If you’ve used any of the popular review tools lately and needed near dupe detection, email threading and clustering, chances are that your experience has been less than ideal. If you’re working with a large set of data, you’ve probably had to wait for the processes to run days or even weeks, and on occasion, had the process simply fail to complete. Furthermore, you’ve likely experienced document clusters that, in an attempt to cluster everything, create a large number of clusters that are little more than seemingly random sets of data, where logical connections can be very difficult to see.
These experiences are common because most of the traditional review tools are using outdated underlying technology and approaches.
iControl ESI is a software company as well as a service provider. We see these flaws, and we have the ability to fix them. Here are the common problems we are solving with our analytics solution, ENVIZE™.
All of us have been impressed with the idea of concept wheels, maps, trees, and bubble charts, only to have them let us down when the rubber meets the road in a large-scale review project. The clusters can take a long time to create, require painful updates when you add new data to the population, and (since they typically strive to put every single document in a cluster), can overwhelm you with noise that really doesn’t help you to quickly work through data.
ENVIZE clustering is truly unique in both its scalability and focus. It uses a fraction of the computer resources needed by other tools, and it creates fewer, more useful clusters. The result: you have your clusters faster and can use them to make better decisions.
Scalable Near Dupe Detection and Email Threading
Near Duplicate Detection and email threading are conceptually simple. They are tasks that we can imagine performing with the naked eye. They are deceptively simple concepts. Comparing each document to every other document in a data set to identify near duplicates or email threads becomes impressively resource-intensive on large document populations. As a result, the most common complaint relative to these features is not that they don’t work, but that they simply take too long or require too much computing power to complete. This doesn’t have to be the case.
ENVIZE near dupe detection and inclusive email identification uses ingenious processes and algorithms that are remarkably faster and require a fraction of the computing resources, when compared to the most common competitors in the eDiscovery market. The result: You wait less for near duplicate and email threading output, and can more readily use that output in managing an efficient review.
In matters where audio data is (or may be) important, dealing with those file types can create a significant challenge. In those cases, wouldn’t it be nice to search the audio, or apply analytics tools, just as you do text-based documents? Of course! ENVIZE can now utilize the latest audio-to-text technology. The result: You can now obtain searchable text for stored audio files and use that text, just as you would use OCR text of scanned documents for searching and analytics purposes.
We would love to answer your questions, and show you how ENVIZE can help you with your next large-scale document review!
About iControl ESI
iControl ESI, founded in 1999, is a complete eDiscovery software and services provider, providing solutions in all phases of the EDRM. Through a combination of expert advisory services, skilled and efficient project management, state-of-the-art technology, and a singular focus on creating the best client experience, iControl ESI provides solutions to the business problems associated with discovery, by lowering the cost of data discovery and increasing document review efficiencies. In addition to working with industry-best technologies, iControl ESI utilizes its own developed technologies, which include ENVIZE, an industry-changing predictive coding solution, and Recenseo, a complete online document review solution. Visit us at www.icontrolesi.com.