In day-to-day operations, an attachment may be missing or the wrong version may be used. When the pleading draft, attachment list, folder, version and date are spread across different screens, documents or team records, the issue may not be noticed in time.
This fragmented data delays preparation of the attachment checklist and forces staff to search for supporting records again by hand. Before deciding, the matter lawyer must complete missing fields and verify each inconsistency individually.
A common exception is that draft, signed and translated versions may all be present. If this context is not checked, an incomplete or incorrect automation could lead to the wrong document being filed, so the output cannot be acted on directly.
The system stops after preparing the attachment checklist. The matter lawyer reviews the sources and the exception, then approves, corrects or rejects the output. Direct execution remains disabled because it could lead to the wrong document being filed; the system does not replace professional judgement.
Access to the pleading draft, attachment list, folder, version and date is limited to the minimum permissions needed for the task. Identifiers and sensitive fields are masked where possible, and only the necessary section is sent to the model rather than the full raw file. Access, output and the matter lawyer's decision are logged; production use does not begin until the organisation approves the retention period and data location.
A good fit
Not a good fit
The pleading draft, attachment list, folder, version and date are used. If a required field is missing, the system does not produce a definitive result and flags the missing source for review by the matter lawyer.
The workflow stops when the attachment checklist is ready and waits for the matter lawyer's approval. The lawyer can correct, defer or reject the output with reasons.
The design retains the source identifier, applied rule, exception, output and human decision together. This makes it possible to review how each source record led to a recommendation.
Project led by:DijitalPi
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