Browser-local acknowledgment conversion

Convert EDI 997 to CSV, Excel, JSON, or XML

Prepare the canonical 58-field mapping or a separate physical Raw representation.

Upload or paste an EDI 997, then choose Smart Mapping or Raw Mode. Automatic detection requires exact ST01=997. Review transaction-level acknowledgment rows, a possible group-summary fallback row, generic validation findings, and the source-grounded summary before exporting.

Choose Smart Mapping or Raw Mode

Smart Mapping produces 58 canonical string fields using TRANSACTION_ACK and GROUP_SUMMARY rows. Raw Mode remains a separate source-ordered physical-segment representation. Switching modes does not reinterpret acknowledgment codes, and 997 has no Key/All selector.

What each canonical export represents

CSV preserves all 58 headers in order with standard escaping. Excel/XLSX prepares a string-safe 58-column workbook. JSON contains canonical row objects with 58 string-valued keys. XML is an escaped canonical-row serialization; it is not native X12 XML, implementation-guide XML, lossless X12 hierarchy, or a reconstruction of the source interchange.

Preserve lexical evidence

Control numbers, AK9 counts, source positions, leading zeros, long numeric-looking values, multiline element evidence, and collection JSON remain strings. Viewer and Data Editor search, filter, sort, editing, and export-after-edit use generic text-safe behavior and do not numerically coerce those fields.

Privacy and validation-report boundaries

Semantic mapping, validation, summary, and export preparation occur locally in the browser. Normal page, asset, authentication, quota, and analytics traffic may still occur, but the source EDI payload is not intentionally transmitted by those semantic steps. Validation reports support CSV, Excel, and JSON—not XML—and suppress raw AK404 bad-data values from safe diagnostics.

Convert a 997 acknowledgment

Open the EDI Converter, inspect acknowledgment rows in the Viewer, or use the EDI 997 canonical data map to interpret fields. The AK-segment reading guide and 997 validation guide help investigate rejected or error-coded source evidence without treating it as a business decision.