How to choose an AI platform for customer service

Start with a need and an observable outcome

Define which inquiry you want to improve and what should happen at the end. Providing requirements, directing someone to a channel and completing a transaction are different outcomes. Spelling out that difference avoids comparing demos that promise different things.

Ask for the test to include representative examples from your operation, and make it clear which capabilities are available, which depend on an integration and which are out of scope.

Review knowledge and the limits of the conversation

Ask where the agent gets its information, who approves it and how it is updated. Try a question with no answer in the sources: the expected behavior should be defined beforehand, including when to ask for clarification or hand off.

A convincing voice does not prove accuracy. Check whether the agent preserves the meaning of the rules, recognizes missing information and avoids claiming it completed an action it did not carry out.

Check continuity with people and systems

Ask for an explanation of the path to an operator and of the information the operator actually receives. Verify the dependencies on telephony and on the company's systems. An announced integration must translate into concrete actions, data and responsibilities.

• What can the agent resolve and what must it hand off?
• What information comes with the handoff and where can it be checked?
• What happens if an external system does not respond?
• Who approves changes to knowledge and instructions?
• How are access and the handling of information controlled?

Ask for evidence and comparable commercial terms

Agree on how errors and results will be reviewed, what will count as a resolution and how changes will be logged. Compare equivalent periods and avoid attributing an improvement to the AI if the process or the sample of inquiries changed at the same time.

The commercial proposal should clarify scope, integrations, expected usage, support and implementation terms. Do not extrapolate the result of a demo to the whole operation without a representative evaluation.

How to evaluate MEHI with this guide

MEHI combines AI voice agents, institutional knowledge and service oversight. A demo lets you review your process and raise these questions with a concrete scope. Whether the solution is a good fit depends on your organization's needs and conditions.