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PARSER GUIDES

Clean and Format Data

Post Processing

Use Ask AI or Custom Code to clean and format extracted values

Use Custom Code in Post Processing when extracted values need a different format before they are exported. You do not need to write the code yourself--Ask AI to Write Code can create it from a plain-language instruction.

There is no separate transformations menu. Formatting is handled through Custom Code.

Common changes

  • Format dates - Convert dates to a standard format (e.g. YYYY-MM-DD)
  • Clean numbers - Remove currency symbols, commas, and convert text to numbers
  • Trim text - Remove extra spaces from text fields
  • Standardize values - Convert text to uppercase, lowercase, or title case

Use Ask AI

1. Go to Settings -> Post Processing.

2. Open Custom Code.

3. Click Ask AI to Write Code.

4. Describe the result you want and include the exact field names.

5. Select a processed document and click Run Code.

6. Compare the input and output, then click Save Code when it looks correct.

For example:

Convert Invoice Date to YYYY-MM-DD and remove currency symbols and commas from Total.

Common transformations

Format dates

Convert dates from various formats to a standard format:

  • "November 8, 2024" -> "2024-11-08"
  • "12/31/2024" -> "2024-12-31"

Clean amounts

Remove currency symbols and convert to numbers:

  • "$1,234.56" -> 1234.56
  • "EUR 500" -> 500

Standardize text

  • Convert to uppercase: "vendor name" -> "VENDOR NAME"
  • Convert to title case: "vendor name" -> "Vendor Name"
  • Trim spaces: " Vendor Name " -> "Vendor Name"

Tips

  • Name the fields clearly - Tell AI exactly which fields to change.
  • Test on a real document - Confirm the result before saving.
  • Keep the structure - Change values inside existing fields; do not add or remove schema fields.
  • Use Lookups for reference data - Use a lookup when the task is matching a value to a CSV list.

Next steps

  • Custom Code - Test and save transformation code
  • Lookups - Match and enrich with CSV files or parser data
OverviewTransform and clean your extracted dataOpen guide → LookupsMatch and enrich extracted data with CSV files or parser dataOpen guide →