Article & News

Businesses planning an AI support assistant usually focus on choosing the tool. The bigger factor is the knowledge base the tool will read. An assistant answering from outdated, contradictory or incomplete articles will repeat those problems confidently to every customer who asks. Preparing a knowledge base for AI is mostly editorial work, and it improves the support experience for human agents and customers reading the articles directly as well. Find the contradictions Knowledge bases accumulate conflicting articles over the years: an old refund policy alongside a new one, two different sets of setup instructions, prices that changed in one place

Users are used to software that responds almost instantly. Language model calls routinely take several seconds, and chained calls can take much longer. The result is an AI feature that works well and still feels broken, because people give up before the answer arrives. Reducing AI latency comes down to two separate jobs: making the system genuinely faster where possible, and making the unavoidable waits feel shorter. Measure where the time goes Before optimising anything, break a typical request into its parts: retrieving context, building the prompt, waiting for the model, processing the output, and any follow-up calls. Record how