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2 min read

Text Analytics for Relativity®: A Buyer’s Guide

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Relativity has over 150,000 users worldwide who have discovered 3 key concepts to looks for in a text analytics app

relativity-logo-orange.jpgThat’s why, like most high-profile solutions, Relativity® has had its core functionality enhanced by a number of third-party developers.

This active, talented developer ecosystem provides a massive amount of pieces for the Relativity® puzzle, from dashboards and data transfer to reporting and redaction. Of particular note, though, is the growing number of companies – including ayfie, naturally – expanding upon the platform’s native text analytics capabilities. The data sets from which organizations must extract meaning are growing larger and more complex every year; the best text analytics engines make unstructured content – like email threads, Word documents, PowerPoint slides, PDFs and more – rapidly available for in-depth search, semantic analytics, data extraction and aggregation.

Of course, all text analytics apps for Relativity® aren’t created equal. Here’s what to look for – and look out for.

1. It’s about natural intelligence, not ‘AI’

Too many text and content analytics platforms tout their “AI” capabilities. Problem is, eDiscovery and knowledge extraction isn’t about anything “artificial.” Software can (and should) help a human cull content, extract meaning and prioritize efforts, but it can’t make final decisions … and certainly can’t be the final eye before production.

Depending on traditional AI and machine learning methodology – the “bag of words” approach, which treats letters, words and phrases merely as symbols – strips valuable context from documents. Most analytics platforms, for instance, would have difficulty properly identifying the entity “JFK” (here, an airport) in the phrase “JFK to Dallas.” Without a human-like understanding of the contextual meaning of “to,” the proximity of “JFK” to “Dallas” would lead the platform to assume the entity “JFK” refers to the president, not the airport.

The upshot? Just because it’s “AI-powered” doesn’t mean a text analytics platform is any good. The ultimate focus is on empowering human knowledge workers to do their jobs more efficiently and effectively. That means applying natural intelligence. 

2. Tight Integration Maximizes ROI

It’s entirely possible to utilize a third-party text analytics platform “with” Relativity® through manual imports and exports. That approach, however, is both inefficient and error-prone; a single bad keystroke or misplaced piece of data can create highly negative downstream effects.

Instead, if you’re looking to augment Relativity’s analytics capabilities with a partner solution, make sure it’s accessible from within the eDiscovery platform itself. It should tie directly into native Relativity® workflows, and data should flow seamlessly both ways, with no manual steps involved. This allows Relativity® to remain the single source of truth for all data, increasing user adoption and maximizing return on the significant investment placed in the system.

3. Think Outside the EDRM

Again, the more Relativity® is utilized in your organization, the more value can be extracted from it. While it’s ultimately an eDiscovery solution, it can be used for tasks outside traditional legal review. When paired with the right text analytics platform, for instance, Relativity® proves an excellent tool for analyzing large sets of contracts (like ayfie Inspector), either to identify current risk and obligation or to perform due diligence in advance of M&A activity. When you combine Relativity’s familiar, intuitive UI with modern analytics software, the sky’s the limit.


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