The Assemble Option: Who Actually Runs Your Customer-Facing AI?

Build versus buy has been an enterprise conversation for decades. AI has put a new spin on it. One platform rarely covers everything, and building from scratch takes engineers that you likely need elsewhere. Today, “assemble” has become the practical answer for customer-facing AI. But once it’s assembled, who maintains it? If changing an answer in your knowledge base takes an engineering ticket, you’ve assembled the wrong thing. This session walks through the architecture decisions that give control to the subject matter experts in your organization. Attendees will map their current operating model, and discover how easy it can be to go from spotting a wrong answer to fixing it.

Enterprises are assembling customer-facing AI from multiple vendors and models, then discovering that every content change, tuning adjustment, or correction routes back through a queue of engineers. Ownership sits with the team least equipped to judge whether an answer is right, and the people who know the answer have no way to change it. The result is an AI deployment that degrades quietly because the cost of each small fix is too high.