Question 1: Can you show me a production system you built, not a demo?
Any competent AI development company can build an impressive demo. What separates capable partners from those who will disappear after the prototype is whether they have taken systems all the way to production and kept them running.
Ask for a specific example. Ask what the system does, how long it has been live, and what challenges they encountered post-deployment. The answer tells you everything about their actual capability.
Question 2: How do you handle data quality problems?
Data quality issues are present in almost every real AI project. A company that tells you data is not a concern, or that they will handle it as it comes up, has not shipped enough real projects to know what they are getting into.
A good answer describes a structured data audit process, a clear approach to handling common data quality issues, and a realistic expectation about what the data preparation phase will involve.
Question 3: What does your post-launch process look like?
Too many AI development companies disappear after the code is delivered. AI systems require monitoring, maintenance, and iteration. If the partner has no structured post-launch process, you will be left managing a system you do not fully understand.
"The partner you want is one who is as focused on what happens after launch as on what they build before it."
Question 4: How do you measure success?
The answer should involve business outcomes, not just technical metrics. If the only metrics they mention are model accuracy and inference speed, they are thinking about the technology, not your business.
The right answer connects the technical deliverable to a measurable business outcome and includes a plan for tracking it.
Question 5: Who specifically will be working on my project?
Many technology companies sell on the credentials of their founders and then staff projects with junior team members. Ask specifically who will be on the project, what their backgrounds are, and who will have final sign-off on architectural decisions.
At Agintex, every project is staffed by specialists with hands-on experience in the relevant domain. The person who scopes the project is the person accountable for delivering it.
About author
Marcus leads AI strategy and client advisory at Agintex, helping businesses translate complex AI opportunities into clear, executable plans. He writes about AI adoption, technology leadership, and the decisions that separate companies that scale from those that stall.

Marcus Reid
Head of Strategy
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