How to Evaluate an AI Development Company: 7 Questions That Separate Builders from Demos

Every agency added "AI" to its homepage in the last two years, and demos are cheap: a wrapper around a model API can look magical in a 30-minute call. Production is where AI projects die. If you are evaluating an AI development company, these seven questions expose the difference.

1. "How do you evaluate quality before shipping changes?"

The only acceptable answer involves an evaluation suite: a versioned set of real test cases the system must pass before any prompt, model, or retrieval change goes live. Vendors who answer "we test it manually" will ship regressions to your customers.

2. "What happens when the model is wrong?"

Listen for guardrails, confidence thresholds, grounded citations, and human-in-the-loop escalation. An honest vendor designs for failure; a demo-seller pretends it will not happen.

3. "Which models do you use, and how locked in are we?"

Good architecture keeps the model layer swappable across OpenAI, Anthropic, Google, and open-source options, because pricing and capability shift quarterly. If the answer is a single vendor's name, you are buying their lock-in.

4. "What will this cost per month at our volume?"

Token economics sink projects after launch. A serious vendor models inference costs at your volume and designs caching, routing, and smaller-model fallbacks accordingly.

5. "Have you run AI in production for your own products?"

The patterns that matter — retries, cost controls, evaluation, drift monitoring — are learned by operating systems, not reading about them. Ask what they run themselves and for how long. (We run our own AI agents platform in production; it is the accelerator behind most of our client builds.)

6. "How do you handle our data?"

Expect concrete answers on data residency, whether your data trains anyone's models (it should not), PII redaction in pipelines, and access controls — not a generic security page.

7. "What does the first month look like?"

Strong vendors propose a scoped pilot with success criteria you agree on in advance, not a six-month contract for a platform you have not seen working on your data. For integration projects, that pilot usually looks like our AI integration engagement: two to four weeks, measured against agreed criteria.

An honest vendor designs for failure; a demo-seller pretends it will not happen.

— Rocket Systems AI team

We wrote these questions because they are the ones we want to be asked. Our AI development team runs its own agents platform in production and starts every engagement with a measured 2–4 week pilot — book a call and put us through the list.