Returns the fields it can actually read, and says so about the rest
Turning documents into rows is the most-copied automation on every platform, and almost all of it fails the same way: every field comes back filled. A total it could not read becomes a plausible number, a date it guessed becomes a date, and the row enters your ledger looking identical to the rows that were read correctly.
Extraction is only worth anything if you know which fields to trust. This agent scores every field it returns, refuses to supply a value it cannot support, and distinguishes a field that is absent from the document from one that is present and unreadable — because the first needs a question and the second needs a better scan.
It also checks the document against itself: lines that do not sum to the stated total, a date after the document's own issue date, a currency that changes mid-page. Those are the errors that survive every confidence score, because each individual field looked fine.
Low-confidence fields are flagged; the rest pass.
The failure mode of every other extractor is a wrong number that looks right.
Internal inconsistencies are found on the way through.
You know which values to trust before they reach a ledger, not after an audit.
A field it cannot read comes back empty. A guessed total is worse than a missing one.
One needs a question to the sender, the other needs a better scan.
Lines that do not sum, a date after the issue date, a currency that changes mid-page — errors every field-level score misses.
It extracts the fields you asked for, and says which of them the document does not contain.
It returns data. Putting it into your systems is a step you control.
Why Operations in particular. It leaves blank what it cannot read. Every other extractor returns a plausible number that looks exactly like a correct one, and nobody checks.
Runs unattended
Started by you or by an event, and it finishes on its own. Nothing waits for someone to be at a desk.
The same standard every time
The two-hundredth item is held to the bar the first one was. Consistency is the part people cannot sustain.
It cannot act on its own
Document Data Extractor has no path to sending, spending or committing. That limit is why its output is safe to act on.
This agent runs server-side through the PROMIVO runtime. Each run is logged step by step and every tool call is permission-checked before it executes.
Read-only by design. This agent has no path to sending, spending, publishing or committing anything. Where that limit is the product, removing it would remove the reason to trust the output.
Demo dataIllustrative sample output, abridged.
{
"text": "…",
"fields": [
{
"name": "total",
"type": "currency",
"required": true
}
],
"documentType": "invoice"
}{
"fields": [
{
"name": "total",
"basis": "Labelled 'Total due' in the summary block.",
"value": "4180.00",
"status": "read",
"confidence": "high"
},
{
"name": "purchaseOrder",
"basis": "No PO reference anywhere in the document.",
"value": "",
"status": "absent",
"confidence": "low"
},
{
"name": "dueDate",
"basis": "Reads '03/04/2026'. Day-first and month-first give different dates and the document states no convention.",
"value": "",
"status": "ambiguous",
"confidence": "low"
}
],
"escalate": true,
"inconsistencies": [
{
"issue": "Line items sum to 4,120.00 but the stated total is 4,180.00.",
"values": [
"4120.00",
"4180.00"
]
}
],
"escalationReason": "The document does not add up to its own stated total.",
"needsHumanReview": [
"dueDate — ambiguous format",
"total — does not match the line items"
]
}No integrations required.
Into rows, with the ones needing a human marked.
Structured, with missing fields listed rather than invented.
Reconciled against their own totals as they are read.
$179/month
Billed monthly through your PROMIVO subscription. Cancel at any time.
Runs consume your plan allowance for agent executions and tokens. See plan limits.
It works from the text you supply, including text produced by your own scanning. Where that text is garbled it reports the field as unreadable rather than guessing what it probably said.
Because a plausible wrong value is the expensive failure. A blank field asks a question; a guessed one answers it wrongly and nobody checks.
No. It returns structured data with confidences. What you do with a low-confidence row is a decision, and it should be yours.
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