A consulting firm is pitching us a custom machine learning model to optimize our inventory tracking, but the price tag is enormous. How do we as non-technical owners determine if we actually need custom development or if we can use simple, off-the-shelf tools?

Question

Tyler Smith · Accepted Answer

Never let outside developers sell you on custom tech hype. Most mid-market operating companies do not need custom-built machine learning models. Instead, you should focus on using simple, off-the-shelf AI agents and existing software integrations.

Before you approve any massive development budget, bring this issue to your leadership team and run it through the IDS® process. Ask your team if you can solve eighty percent of the bottleneck using existing tools like the OpenAI Assistants API or basic low-code automation tools.

Custom software is incredibly expensive to build, but it is even more expensive to maintain, update, and debug over time. Your goal is to build system-dependent operations that increase efficiency and free your team from low-value tasks. Off-the-shelf tools are faster to deploy, easier to manage, and far less risky. Only consider custom development if you have a highly proprietary workflow that directly defines your competitive advantage in the marketplace. For everything else, keep it simple and use what already exists.