Build vs buy vs integrate

Every AI capability on a roadmap can be obtained three ways. Build: your team or a partner writes the application logic, prompts, evals and integrations, usually on top of commercial or open-weight models. Buy: you license a vendor product that already does the job, such as a helpdesk with an AI agent add-on. Integrate: you take a platform you already run and connect it to models and your data through a custom layer, which is often where the real value sits.

The framework scores each option against a few questions. Is this capability part of what makes your product or operation different, or is it a commodity? How much of the value depends on your own data and business rules? What does each option cost over three years, including the people needed to run it? Who owns the prompts, models and data at the end, and what happens if the vendor changes pricing or retires a model?

It is not a permanent verdict. Buying is often right for a first year and wrong once the capability becomes core, and the total cost of ownership of a bought tool can exceed a build once usage scales. The most common mistake is treating it as build versus buy only, and missing the integrate option that reuses systems already paid for.

• CTO / Head of Engineering: it prevents both extremes: rebuilding commodity features and locking core differentiation inside a vendor's roadmap.
• CFO: the three-year cost comparison, including seats, usage fees and internal staff, is what makes the decision defensible.
• Founder / CEO: it forces the question of what is strategic to own versus what is fine to rent.
• Product manager: buying speeds up the first release; knowing when to switch to build protects the product's roadmap later.

The framework exists because the default choices are usually wrong in predictable ways. Engineering teams tend to build what they could have bought, and business teams tend to buy what will cap their product's differentiation. Meanwhile, the integrate option, adding AI to a CRM or ERP you already run, is overlooked because no vendor is selling it. A written decision with costs and ownership terms makes the trade-off explicit: buying is faster but rented; building is slower but owned; integrating is usually cheapest but depends on the existing platform's APIs. The framework does not make the decision for you; it makes it visible.

• A SaaS company buying a transcription API but building the in-product copilot that uses it, because the copilot is the differentiator.
• A bank integrating a private LLM with its existing core-lending system rather than buying a fintech point solution that would take data outside the perimeter.
• A retailer integrating recommendations into an existing Shopify store rather than paying a platform subscription per order.
• A hospital buying a scheduling product but building the multilingual voice front end that patients actually interact with.
• A logistics company integrating exception-handling agents into its current TMS instead of replacing the whole platform.

ConceptA decision concept rather than a skill. Eazyware applies it in every AI strategy engagement and is willing to recommend buying or integrating when that is the honest answer; the framework is the same one we use to decide what to build ourselves.

Eazyware service that covers it: AI Strategy & Discovery. Starting prices are on the pricing page.