IN BETA

Document extraction that tells you when it might be wrong.

Finance and ops teams can't trust AI extraction for invoices, receipts, and bank statements — because a silent error is worse than no extraction at all. FieldScore extracts your documents and scores the confidence of every single field, so you know exactly what to double-check.

No credit card. In beta — we're onboarding waitlist users first.

How it works

Five steps. The fourth one is the one nobody else sells.

1

Upload

Drop in invoices, receipts, bank statements, or purchase orders — PDF or image.

2

Extract

Vision + LLM models pull structured fields: vendor, dates, amounts, line items, tax IDs.

3

Score every field

Each extracted value gets a confidence score based on source clarity, cross-field consistency, and model agreement.

4

Review the flagged ones

Low-confidence fields land in a review queue. Approve or correct them in one click — only touch what needs touching.

5

Export

Clean CSV with every field, its confidence score, and your corrections — ready for your accounting system.

Product preview

Mock of an invoice extraction result. Amber = check it. Red = fix it. Green = trust it.

extraction-result — invoice INV-2026-1042.pdf Product preview — in beta
FieldExtracted valueConfidence
Vendor nameAcme Supplies Ltd.99%
Invoice numberINV-2026-104298%
Invoice date2026-09-2897%
Due date2026-10-2? — print smudged71%
CurrencyUSD99%
Subtotal$4,820.0096%
Tax amount$386.0094%
Total amount$5,2?06.00 — digit ambiguous, total ≠ subtotal + tax52%
Tax IDTX-882-10495%

Review queue (2)

Total amount 52%
Digit ambiguous and total ≠ subtotal + tax. Verify against the source scan.
Due date 71%
Smudged print. Source crop shown alongside for one-click confirmation.

7 of 9 fields auto-accepted. You review only the 2 that matter.

Illustrative mock-up of the extraction view — in beta.

What makes us different

Existing tools extract documents. We extract — and tell you what to double-check.

Conventional extraction tools

  • ✕Extract text and fields from documents
  • ✕Return values with no per-field reliability signal
  • ✕Errors surface silently — downstream, in your books
  • ✕Your team must re-verify everything, manually

Tools in this category include Parseur and Docparser, which offer document extraction at roughly $39/mo+ pricing.

FieldScore (in beta)

  • ✓Extract fields from invoices, receipts, bank statements
  • ✓Score the confidence of every extracted field
  • ✓Route low-confidence fields to a one-click review queue
  • ✓Export CSV with scores + your corrections attached

No other mainstream extraction tool sells field-level confidence as the core workflow — that's the whole point.

Pricing

Simple, usage-based tiers. COMING SOON

Starter

$15/mo

For freelancers and small teams. Core extraction + confidence scoring + review queue.

Team

$29/mo

For finance & ops teams. Higher volume, multi-user review queue, priority exports.

Scale

Custom

Usage-based volume tiers for high-throughput AP/AR pipelines. Talk to us.

Pricing is planned, not yet live — waitlist members get launch pricing and beta access first.

Get beta access

Join the waitlist. We'll email you when your beta seat opens.

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No spam, ever. One email when beta opens, unsubscribe anytime.

FAQ

How are confidence scores computed? +
Each score combines source-image clarity, model agreement across passes, and cross-field consistency checks (e.g., does total equal subtotal + tax?). The exact weighting is being tuned during beta — scores are designed to be directionally useful, not perfectly calibrated, from day one.
What documents are supported? +
Beta focuses on invoices, receipts, bank statements, and purchase orders (PDF or image). Other document types are on the roadmap — tell us what you need in the waitlist form.
Is this available now? +
Not yet — we're in beta and onboarding waitlist users in batches. Join the waitlist and you'll get an email when your seat opens.
How is this different from Parseur or Docparser? +
Those are mature, proven extraction tools. The difference is workflow: they return extracted values; we return extracted values with a confidence score on every field and route only the uncertain ones to human review — so your team verifies 10% of fields instead of 100%.
Do my corrections improve the system? +
Corrections are stored with your exports so your downstream data stays clean. Using corrections to improve shared models is opt-in and only ever done on anonymized, aggregated data — never your raw documents.
What does it cost? +
Planned pricing is $15–29/mo with usage-based tiers, but pricing isn't live yet. Waitlist members get launch pricing when we open paid plans.