Custom AI Chatbots & Customer Support Agents

Does the chatbot hallucinate?

We implement strict Retrieval-Augmented Generation (RAG) constraints that force the AI to answer exclusively from verified documentation.

Which information should a customer-support chatbot use?

Use maintained, approved sources that fit the task and the requester's access. Identify the source owner and refresh process so answers do not depend on outdated or unauthorized information.

What should a chatbot do when it cannot support an answer?

Acknowledge the limitation and offer a suitable handoff or source-review route. It should not invent a policy, price or account state to keep a conversation moving.

Can an AI agent take actions in business systems?

Only enable actions within agreed permissions and validation rules. Define which actions require authorization or a human checkpoint, and keep a traceable record of what actually happened.

How should a chatbot be evaluated before launch?

Test representative questions, unsupported requests, permission boundaries and handoffs. Review factual accuracy, useful completion and failure behaviour rather than relying only on a polished demonstration.

What should we prepare before discussing Custom AI Chatbots & Customer Support Agents?

Prepare support questions, approved knowledge sources, permissions, desired actions and the human escalation owner. These details help define a useful scope, identify dependencies and agree on acceptance criteria before implementation.