Vanta Logística (fictional) · Process Optimization · AI-enabled Finance Automation
Intelligent Document Capture
A redesigned document-intake process that turns invoices and fiscal documents into clean, validated data and screens them for anomalies — with applied AI as the enabler, not the headline.
The Problem
Vanta Logística received invoices and fiscal documents in every format — structured files, PDFs, photos of paper — and a team typed each one in by hand. Errors surfaced only weeks later, during reconciliation, when they were expensive to fix.
Why It Matters
Manual data entry never shows up on a P&L, yet it quietly sets the ceiling on how fast and how accurately the whole Finance function can work.
How I Approached It
I designed a document-understanding pipeline that extracts every field into structured data with a confidence score, validates it against business rules, and flags anomalies for review. High-confidence documents flow straight through; only the uncertain ones reach a person.
- Any format — structured files, PDFs, scans
- Confidence scoring routes only uncertain items to review
- Duplicates and out-of-pattern documents flagged automatically
Interactive Demonstration
The preview shows a sample document with its fields extracted and scored. All documents and figures are fictional and illustrative only.
DOC-4471
Click a field to highlight it on the document
Source document
Orion Manufacturing
Extracted fields
Vendor
Orion Manufacturing
Document no.
INV-88213
Issue date
2026-07-02
Subtotal
$11,540.00
Tax
$940.00
Total
$12,480.00
Enabling Technology
Capture
- Multi-format intake
- OCR for scans
- Document AI extraction
Validation
- Rules engine
- Confidence scoring
- Duplicate detection
Output
- Structured records
- Review queue
- Audit log
Business Value & Takeaway
Documents move from hours of manual entry to seconds of structured, validated data, with anomalies caught at intake instead of in reconciliation. Humans handle only the exceptions, not every document.
The breakthrough was not the AI. It was deciding the data should never be typed twice.