Advanced Invoice Data Extraction System
Budget: €250 – €750 EUR
Title: Invoice data extraction (PDF & noisy images) + 100% accuracy with human-in-the-loop review
Brief:
I need a robust pipeline to extract structured data from supplier invoices that are not standardized (PDFs, scans, smartphone photos, sometimes skewed/low contrast). The system must reach 100% final accuracy via automatic extraction plus a lightweight human-review screen for uncertainties.
Data to extract (per document & per line item):
Supplier data (legal name, address, VAT/Tax ID)
Customer data (legal name, address, VAT/Tax ID)
Product code (the real code on the invoice)
Product description snippet (from the code’s line up to before the next product code, multi-line allowed)
Quantity purchased
Unit of measure
Unit price
Discounts (any format: %, chained like “10+10”, text notes)
Line total (net)
VAT code/rate per line
Quality & Review (mandatory):
The model flags any low-confidence field.
A review page shows: left = cropped snippet from the invoice (exact region), right = pre-filled field (editable) with Validate/Correct actions.
After review, exported data must be clean JSON/CSV/Excel.
Input conditions:
PDFs, multipage PDFs, photos (skewed, rotated, shadows).
Mixed layouts, multiple columns, line wraps, product descriptions spanning lines, some items without lot/notes.
Italian invoices mainly, but layout is vendor-specific (not a single template).
What I need from you:
Approach: which stack/services (e.g., custom OCR + ML, Document AI/Rossum/AWS Textract + post-processing, open-source alternatives), how you’ll handle layout variance and chained discounts.
Prototype: working PoC on my samples (both PDFs and phone images) with the review UI.
Costing:
Your fixed/estimated fee for the PoC + optional phases to productionize.
Ongoing operating costs (SaaS/API pricing, pay-as-you-go vs subscription, expected cost per invoice at different volumes).
Delivery: clean code, brief README, and instructions to run locally (Docker preferred) or on my VPS.
Success criteria:
High auto-extraction accuracy; 100% final accuracy achieved via the review step.
Correct parsing of multi-line descriptions and discount formats (including “10+10”).
Stable on noisy images (deskew/denoise/contrast/dewarp included).
Nice to have (not mandatory):
Field-level confidence scores; heatmaps for click-to-zoom on the original region.
Vendor-specific learnings that improve over time.
Italian language nuances.
Please include in your bid:
Short description of your relevant experience.
Proposed tools/services and why.
Timeline estimate for PoC and a ballpark for total cost.
Any clarifying questions + a list of sample files you need.
Brief:
I need a robust pipeline to extract structured data from supplier invoices that are not standardized (PDFs, scans, smartphone photos, sometimes skewed/low contrast). The system must reach 100% final accuracy via automatic extraction plus a lightweight human-review screen for uncertainties.
Data to extract (per document & per line item):
Supplier data (legal name, address, VAT/Tax ID)
Customer data (legal name, address, VAT/Tax ID)
Product code (the real code on the invoice)
Product description snippet (from the code’s line up to before the next product code, multi-line allowed)
Quantity purchased
Unit of measure
Unit price
Discounts (any format: %, chained like “10+10”, text notes)
Line total (net)
VAT code/rate per line
Quality & Review (mandatory):
The model flags any low-confidence field.
A review page shows: left = cropped snippet from the invoice (exact region), right = pre-filled field (editable) with Validate/Correct actions.
After review, exported data must be clean JSON/CSV/Excel.
Input conditions:
PDFs, multipage PDFs, photos (skewed, rotated, shadows).
Mixed layouts, multiple columns, line wraps, product descriptions spanning lines, some items without lot/notes.
Italian invoices mainly, but layout is vendor-specific (not a single template).
What I need from you:
Approach: which stack/services (e.g., custom OCR + ML, Document AI/Rossum/AWS Textract + post-processing, open-source alternatives), how you’ll handle layout variance and chained discounts.
Prototype: working PoC on my samples (both PDFs and phone images) with the review UI.
Costing:
Your fixed/estimated fee for the PoC + optional phases to productionize.
Ongoing operating costs (SaaS/API pricing, pay-as-you-go vs subscription, expected cost per invoice at different volumes).
Delivery: clean code, brief README, and instructions to run locally (Docker preferred) or on my VPS.
Success criteria:
High auto-extraction accuracy; 100% final accuracy achieved via the review step.
Correct parsing of multi-line descriptions and discount formats (including “10+10”).
Stable on noisy images (deskew/denoise/contrast/dewarp included).
Nice to have (not mandatory):
Field-level confidence scores; heatmaps for click-to-zoom on the original region.
Vendor-specific learnings that improve over time.
Italian language nuances.
Please include in your bid:
Short description of your relevant experience.
Proposed tools/services and why.
Timeline estimate for PoC and a ballpark for total cost.
Any clarifying questions + a list of sample files you need.
Related categories:
PHP
Data Processing
Excel
Software Architecture
Machine Learning (ML)
OCR
Data Extraction
AWS Textract