Connecting a model to a chat can generate answers. A service system also needs accessible context, business rules and a way to intervene when something goes off script.
From demo to operation
A demo answers a question. In operation, the system sustains many conversations, records context, recognizes its limits, escalates to a person and lets the team review what happened. That's where it delivers value.
What a makeshift chatbot is missing
- Up-to-date business knowledge.
- A clear handoff to a person.
- Conversation records and follow-up.
- Rules about what it should avoid answering.
- Metrics to improve and detect errors.
The actual project
Design a conversational system with inputs, outputs, data, boundaries, owners and controlled learning.
Where to start
Choose three or four common cases. Define the data AI needs, which answers are off-limits, when to hand off and how to measure whether it helped. Think about scaling after that.