Build vs. Buy

"Should we build it or buy it?" is the wrong question. It assumes AI is a single thing you either purchase whole or construct from scratch. It isn't. AI capability comes in layers — and the right answer is almost always to buy some layers and build others.

Think in layers, not in one decision

A useful AI capability stacks roughly like this: the model, the tooling around it, the integration into your systems, and the workflow logic that makes it valuable to your business. You should buy the layers that are commoditised and build only the layer that is genuinely yours:

• The model — buy. Foundation models are a commodity; training your own is rarely justified in the mid-market.
• The tooling — usually buy. Mature SaaS and platforms cover most needs.
• The integration — it depends. Off-the-shelf where connectors exist; custom where your stack is unusual.
• The workflow logic — build. This is your process, your edge, the part no vendor can sell you.

The decision moves with your maturity

The line between buy and build shifts with three variables: organisation size, data maturity, and how much the use case is a genuine differentiator versus table stakes. A 60-person firm automating invoices should buy almost everything. A 2,000-person firm building a proprietary classification engine that is its competitive advantage should build the layer that matters and buy the rest.

This is the logic behind PrimeStream™'s four tiers — from SaaS configuration, to no-code automation, to low-code, to fully custom development. The tier is matched to the complexity of the solution and the maturity of the organisation. No over-engineering. No underdelivering.

The honest version of this analysis is hard to get from anyone with something to sell. An independent assessment — with every vendor relationship disclosed in full — is the only way to get a recommendation that is actually the recommendation.