What are the options for an AI evaluation capability?
Three. Build it in-house from scratch, buy a vendor or open-source eval tool, or own a capability that a partner builds inside your perimeter and transfers to your team. The right answer depends on whether you need dev-time model tests or a business number you can defend, and on how much you can afford to expose.
Building your AI evaluation in-house
In-house gives you the most control and full ownership, which is exactly right in principle. The catch is cost and time. A real evaluation capability needs scarce talent, privacy-preserving data engineering, and often more than a year to mature before anyone trusts it, and it competes with every other priority your team has. Most enterprises start this, stall, and end up with a half-built harness nobody trusts.
Buying a vendor or off-the-shelf eval tool
Buying is fast, and for developer-time model testing in CI it is often the right call. The catch is what the tool is for and who runs it. Your AI vendor's built-in evals are conflicted by construction, and dev-focused eval platforms measure model and token metrics, not your business outcomes. Neither gives you a number your board can rely on, and using the vendor's own tool means exposing your criteria to the party you are judging. See vendor evals vs. owned evals.
What does it mean to own an AI evaluation capability?
Owning an AI evaluation capability means the whole evaluation, the data, the criteria, the harness, and the number it produces, runs on infrastructure you control and belongs to your team outright, rather than being rented from a vendor or produced by one. In practice a partner builds it inside your perimeter, on your data, operates it as a bridge if you want, and transfers it to your team to run and own.
This is the build, operate, transfer model. The point is not that you rent a capability forever. It is that you end up owning it, with the know-how transferred, on infrastructure you control. It is the only one of the three that gives you a trustworthy number quickly and keeps your criteria private.
Build vs. buy vs. own, side by side
| Build in-house | Buy a tool | Own (build, operate, transfer) | |
|---|---|---|---|
| Time to a trusted number | Over a year, typically | Fast, but not a business number | Weeks to a first baseline |
| Ownership | Full | None; you rent the platform | Full, transferred to you |
| Conflict of interest | None | High if it is the AI vendor's tool | None; the partner sells no AI |
| Criteria stay private | Yes | Often no | Yes, invisible to your vendors |
| Talent required from you | A scarce, dedicated team | Low | Low; the know-how is transferred |
So which should you choose?
If you already have a spare, world-class privacy and eval team and two years, build. If you only need model-level tests in your pipeline, buy a dev tool. If you need a business number you can trust, defend, and keep private, and you want to own it without the multi-year build, own it. That is the capability PrivateEval delivers, and what private AI evaluation is covers the model in full.