other services
- AI Agent DevelopmentAutonomous agents built with LangChain and LangGraph, with guardrails.Read more →
- AI Automation ServicesReplace repetitive manual work with reliable AI-driven pipelines.Read more →
- n8n Workflow AutomationConnect your apps and AI models with robust, documented n8n workflows.Read more →
Helpful guides
- AI Agents vs Chatbots vs Workflows: What Does Your Business Need?AI agents, chatbots and automated workflows solve different problems. Learn how each works, what it costs you in risk and effort, and how to choose.Read more →
- How to Build an AI Agent for Your BusinessA practical 7-step guide to building an AI agent for your business: choosing the job, tools, guardrails, testing and launch, without the hype.Read more →