This webinar takes a different approach: instead of talking about chatbots in theory, we actually make a chatbot together — live, from scratch, using the Crafter.ai platform. This is a hands-on session for anyone who wants to understand how AI chatbots are really built.
What We Build in This Webinar
In the session, we build a complete, functional AI chatbot for a fictional e-commerce company, covering:
- Defining the chatbot's purpose and scope — what it will and won't do
- Setting up the knowledge base — uploading product information, FAQs, and policies
- Designing conversation flows — using Crafter.ai's visual conversation designer
- Configuring escalation rules — when to hand off to a human agent
- Testing and refining — using the built-in test console
- Deployment — embedding the chatbot on a website and connecting to WhatsApp
The entire process is completed live during the webinar, without writing a single line of code.
Step 1: Defining Chatbot Purpose and Scope
Before touching any tool, the most important step is defining what the chatbot is for. The webinar shows how to:
- Map the top 20 most frequent customer questions
- Categorise them by complexity (automatable vs. requires human)
- Define the chatbot's "success criteria" — what counts as a successful interaction
- Set boundaries: what the chatbot will say when asked something outside its scope
This planning stage is often skipped by companies rushing to deploy, and it's one of the main reasons chatbots fail. The webinar shows exactly how to do it right.
Step 2: Building the Knowledge Base
The chatbot's intelligence comes from its knowledge base — the structured information it uses to answer questions. In the live build, we:
- Upload product catalogue information as a PDF
- Add an FAQ document with common questions and answers
- Configure the return and shipping policy pages
- Set up the knowledge base chunking and indexing for optimal retrieval
Crafter.ai's RAG (Retrieval-Augmented Generation) system automatically makes this information available to the AI, ensuring accurate, grounded answers rather than AI hallucinations.
Step 3: Designing Conversation Flows
The visual conversation designer is at the heart of Crafter.ai. The webinar demonstrates:
- How to create a welcome message and initial menu
- Building a flow for the most common request type (order status check)
- Adding conditional logic based on customer responses
- Configuring rich media responses (images, buttons, carousels)
- Setting up multi-turn conversations that remember context
The no-code interface means business users — not just developers — can design and modify conversation flows.
Step 4: Testing and Iteration
Before deployment, the webinar shows the testing and iteration process:
- Using the built-in test console to simulate customer conversations
- Testing edge cases and unexpected inputs
- Reviewing conversation logs to identify gaps
- Making rapid iterations based on test results
Step 5: Deployment
Finally, the webinar covers deployment options:
- Website embedding: copy-paste the embed code, chatbot is live in minutes
- WhatsApp Business: connect via the WhatsApp Business API for messaging channel deployment
- Custom branding: configure colours, fonts, and logo to match brand guidelines
FAQ: Building a Chatbot with Crafter.ai
Do I need technical skills to build a chatbot on Crafter.ai? No. The platform is designed for business users. You need to understand your business, your customers, and your content — not programming. The webinar proves this by building a complete chatbot live with zero code.
How long does it take to build a production-ready chatbot? A basic chatbot covering your top 20 use cases can be built in a day. A fully-featured, integrated production chatbot typically takes 2-4 weeks, including integration with your CRM and testing with real users.
What happens when the chatbot doesn't know the answer? The webinar shows how to configure graceful fallbacks — honest responses when the chatbot doesn't have the information, plus automatic escalation to human agents for questions outside the chatbot's scope.