How to Choose an AI Development Company: A Buyer's Checklist
Nearly everything you evaluate is easy to manufacture Case studies, client logos, team biographies, framework lists, a tidy portfolio page. All of it can be assembled by a firm that has never put a model into production or had to explain why one stopped working. The signals that cannot be manufactured require having failed at something. A vendor who has watched a project stall knows where projects stall, and that shows up as specific, uncomfortable answers. A vendor who has only closed deals produces smooth answers with no edges. Five questions separate the two, and none are about model architecture. What would make you decline this work? Ask it directly in the first conversation. A vendor with a real answer names conditions: not enough labelled outcomes, no reliable way to measure whether it worked, no capacity to act on predictions, an unsettled regulatory position, or data that cannot be reconstructed as it stood when decisions were made. Each of those answers come...