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Plumb AnalysisFor what AI produces Plumb BoundaryFor what AI does Talk to us →
Plumb

Keep AI true.

AI can change what your information means without making anything up.

Plumb shows you exactly what changed, and when AI reports something as settled that never was.

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AI doesn’t have to hallucinate to get it wrong.

And it still sounds completely reasonable.

  1. 01A condition disappears.
  2. 02“May” becomes “will.”
  3. 03A requirement becomes a suggestion.
  4. 04An exception gets dropped.
  5. 05A limited claim starts sounding universal.
  6. 06An explanation becomes an offer.
  7. 07A recommendation becomes a commitment.
Plumb Analysis

A refund goes out before the inspection that was meant to gate it.

Condition removed
Plumb Analysis

A possible hardware fault is reported as confirmed, and the replacement ships.

Possibility became certainty
Plumb Analysis

Supervisor approval stops being mandatory, and nobody reading it can tell.

Requirement weakened
Plumb Analysis

The one case that would have changed the answer is gone from the summary.

Exception omitted
Plumb Analysis

A rate offered to some accounts now reads as offered to all of them.

Scope widened
Plumb Boundary

AI explains the discount policy, then offers 12% to close this week.

Offer introduced
Plumb Boundary

AI suggests a service window, then books the technician for Friday.

Commitment introduced

None of this is a bad model. The source can be right, the retrieval can be right, the citation can be right and the tool call can be allowed, and the result can still be wrong in a way that costs you something.

You trust it blind, or you check it twice.

One layer underneath the AI work.

Plumb reads what AI produced against the information behind it, and what AI did against what actually became true. It tells you where the two stopped matching.

It replaces nothing. Not the model, not your workflow, not your permissions.

What changes

Every piece of AI work arrives with a record of what happened to it.

Not a sample. Not a spot check. Every analysis your AI produced and every session it ran, read back against the information behind it and against what actually happened.

Coverage stops depending on headcount

Plumb reads what AI produced and what AI did across the whole run, not the percentage a review team had time for.

What held is known to have held

The parts that carried through are marked as such. Attention goes to the parts that did not, and nowhere else.

Widening what AI does becomes a decision

You can see what it did inside the authority you already gave it, before you decide whether to give it more.

That is the difference between hoping AI held and knowing where it did not.

And you see exactly what moved.

Knowing something changed still leaves you reading it. Knowing a condition was removed tells you what to do about it, and how fast.

Not just

Changed.

But exactly what
Condition removed Scope widened Possibility became certainty Requirement weakened Exception omitted Commitment introduced Authority exceeded Meaning held

Two ways to use Plumb.

Plumb Analysis For what AI produces

Keep AI-generated analysis true to the information behind it.

AI reads across documents, email, calls, spreadsheets and system records, and turns all of it into a brief, a summary, a recommendation or a report. Somebody acts on the result.

Analysis reads that result back against everything it was built from. It shows you when AI changed something, dropped something or added something on the way, and names exactly what moved. A condition removed. A scope widened. A possibility reported as settled.

So you can rely on the analysis without doing the analysis twice.

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Plumb Boundary For what AI does

Keep AI from turning information into decisions the business never made.

AI replies, offers, schedules, approves or carries work forward on its own, across a whole session, without a person checking every step.

Boundary reads what AI did against what actually became true. It shows you when a recommendation is reported as approved, a proposal as accepted, an estimate as committed, or when AI acts past what it was ever empowered to do.

So you can give AI more room to work without quietly giving it more authority.

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Use more AI without losing control of what it says and does.

More analysis. More automation. More AI doing real work.

Without losing sight of what it was supposed to mean, or what it was actually allowed to do.

Where does AI enter your work?

Bring us a workflow where AI is producing or performing work, and whatever should have governed it. We’ll start there.

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