Before choosing a chatbot, know that there are two main approaches, each suited to different situations. The wrong choice creates either a poor user experience or unnecessary cost.
Rule-based chatbots
These follow fixed, button-driven paths. They are fully predictable and never give an off-topic answer, but they can’t handle anything outside their defined paths and become tiresome for varied questions.
LLM-powered assistants
These understand natural language and can answer varied questions. Built on company knowledge (RAG), their answers are accurate and reliable. In return, good design and clear boundaries matter more.
Quick comparison
| Feature | Rule-based | LLM-powered |
|---|---|---|
| Natural-language understanding | Limited | High |
| Predictability | Very high | High with good design |
| Coverage of varied questions | Low | High |
| Cost per answer | Almost zero | Low, depends on model |
| Best for | Simple, fixed flows | Support and varied questions |
Which should you choose?
- If questions are simple and limited: rule-based is enough.
- If questions are varied and need company knowledge: an LLM assistant.
- Often a hybrid works best: button menus for common tasks and an LLM for open questions.
Frequently asked questions
Can both approaches be used together?
Yes. A hybrid is common: simple paths are rule-based and open questions are answered by a language model.
Which approach is cheaper?
Rule-based bots are usually simpler, but if questions are varied, their maintenance cost and poor experience can end up costing more.