How do you build an AI chatbot?

To build an AI chatbot, define the questions it should handle, collect the knowledge it will answer from, choose a platform or language model, connect it to the systems it needs, write instructions and guardrails, test it on real past conversations, and launch on one channel with a clear handoff to humans before expanding.

The seven steps

  1. Pick the use cases. Start with the 3 to 5 most common, well-documented questions.
  2. Gather knowledge. Help articles, policies, product docs and resolved tickets. Remove outdated content.
  3. Choose how to build. Options range from no-code chatbot builders to agent platforms to custom code on a model API.
  4. Connect systems. If the bot needs to check orders or accounts, connect those systems with read and write permissions scoped to what the bot should do.
  5. Write instructions and guardrails. Tone, topics to avoid, when to escalate, and actions that need approval.
  6. Test on real conversations. Replay a set of past tickets and grade the answers. Fix knowledge gaps.
  7. Launch gradually. Start on one channel or a share of traffic, watch transcripts daily, then expand.

Build options compared

OptionBest forTrade-off
No-code chatbot builderSimple FAQsLimited actions and reasoning
Agent platformSupport teams that need actions and governancePlatform cost
Custom code on an LLM APIUnique workflows with engineering capacityYou own security, evals and upkeep

What makes it good

Grounded answers with sources, access to real account data, and a fast handoff when the bot isn’t sure. Avoid launching a bot that can only say “I don’t know” or loops customers.

Frequently Asked Questions

Follow us

Language

Status

All Systems Operational

Certified Secure

secure