Home / Case Studies / ScanZilla
- Document Intelligence · AI-Powered Scanning
ScanZilla
An AI-powered document scanning and data extraction platform that transforms raw documents, receipts, and forms into structured, searchable, and actionable data — eliminating manual data entry at scale.
Data Entry Eliminated
0
%
Faster Document Processing
0
x
Invoice Generation Time
Days
→ Secs
The Problem
The Problems We Were Brought In to Solve
01 — Problem
100% Manual Data Entry
Every invoice, receipt, and form was being read and typed by staff into spreadsheets or ERPs. A single batch of 200 documents could take an entire workday — and still contain errors.
02 — Problem
3–5 Day Processing Lag
Documents received Monday wouldn’t be fully entered until Thursday. Downstream teams — finance, operations, compliance — were always waiting on data that should have been instant.
03 — Problem
High Error Rate & Rework
Manual transcription introduced a steady stream of errors — wrong totals, missing fields, misread vendor names. Catching and correcting these consumed another layer of staff time every week.
04 — Problem
No Scalability — Headcount Bottleneck
As the business grew, document volume scaled faster than hiring could keep pace. Adding more clients meant adding more people, with no end to the overhead in sight.
05 — Problem
The Bottom Line Impact
The client was losing 40+ person-hours per week to manual document processing — hours that could have been directed toward growth, clients, and strategy instead of data entry and error correction.
What We Built
Every Feature Engineered to Eliminate Manual Work
A fully custom platform that covers the entire business workflow — from the moment a dealer submits a quote, all the way through production, invoicing, and payment — with separate interfaces for internal staff and dealers.
| Feature | Description |
|---|---|
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📥 AI-Powered OCR Engine
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Custom-trained optical character recognition that reads printed and handwritten documents with 99% field-level accuracy — handling skewed scans, poor quality images, and mixed formats.
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📍 Custom Template Builder
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Build and save extraction templates for any recurring document type. Map fields once — ScanZilla handles every future document of that type automatically without retraining.
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🗂Batch Upload & Processing
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Upload hundreds of documents in one action. The engine queues, processes, validates, and flags errors without any user intervention — results available in minutes, not days.
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📦 Confidence Scoring & Review Queue
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Every extracted field receives a confidence score. Low-confidence fields are automatically routed to a human review queue — so teams only touch what actually needs attention.
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📝 ERP / CRM Direct Integration
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Extracted data pushes directly to QuickBooks, Xero, Salesforce, SAP, or any system via webhook or API — eliminating the export-import cycle entirely.
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📡 Analytics & Audit Dashboard
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Track extraction volume, accuracy trends, processing time, and error rates in real time. Full audit trail for every document processed — essential for compliance-heavy industries.
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THE RESULT
What
Changed
A side-by-side look at the operational reality before ScanZilla, and what the client’s team experiences every day after go-live.
| Area | Before | After |
|---|---|---|
| Document data entry | Manual transcription, ~3 min per doc | Fully automated, seconds per doc |
| Processing turnaround | 3–5 business days | Under 60 seconds per document |
| Error rate | 4–6% transcription error rate | <1% — AI confidence-scored & flagged |
| Staff hours on data entry | 40+ hours per week | ~2 hours/week for edge-case review |
| Batch processing | 1 person, 1 document at a time | Hundreds in parallel, unattended |
| ERP/CRM sync | Manual re-entry after extraction | Auto-pushed via API on extraction |
| Scalability | Headcount grows with volume | Volume grows — headcount stays flat |
We built an AI-powered document intelligence engine that connects any incoming document — invoices, receipts, contracts, forms — to a business's downstream systems in seconds instead of days, eliminating the manual data entry bottleneck that was holding the team back from scaling.
Tech DeJure Engineering Team
ScanZilla — Lead Architects
