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Monitor

Every object and field,
documented and scored

One page per object, one per field, one search across all of them. Reliable context for humans and AI, with missing descriptions flagged.

What changes when nobody has to guess

Before Plauti

  • Fields with no description pile up into clutter and confusion.
  • “Is this safe to delete?” No one knows, so nothing gets deleted.
  • An AI rollout goes live, then fails on data nobody checked first.

WithPlauti

  • Every field says what it is, or shows the gap where it doesn't.
  • Fill rate per field, so you can spot the test and obsolete ones.
  • The descriptions an AI would read are on screen, gaps included.

What the library holds

Which objects are in the library, how the last analysis job went, and a route into every object and field.

  • A health snapshot of the library

    How many objects are onboarded, which job ran last, and whether it completed.

  • How much you have collected

    How much analysis and metadata has built up, and where the space goes.

  • Two routes to any field

    Drill down from the index, or type part of a name and skip the hierarchy.

Every question about a field, on one screen

  • What's covered, and when it last ran

    How many objects are in the library, which analysis ran last and whether it completed, plus a field-type breakdown across all of them.

  • The field count nobody guesses right

    Every object in one sortable table, with the number of fields found on it. That number is usually the shock.

  • Open an object, see all of it

    Record counts, and every field with two types: the exact one your CRM reports, and the normalized one used for analysis.

  • Definition and health, on one page

    Its definition on one tab, its results on the other.

  • Find a field without drilling down

    Type “source” and every Source field appears, across every object at once.

Does it work the way you need it to?

  • Point it at what needs attention

    Add the objects that matter, and deselect the fields that don't.

    • Objects added one at a time
    • Fields deselectable per object
  • It reads, it does not rewrite

    The metadata stays your CRM's. Changing it still happens there.

    • Definitions are read, never edited
    • Edits happen in your CRM
  • Refreshed when you say so

    Re-sync one field or a whole object, or run a new analysis.

    • Refresh per object or per field
    • Start a job from the object page
  • Every field gets its own record

    Not a list of what exists. What each field holds, and how healthy it is.

    • A page per field, not a row
    • Config stays in your CRM

Open the library, pick a field.

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Customer quote

AI readiness

"There’s a lot of room for AI to help our end users do their jobs better. That’s one of our big driving factors for adding more Plauti use cases this year, making sure all of our data is as accurate as possible so when we start implementing AI, it’s using good data, not something skewed."
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Alex Casey — Sales Technology Innovator

Wedgewood Weddings

Wedgewood Weddings

Frequently asked questions

Why does a field description matter that much?

Because without one, nobody can answer the first question anyone asks about a field: why does it exist? The same question comes back to you as a ticket, cleanup stalls because no one can say what is still needed, and every new field makes the guessing worse.

Can it tell me whether a field is safe to delete?

It gives you the evidence, not the verdict. You see how often the field is actually filled in, and how often the value is just the default nobody changed. A field sitting at two per cent is dead weight. Layouts, reports and automations are not tracked, so check those before you delete.

We already document our CRM with another tool. Why this as well?

Those tools tell you how your CRM is configured. This tells you whether the data in those fields can be trusted, a different question. A catalogue shows that a field exists, its type and where it appears. It will not tell you the field is barely filled in, that nobody ever described it, or that what was clean last quarter has drifted since.

We added field descriptions for our AI project and it did not help. Why would this?

Because a description only tells an agent what a field is for. If the data in that field is missing, inconsistent or wrong, the agent still gets it wrong. This shows you both halves: whether the field is described, and whether what is in it holds up. The data check comes first.

Our team already knows the CRM. What does this add?

Most of what a team knows sits in one or two people's heads. Even then, nobody recalls which fields are barely filled in or which never got a description. This writes it down, where the rest of the team can read it.

See how it works

Talk with one of our experts to see how that works for your use case.