Who is answering, and what can they know?
A website assistant can retrieve published information and use it to answer a visitor’s question. In Sairo, that information comes from the site’s indexed pages, confirmed facts, and saved answers. Its usefulness depends on those sources and the response controls.
In staffed live chat, a person replies from the Sairo specialist desk. What that person can do still depends on their training, permissions, and access to business systems. The chat channel does not itself grant authority to approve a refund or inspect an account.
Compare responsibilities rather than labels.
The table describes both modes available in Sairo. The assistant and live specialist share one conversation, but they have different operating requirements and should set different expectations for the visitor.
| Question | AI website assistant | Sairo live chat |
|---|---|---|
| Where does the answer come from? | Configured website knowledge and approved records. | An assigned specialist using the information and systems available to them. |
| Who handles an exception? | The assistant can acknowledge a limit and request human help. | The specialist can assess it within their actual authority. |
| What determines coverage? | Service availability, source quality, and usage allowances. | Per-site enablement, assigned specialists, presence, and queue capacity. |
| What requires maintenance? | Sources, configuration, tests, and conversation review. | Team knowledge, permissions, staffing, and queue ownership. |
| What does the visitor see? | An assistant answer with the appropriate source context. | The specialist’s name and near-real-time replies in the same widget. |
Choose published answers for repeatable information.
An assistant is a useful fit when visitors repeatedly ask about public services, documentation, hours, or an established process. It can give the team a record of what was asked and reveal missing website content.
Before choosing it, test whether the important information is actually available. A website full of visual messaging but little practical detail may need content work before any source-based assistant can represent it well.
Choose a person for decisions and sensitive context.
A request can depend on information that is private, unpublished, or specific to one customer. The next step should reflect that dependency instead of encouraging the assistant to infer a decision from a loosely related page.
If your service needs an exchange with staff, enable live chat for that site, assign eligible specialists, and agree who will set themselves Available. Sairo shows availability from that setting and offers an offline team queue when nobody is there.
A combined workflow needs a clear handoff.
Use AI answers for repeatable public information and live chat for questions that need judgement, clarification, or reassurance. A visitor can request a person, and an AI escalation can place the same conversation into the site’s specialist queue.
The transcript and contact context remain available to the person responding. Agree who checks the queue, who sets themselves Available, and how offline requests are owned. Enabling the button does not replace that operating process.
Example evaluation question
“Your site explains the usual process, but my situation has an extra condition. Can someone review it?” Check whether the system explains its limits, preserves the relevant context, and leads to the actual team workflow.
Include the ongoing work in the decision.
Compare the full operating effort: maintaining sources, reviewing generated answers, staffing conversations, and completing follow-up. The cheapest visible subscription is not automatically the least expensive way to deliver the required service.
Use a pilot and the same review criteria to judge the experience. Record answer quality and completed follow-ups separately from the number of messages sent.