A document can hold the information your team needs while still requiring someone to copy it into a database. Norml builds extraction workflows for a defined set of forms, order documents or other recurring records. We agree the fields, test representative files and prepare structured results for review. Each result keeps a link to its source so someone can check the wording before accepting the value.
We scope the document families and output fields together. Supplier invoice processing and document classification can be separate stages when the intake requires them.
We specify names, data types and required fields before choosing the extraction model. The review record retains the supplied value alongside any normalized version, such as a date. Source file and page references help a reviewer resolve conflicting values or check a table entry.
Required-field, format and cross-field checks run after extraction. Missing values stay empty or flagged according to your rules. Available model confidence can help route review, but it does not replace validation or prove that a value is correct.
Airtable can hold the proposed values and review status. File identity, source version and destination record ID help prevent duplicate writes. Unreadable files, unsupported layouts and interrupted runs remain visible for an owner to resolve before data moves onward.
Provide anonymized examples covering normal layouts, scans, multi-page files and known exceptions. We need permission to process the chosen content and an agreed retention policy for files and extracted results.
List the fields your team needs, acceptable formats and which source wins when values conflict. Identify tables, repeated sections and fields that must remain manual if they cannot be read reliably.
Name the reviewer, the acceptance action and the destination system. Decide whether this phase ends in Airtable or includes a separately tested write to another application.
We compare extracted values with checked examples and record where layouts, handwriting or scan quality affect the result. This establishes the supported scope and which cases require review.
We connect the intake, extraction model and review records. Normalization rules remain separate from source values, and retries use the processing record to avoid creating another accepted result.
We test missing pages, repeated uploads, conflicting fields and destination errors. Your team checks the review experience and receives instructions for correcting a record, resubmitting a file and updating the supported field set.