Harness The Power of Simplicity

While Artificial Intelligence is not new, it has gained momentum, over the last year, as part of robust eDiscovery solutions. Technology companies are incorporating AI into their processes, allowing their staff to be more productive and, in turn, their businesses are becoming more efficient and more profitable. The opportunities for AI seem endless, and while the math and science at its core may be extremely advanced and hard to comprehend, the truth is that AI unlocks the “The Power of Simplicity” for those who use it effectively.

For some, the connection between AI and “The Power of Simplicity” might not be immediately obvious.  Sure, it sounds great, but how can you actually see “The Power of Simplicity” in action? Let me illustrate how this worked in a recent oil and gas matter, on which our law firm customer used ENVIZE to save over $300,000 in review costs. 

The best way to demonstrate ENVIZE’s “Power of Simplicity” is to break down what it gives you, as an ENVIZE user, in a real project.  For this case, I will focus on flexibility.  We’ve all seen “flexible” tools that fail to deliver on their potential. Why? Because in attempting to deliver flexibility, they cloud our goals with complexity and confusion. Flexibility done right does not do that.  Powerfully simple tools deliver flexibility in creative ways that (a) maintain simplicity (b) adapt to your project needs, and (c) keep you focused on doing what you need to succeed.

So, back to our oil and gas example . . . In this case, our team’s first objective was to obtain a thorough understanding of the types of relevant documents they had collected. Accordingly, we started the review with an ENVIZE workflow tailored to this priority.  The customer team provided ENVIZE with a few sample relevant documents.  Based on those few examples, ENVIZE quickly started queueing up the most likely relevant documents for review in an iterative but automatic process.  As the review continued, ENVIZE continuously updated the AI training, learned more about what our team was looking for, and utilized the updated AI in presenting more documents for review.

After just under 2,000 documents, 85% of which were relevant, the review team was confident in their understanding of the collection. 

Now, however, there was a bigger problem and a new priority looming: there were additional collections mounting and the production deadline was fast approaching.  The team needed to shift gears and focus on identifying a production population and getting that out the door – ASAP!

ENVIZE automatically accommodated the priority change by efficiently shifting to a different workflow tailored to the new priority and accelerated timeline.

From this point forward, ENVIZE queued up the documents that would help it learn the fastest, minimizing the effort needed to predict which documents were responsive.

ENVIZE used all of the training from the previous workflow, and automatically queued up documents to confirm that training – it did not require re-training.  You can see that on the included training stability chart. The stability dropped as new collections were added, but ENVIZE used its prior training, along with minimal confirmation decisions to quickly bounce back, keeping the production on schedule.

ENVIZE’s patent-pending sampling method allowed it to identify the best new training documents and adjust the learning for the new data with very little incremental work.

And just when you thought it couldn’t get any easier, our customers used ENVIZE’s simple-to-understand dashboard to monitor progress, get a better understanding of the document population, and prepare for production – ALL ASAP! 

In only 40 hours of review time, the team trained the system, identified the production population, and performed the necessary QC to be confident in their result.  ENVIZE saved a ton of review time and over $300,000 in review cost.

After seeing their law firm harness “The Power of Simplicity” on this one case, the corporate client decided to take advantage of the ENVIZE difference in all their cases. Should you?

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