How to Choose the Right AI Development Agency

An agency that answers yes to every idea is selling capacity, not judgement. The ones worth hiring will tell you when a problem does not need AI, when a smaller first phase would answer the question more cheaply, and when your data is not yet in a state that would support what you are asking for.

A prototype that works in a meeting is a low bar. Ask what they have running with real users, what broke after launch, and what monitoring told them. The answers reveal whether they have carried something past the demo stage or only up to it.

Ask specifically about evaluation — how they measure whether an assistant's answers are actually correct. Teams that have run something in production have a method. Teams that have not will describe testing it by hand.

Where does your data go, which providers process it, is it retained or used for training, how is access controlled, and what happens to it when the engagement ends. These should produce direct answers, not reassurance.

You want a defined first phase with a deliverable you can evaluate, milestone updates you do not have to chase, and decisions recorded somewhere you can read them. Open-ended discovery that never reaches a release is the most common way these projects fail.

Confirm what you receive at the end: source code, documentation, credentials, and enough written explanation for another team to continue the work. If handover is vague in the proposal, it will be vague in practice, and you will have bought a dependency rather than a product.