AI build vs buy,
decided with the reasoning shown.
Most AI does not need to be built. We make the build-versus-buy call on each of your use cases: where an off-the-shelf product wins, where a custom build earns its cost, and where the honest answer is not yet. The reasoning is written down, so the decision is yours to defend.
Why most AI should be bought
For a large share of use cases, an existing product already solves the problem better and cheaper than anything custom, and it comes maintained. Our default recommendation is to buy, and we will say so even though we are the ones who could build it.
Building is worth it when the use case is core to your business, when no product fits your data or workflow, or when owning the system is the point. We name which of those applies, or that none does.
What a build actually costs to own
A build is not just the first version. It is the evals, the guardrails, the monitoring, the security review, and the team to keep it running for years. We cost the whole lifecycle, not just the demo, so buy-versus-build is compared honestly.
We have seen custom builds that should have been a subscription, and subscriptions stretched to do a job that needed a build. Naming the reason for each call is most of the value.
A decision, per use case
You leave with a build / buy / skip recommendation on each use case, the reasoning behind it, and, where you buy, the shortlist of options worth evaluating. The recommendation is vendor-portable: nothing locks you into building with us.
This is one decision the full Audit & Consulting engagement makes across your whole portfolio, alongside use-case prioritization and EU AI Act classification.
Common questions.
Direct answers to the questions we get asked the most. If yours isn't covered, write to the team.
Build, buy, or skip? Decide it with the reasoning shown.
Tell us the use cases on the table. We come back with a build / buy / skip call on each, and why.