BlackOre

What is BlackOre?

BlackOre is an AI platform that automates complex tax return preparation directly within supported tax software for CPA firms. The vendor claims the system extracts data from source documents and reduces manual preparation time by up to 98%. Access requires requesting a demo, and the platform integrates with specific tax software including Intuit Lacerte, CCH ProSystem fx, Drake Tax, and others.

What are the features of BlackOre?

• Automated data extraction

  Extracts information from source documents to populate tax returns, with the vendor claiming over 99% accuracy in data extraction.
• Document classification and organization

  Automatically categorizes client documents and generates data request lists after users drag and drop files into the platform.
• Return review assistance

  Flags potential errors and inconsistencies in completed returns and coordinates reviews across team members.
• Audit traceability

  Links every figure in a prepared return back to its source document through centralized storage, indexing, and exportable audit packages.
• Tie-out package generation

  Produces Excel-based tie-out packages and return packages formatted for CPA sign-off.
• Tax software integration

  Connects with supported platforms including ATX, CCH Axcess Tax, CCH ProSystem fx, Drake Tax, Gosystem Tax RS, Intuit Lacerte, Intuit ProConnect, Intuit Proseries, and Ultratax CS.

What are the use cases of BlackOre?

• High net worth individual returns

  Preparing complex 1040 returns with dozens of K-1 schedules, which the vendor states can be readied for review in minutes instead of days.
• Firm capacity expansion

  Increasing the volume of returns a firm handles without adding headcount by reducing preparation time per return.

How to use BlackOre?

1. Upload documents

   Drag and drop client documents into the web dashboard.
2. Track preparation

   Monitor each return's status as the platform prepares it directly in the connected tax software.
3. Review flagged items

   Examine potential errors and inconsistencies identified by the system before finalizing.