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What Should You Look for in an AI Development Company?
The right technology decision starts long before development begins. Practical insight on building mobile apps, AI products, custom software and cloud platforms — aimed at the questions businesses need answered before they invest.
Most of the difficulty in an AI project is not the model. It is the data around it, the evaluation that tells you whether it is working, and the plumbing that puts it in front of a user without leaking anything. A firm that talks only about models has not shipped many.
Ask how they handle your data: where it lives, what leaves your environment, what a provider retains, and how they would run the same product if you were subject to HIPAA or GDPR. If the answer is vague, that is the answer.
Ask how they know it works. Serious AI teams have evaluation sets, regression tests on prompts, and a way to measure quality that does not depend on someone eyeballing outputs. Without that, every change to the system is a guess.
Then ask about the boring half — retrieval, caching, rate limits, cost per request at ten times your current volume, and what happens when the provider deprecates a model. That is where AI products actually live or die.
