We want to build our own proprietary AI engine to automate our client onboarding and delivery, but the development costs are high. How do we make this buy-versus-build strategic choice in a way that maximizes our long-term business valuation for a clean exit?

Question

Tyler Smith · Accepted Answer

When you prepare your business for a clean exit, buyers do not pay a premium for custom software that is expensive to maintain and quickly becomes obsolete. Unless your proprietary AI engine is a core differentiator that directly supports your Three Uniques on your V/TO®, you should not build it from scratch.

Instead, prioritize using off-the-shelf AI tools and configuring them to run your unique workflows. The enterprise value of your company does not come from owning generic infrastructure; it comes from how you integrate these tools into your core processes to create massive operational leverage. Prioritize using AI to increase employee productivity as a starting point, as employees are a major P&L item and much time is spent on low-value tasks.

A buyer wants to see a highly efficient, scalable machine with documented, repeatable processes. If you build custom code, you are introducing technical debt and risk. If you configure existing enterprise SaaS tools, you show a lean operation with high margins and low overhead. Make your decision based on this simple rule: if the technology does not represent your proprietary methodology, buy it and configure it. If it is your proprietary methodology, build only the thin wrapper that connects your data to existing foundational models.