Plumb shows you where meaning changed between your source and your AI output, before anyone makes a decision on it.
When AI summarises a source, it compresses it. Conditions become conclusions. Uncertainty becomes clarity.
Most of the time that's fine. But in workflows where the output drives a decision: what you tell the client, which vendor you choose, what risk you flag, what you sign. The handling matters.
The client email said: "we're moving along quickly but we have some slight changes we need to work through before we can confirm the timeline."
The brief said: "the client is progressing well and working through a few minor adjustments."
Nothing is missing. Every idea made it in. But the condition on the timeline is gone. The uncertainty about confirmation is gone. You read the brief at 8am and walk into the call thinking the client is fine.
The source said they couldn't confirm the timeline yet. The brief said things are progressing. Same words. Different decision. And no signal that anything changed.
Today, that shift is invisible. Decisions get made on it anyway. Plumb makes it visible before anyone acts on it.
The source took a position. The output hedged it. A firm obligation became a general expectation. A clear risk became a passing note. The content is there. The force of it isn't.
The source was measured. The output drew a conclusion it didn't earn. The recommendation sounds grounded. The source material doesn't actually support it at that strength.
A condition. A constraint. A client signal. A risk that mattered. Not reframed. Just gone. The output has a beginning, a middle, and an end. It feels complete. It isn't.
The AI connected dots that don't exist in the source. The output sounds supported. It isn't traceable to anything your source actually said.
The workflows where AI is saving your team the most time are the same workflows where a decision gets made on whatever the output said.
A vendor sends a revised contract. AI produces a comparison summary of what changed between version one and version two. The summary lists the changes accurately. One obligation that was tightened in version two is described using the same language as version one.
The team negotiates on version one terms. Version two had already changed them. The summary didn't carry the difference.
A 60-page report gets fed to AI. The summary comes back in minutes, tight, readable, looks like it covered everything. Two of the five key findings in the source didn't make it in. One that did was reframed as a conclusion the report never actually drew.
The summary gets used. Nobody goes back to the report. That's the whole point of a summary.
An analyst uses AI to summarize three target companies from a stack of financials and market reports. The memo reads well. One company's revenue figure was restated in a later filing. The AI used the earlier number. The restatement never made it into the output.
The memo goes to the investment committee. The number was wrong. The source had the right one.
AI brings you information faster. Plumb shows you whether the information it brought you is faithful to what the source actually said, so the decision you make is made on the full picture, not the processed version.
Structured workflows or freeform documents: reports, transcripts, emails, RFP responses, research notes. Whatever your AI was working from, and whatever it produced.
Not whether the output sounds right. Whether it stayed true to what the source actually said — and precisely where it didn't.
Not a summary. Not a score. Not a guess. A precise account of what changed, before anyone acts on it. You don't have to trust the output. You know what it carried and what it changed.
No new workflow. No new tool your team needs to learn. Plumb reads your source and your output and reports back.
Structured workflows or freeform documents: reports, RFP responses, transcripts, client emails, research notes. Whatever your AI was supposed to be working with.
→The brief, evaluation, summary, or recommendation your AI produced. Plumb reads it against the source. Not against what AI outputs usually look like, but against what your source actually said.
→A precise account of where the meaning held, where it shifted, what didn't make it through, and what was added. Before the decision. Before it goes anywhere.
One API call at the end of your existing workflow. Plumb connects to what you already run. Your team doesn't change how they work. They just know whether the decision they're about to make is based on what the source actually said.
Plumb is built for organisations already using AI to produce work that drives decisions — where the gap between what the source meant and what the output said has real consequences for what happens next.
The workflows vary. The underlying problem doesn't.
You're reading AI-generated outputs and making calls based on them. What you recommend, what you approve, what you send: it all follows from what the output told you.
Plumb makes sure what the output told you is what the source actually said. So you don't have to trust the brief is right. You know what it carried.
You put AI in the process to make the team faster. Plumb makes sure faster didn't mean flatter. That the outputs coming out of your workflow are carrying the full meaning of the sources that went in.
One integration at the tail end of what you already run.
The demo takes 15 minutes. We'll run Plumb against a real AI output, yours or one of ours, and show you exactly what it finds. No deck. No pitch. Just the product working.
If you've sent an AI output in the last month that you weren't completely certain about, that's the one to bring.