5 Features Your Data Processing Team Wants

There are many reasons why data processing teams love Rampiva Automate—faster results, improved data quality, and freeing up technical experts to tackle new problems. 

But, we wanted to specifically share 5 features that get actual users excited:

1. Notifications

Most teams have to monitor their data processing activity to see when it is finished. Then they have to generate a report with the results, customize the findings, and then send that report to another team member.

With Rampiva Automate, those steps happen automatically.

Which means you can go to lunch.

2. Nested Processing/Search Runs

We’ve all been there—the first OCR run doesn’t get all of the items, so you have to run another one on just the items that didn’t get populated. Then you have to do it again on the remainder from that set…and so on.

Or, maybe we’re talking about password cracking, escalating confidence in search criteria, or even rounding out the profile of your custodian aliases.

Doing the same task over and over again is a grind, particularly when you’re on a clock.

This feature helps you to stop doing that.

3. Access Control

Much of the data that we work with is sensitive (e.g., PII, PCI, PHI or NPI). The items themselves, the search criteria, known good/known bad files—at the end of the day, the data analytics process itself creates risk.

Rampiva makes it easy to give users the ability to process, search, analyze, and export results without ever having to actually look at any of that material.

4. Real Time Metrics

We know, we know, it’s all we talk about.

Rampiva Automate generates operational and “point in time” metrics across all cases, in real time.

We’re seeing clients tracking error-rates, modeling throughput by file type, tracking duplication and tag hits, across all data processed for specific clients.

It’s super cool.

5. Export to Review

Many review platforms make it easy to upload items for review—if there aren’t too many items.

Rampiva Automate makes it easy to “stream” small batches within a production set so that the review platform can upload the exports through their standard channel.

This accelerates the process and makes it more stable. Which means it can be reliably executed off-shift.


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