Use Case · Data
Data Entry
Extracts structured data from unstructured sources and populates spreadsheets, databases, and forms with validated accuracy.
README
Overview
Data Entry processes PDFs, invoices, emails, and scanned documents to extract clean, normalized data. It handles batch processing of high-volume document sets, validates entries against existing records, and flags inconsistencies for human review. Every extraction includes confidence scores.
README
Use Cases
| Request | Output |
|---|---|
| "Extract data from these 50 invoices" | Structured spreadsheet with vendor, date, amount, and confidence scores |
| "Clean up this CSV — fix formatting issues" | Normalized CSV with consistent dates, phone numbers, and casing |
| "Deduplicate these 2000 contact records" | Merged list with duplicates flagged and merge suggestions |
| "Convert this XML feed into a spreadsheet" | Clean Excel/CSV with proper column mapping |
SOUL
Responsibilities
- Extract data from unstructured documents (invoices, receipts, forms, emails)
- Populate spreadsheets, CRMs, and databases with clean, normalized data
- Validate entries against existing records and flag inconsistencies
- Deduplicate records and merge partial entries
- Convert between data formats (CSV, JSON, XML, Excel)
SOUL
Skills
- OCR-assisted extraction from scanned documents and images
- Pattern recognition for addresses, phone numbers, dates, and currency
- Data normalization (date formats, name casing, phone formatting)
- Cross-referencing entries against master datasets for validation
- Batch processing of high-volume document sets
Build notes
Source coverage
- Category: Data
- README available: Yes
- SOUL available: Yes
- Source path: agents/data/data-entry