There’s a crucial step between “the idea is feasible” and “roll it out to everyone”: a pilot. An AI pilot program puts a real, working solution in front of a limited set of actual users to prove it delivers value in practice — before you commit to scale. This page explains how dgm runs one. (dgm implements osFoundry, a separate company’s platform — we are not osFoundry.)

What a pilot proves that a POC can’t

A proof of concept answers a technical question: can this work? A pilot answers a human and operational one: does this actually help our people, in their real work? That’s a different and equally important test, because plenty of technically feasible AI fails on contact with real users — it doesn’t fit the workflow, people don’t trust it, or the value that looked obvious in a demo evaporates in practice.

A pilot surfaces all of that while the stakes are still low: limited users, limited scope, real conditions. You learn whether the solution earns adoption before you bet the whole organization on it.

The discipline that makes pilots work: a clear exit

The biggest risk with pilots isn’t failure — it’s drift. A pilot with no defined endpoint becomes “pilot purgatory,” running indefinitely while everyone waits for someone to decide. The fix is simple and non-negotiable: define success metrics and a scale-or-stop decision before the pilot begins. When the pilot ends, the data says one of three things — scale it, adjust and re-test, or stop — and you act. dgm sets those criteria up front precisely so the pilot produces a decision, not a limbo.

What dgm’s pilot includes

A dgm pilot is a genuine, scoped deployment:

  • A real solution — built and integrated for the pilot scope, not a mockup.
  • Real users — a defined group using it in their actual work.
  • Clear metrics — agreed before launch, tracked throughout.
  • Support and iteration — fixing friction quickly so the pilot tests the solution fairly.
  • A decision — a documented scale-or-stop recommendation at the end.

Because dgm builds on a model-agnostic, integration-first platform, a successful pilot scales into full implementation without a rebuild — the pilot is the first phase of the real thing, not throwaway work.

What it costs

A pilot runs within dgm’s $3,999/month integration engagement, scoped up front, following the one-time $399 assessment and roadmap. No per-seat fees. The phased structure means you’re proving value at limited scale before paying to scale it everywhere.

How dgm helps

dgm runs disciplined AI pilots for US businesses — real solutions, real users, clear metrics, and a defined scale-or-stop decision — so the move to full rollout rests on evidence of value in practice. If you’d rather explore the platform yourself first, you can go straight to osFoundry; if you want a pilot that ends in a real decision, that’s where dgm comes in.