New Features
Signature Detection
VMR now automatically detects when a document contains one or more signatures, making it easier for you to confirm whether a document is fully or partially executed, during the bulk review and publish process.
As part of the AI document classification and data extraction, VMR will:
- Pinpoints the exact page(s) where signatures appear, so you can navigate to them quickly.
- Automatically apply the new "Signed Docs" system tag and metadata for publishing to Class Document Management System (DMS) or linked SharePoint.
- Remove the tag dynamically if the Doc Signed toggle is manually overridden.
This feature is available for the following document types:
- Request to Adjust Concessional Contributions
- SMSF Deed of Amendment/Variation
- SMSF Deed of Appointment/Retirement
- Investment Strategy
- ATO Trustee Declaration
Member Extraction
VMR now automatically extracts member details from supported document types and maps each member to the correct fund in Class.
As part of this enhancement:
- A dynamic tag containing the member’s full name is automatically created.
- The member tag is removed if the member‑to‑fund mapping changes.
- Member tags are included when documents are bulk reviewed and published to Class DMS.
This feature is available for the following document types:
- ATO Commutation Authority
- Notice of Intent to Claim Personal Super Contributions
Enhancements
VMR performance has been upgraded to deliver noticeably faster load times and improved responsiveness. These enhancements create a smoother experience today while also laying the groundwork for upcoming User Experience improvements.
Other Updates
- Monthly AI model re-training and automated sampling for November 2025, December 2025, and January 2026 confirm that VMR accuracy remains exceptionally high at 96%.
- The list of supported document types has been updated. See the full list here: What is the Difference Between VMR-Supported and Unsupported Document Models?