Introducing PCLaw® Verify to help support you

With your AMP membership, PCLaw Verify helps identify and manage data discrepancies.
We will continue to make enhancements that will improve PCLaw reliability for years to come.
Learn More Below

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As some on-premises databases age, data integrity naturally degrades, in severe cases causing database corruption.

Database corruption can be caused by server issues, computer errors, improper connections, power outages, or other incidents. As your database technology ages, there is an increasing risk that your data may have accumulated corruption over the years.

We now have a solution available to you to help combat this problem.

PCLaw Verify

As part of the AMP Membership, firms with flat file non-SQL databases have access to this tool to take a scheduled backup of your data and scan it and test it for discrepancies.

Depending on the database your firm uses, you may not need PCLaw Verify. Contact us using the form above to learn more and get started.


Frequently Asked Questions

Below are some common questions we have heard from our customers, with answers, for your reference.

PCLaw Verify is a new service offered by PCLaw | Time Matters™ to help you proactively scan and assess your PCLaw data files such that you can address potential data issues while minimizing disruption to your firm’s operations.

PCLaw Verify is currently developed for firms using a flat-file database NOT those on SQL or SQL Express. We recommend everyone on flat-file systems use PCLaw Verify as it serves as a back up to help ensure accuracy. Once you use PCLaw Verify you will be able to better understand data discrepancies your firm my be experiencing.

When using PCLaw Verify, it will automatically take a backup of your data and analyze it for certain types of corruption and other types of errors. PCLaw Verify can also help reduce your current data-backup costs.

The PCLaw Verify scanning service attempts to uncover data issues in a way that is essentially identical to the PCLaw VDI tool when run locally within the firm. The service currently looks for four types of potential data inconsistencies: c-tree indexing errors, address information mismatches, general bank and trust bank recalculation issues.

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