Comparison

Build vs buy for AI agents

Buy when your workflow looks like everyone else in your industry and a vendor already sells for it. Build when the workflow is specific to how your business works, when the data lives in systems no vendor integrates with, or when the process is the thing you compete on. Most companies should buy more than they think and build the one or two things that are actually theirs.

The options

Buy a vendor product

A packaged AI product for a defined job: support deflection, meeting notes, sales outreach, document review.

Best for
  • Workflows that are essentially the same across every company.
  • Getting value in weeks without engineering capacity.
  • Cases where the vendor already integrates with the systems you run.
  • Testing whether AI helps at all before committing to a build.
Avoid when
  • Your process differs from the vendor assumptions in ways that matter.
  • The data it needs sits somewhere the vendor cannot reach.
  • Per-seat pricing scales past what a build would cost within a year or two.
  • The workflow is a genuine competitive differentiator.

Build custom

An agent built for your workflow, running in your cloud, calling your systems, owned by you.

Best for
  • A workflow shaped by how your business specifically operates.
  • Data in internal systems, legacy databases, or niche vendor tools.
  • Compliance requirements that dictate where data can live and be processed.
  • Volumes where per-seat or per-action vendor pricing gets painful.
Avoid when
  • A vendor product covers 80 percent and the last 20 percent does not matter.
  • Nobody can maintain it and you do not want an ongoing relationship.
  • The process is not settled enough to encode.
  • It is being built because building is more interesting than buying.

Buy the platform, build the workflow

Use model APIs and existing infrastructure, build only the logic specific to you. The usual middle answer.

Best for
  • Almost everyone. Nobody should be training their own model for this.
  • Keeping the specific logic yours while the commodity parts stay vendor-supplied.
  • Switching models later without rebuilding the workflow.
Avoid when
  • A complete vendor product genuinely covers the whole job.

How to decide

If this is truePick
Every company in your industry does this the same wayBuy
The data lives in a system no vendor integrates withBuild
This process is how you win businessBuild
You need something working next monthBuy, then reassess
Per-seat cost exceeds a build inside two yearsModel both properly

What we actually think

We build custom systems and will still tell you to buy when a product covers your case. A build that duplicates something you could have licensed is a bad outcome for you and an awkward reference for us. The question worth asking is not whether AI can do this, but whether the way you do it is different enough to be worth encoding.

Common questions

How do we compare costs honestly?

Include the parts people leave out. For buying: per-seat cost at your headcount in three years, integration work, and the cost of the workflow you change to fit the tool. For building: the build, model usage, and ongoing maintenance, which is real and continuous.

What if we buy and outgrow it?

That is a good outcome, not a failure. You will have learned exactly what you need, which makes the eventual build cheaper and better scoped. Check the exit terms before signing: whether you can export your data and history matters more than most people check.

Should we ever train our own model?

For almost every small and mid-sized business, no. Fine-tuning is occasionally worth it for a narrow, high-volume, well-defined task. Training from scratch is not a small-business activity, and vendors suggesting otherwise are selling something.

Next step

Still not sure which fits your case?

Describe the workflow and the constraints. You will get a straight recommendation, including the one where you do not hire us.