A compelling demonstration shows what a tool can do under selected conditions. A good project conversation also explains how it will behave with your information, your team, and the exceptions that appear in ordinary work.
Use these questions with any prospective provider—including The Rescue Team, which publishes this guide. You do not need to know the technical vocabulary. You need answers specific enough to compare proposals and understand what you are buying.
01. What exact business problem are we solving?
Ask for a description of the current workflow, the proposed change, and the people affected. “Add AI to operations” is not a useful scope. “Help staff produce a reviewable summary of an incoming request” is much easier to evaluate.
Also ask which simpler alternatives were considered. Sometimes a better form, clearer documentation, or an existing software feature is enough. A provider should be able to explain why the proposed approach fits the task.
02. What information will the system receive?
Identify the documents, customer details, and other information needed for the work. Ask where information is sent, which other services process it, who can access it, and how retention and deletion work under the proposed configuration.
A general statement that a tool is “secure” is not a substitute for a concrete explanation. If sensitive or regulated information is involved, include the appropriate security, legal, or compliance reviewer before work begins.
03. What happens when it gets something wrong?
Ask which outputs require human approval and which actions, if any, happen automatically. Discuss missing information, unsupported questions, service outages, and instructions that conflict with your business rules.
Request a demonstration of the fallback, not just the ideal case. Your team should know how to pause the workflow, reach the original information, and continue working without the AI component.
04. How will we measure success?
Agree on the current baseline and how you will measure the pilot. Include correction time, missed cases, and the effort required from your team—not just the speed of an initial response.
Write down what would justify expansion, what would require a change, and what would cause you to stop. Treat early results as evidence from the tested workflow, not a guarantee that the same result will apply across your business.
05. What will we own and control?
Clarify ownership of accounts, domains, documents, custom work, and configuration. Ask whether your business will hold administrator access and what can be exported if you change providers.
Request that ownership and exit arrangements be written into the agreement. Know which parts are yours, which are licensed, and which depend on a third-party service continuing to be available.
06. What does the full ongoing cost include?
Separate implementation fees from subscriptions, usage charges, maintenance, and support. Ask what happens if usage grows or a third-party price changes. Make sure you know whether training, revisions, and troubleshooting are included.
For a useful comparison, give each provider the same realistic usage assumptions. A low setup price can be misleading when the recurring obligations are unclear.
07. Who supports the system after launch?
Ask who responds to a problem, through which channel, and on what schedule. Identify who maintains business instructions, reviews errors, manages permissions, and updates integrations when connected tools change.
Request a plain-language handoff that your staff can use. It should explain ordinary operation, escalation, recovery, and the boundaries of what the system is intended to do.
A strong proposal explains the boundaries as clearly as the benefits.
Bring one real workflow to the conversation.
For a St. Louis business owner, the most useful preparation is a concrete example of repetitive work, a description of who does it, and an estimate of how often it happens. Remove private customer information before sharing an example with an unapproved provider.
That gives the conversation a practical center: not what AI might do someday, but what would make this piece of work better.