I recently interviewed Dave Ruel of Hanzo and Isaac Madan of Nightfall. We covered so much with regard to eDiscovery trends that we couldn’t fit it all in a single blog post. Part 1 of our interview was published Monday, part 2 was published Wednesday, here is part 3 with Dave Ruel and Isaac Madan.
In part 3 with Dave Ruel and Isaac Madan, we discussed the impact of personal data on eDiscovery workflows and how Hanzo’s and Nightfall’s technology solutions will help organizations effectively manage the various communication apps to support eDiscovery workflows.
Doug Austin: Dave, you and I both know discovery is about workflows. How has the identification and mitigation of personal data impacted eDiscovery workflows and how can leveraging technology to address PII make those workflows more efficient?
Dave Ruel: For me, it’s all about choices. For many years, classic eDiscovery simply didn’t provide any intelligence on the data that you had collected. You just collected the data, and you did some culling of that data. You put a big team of reviewers on it, but little intelligence bubbled up to the surface. So, you didn’t make intelligent decisions until the review stage, when someone finally took an in-depth look at the data. Artificial intelligence and machine learning have started to come into their own in terms of being able to illuminate information. People leveraging AI have more choices on the front side of discovery for early case assessment – even before review – which sets up more productive eDiscovery workflows because now you get to choose what to do with sensitive data. For me, it’s about allowing people the choice to incorporate new and different workflows. For example, do you redact information or simply choose not to transfer the data to a review platform because you don’t want to continue propagating PII outside of the collection system?
That’s what gets me excited about what we’re doing for customers. We’re getting them data intelligence to make wise decisions about their entire EDRM workflow at the earliest point possible. DLP is finding that data at the earliest phase of the process – at the point of creation, which can be very important. Early intelligence is what it’s all about for better eDiscovery workflows.
Doug Austin: Last question. Dave and Isaac, organizations today use a multitude of apps and solutions for communicating and most use more than one collaboration app – many use several apps and there are often Shadow IT apps within large organizations. How can the technology solutions offered by Hanzo and Nightfall help organizations effectively manage the various communication apps to support use cases like eDiscovery, compliance and investigations?
Dave Ruel: Well, that’s a great question. You’re right; it’s a multitude of apps, whether it’s Asana, Slack, Jira, Confluence, Google, or others, and it’s happening everywhere. The challenge for organizations is connecting to all these modern sources and collecting meaningful and valuable data. Because the different use cases, such as eDiscovery, compliance, and investigations, all have a unique workflow and a methodology of how people want to look at that information, Hanzo has taken a unique approach, what we call “API plus.” Many companies simply go to the API, which may not be as valuable as it seems because you may not get all the data you want. You may only have access to some of the capabilities of the API. Our “API plus” approach enables us to capture the API information and augment that information with unique crawl capabilities to make it even more useful in the workflow for the user.
So, if it’s a compliance manager, someone conducting an investigation, or someone else who may want to traverse through the information that they’re viewing, Hanzo takes these API sources, and we go as deep as we can with them. Instead of just doing a “wide net” casting across all the API sources, we try to bring some depth and share the value of the unique connectivity that we have with those sources.
Isaac Madan: To protect sensitive data across a rapidly growing number of applications and services, organizations need flexible and effective solutions. Nightfall has two solutions to address both flexibility and scale: (1) our machine learning-powered detection engine and (2) our Developer Platform. When we built the detection engine, we wanted to provide teams with the ability to granularly and easily customize when and how sensitive data like PII, PHI, secrets and other business-critical data is detected within their environments. This ability would help them easily comply with various compliance regimes like SOC2, HIPAA, PCI, etc. The developer platform democratizes data protection in any application by delivering a set of end-to-end APIs for content inspection. That means that organizations can easily embed our machine learning-powered detection engine and our detectors into any business logic or data flow to monitor sensitive data as data flows within and across applications. Of course, this partnership itself is just one excellent example of that.
Dave Ruel: And that second point was essential to Hanzo. The more sources we can connect to and the more we can flow that data through this API, we allow users to gain greater access and knowledge on the information they are collecting. It’s a critical component. The other part of that is Nightfall’s ability to keep up with PII, PHI, etc. Tapping into Nightfall’s veritable library of data classification and detection capabilities enables our clients to get historical visibility and insights about the sensitive data in their systems which provides enormous value.
As we think about converging use cases, I love Isaac’s description of democratizing data analysis wherever it lives. You mentioned in your question this convergence of investigations, compliance, litigation, and response. We see that in all kinds of disciplines. But this is an example where we’re bringing together the power of what were formerly individual silos. There are many synergies to benefit from using the same detection rules, whether you’re looking in real-time or looking back in time. By leveraging Nightfall’s expertise to dive in and identify unwanted behavior or various types of sensitive information, Hanzo is extending new insights for legal, investigations, and discovery teams. Those insights are where the real power is.
Great. Thanks, Dave and Isaac, for appearing on the eDiscovery Today Thought Leader Interview series!
BTW, Hanzo and Nightfall will be conducting the webinar Drive Data Intelligence with Collaborative Data on Tuesday, May 24th at 1pm ET! For more information and to register, click here!
So, what do you think? Please share any comments you might have or if you’d like to know more about a particular topic.
Disclosure: Hanzo is an Educational Partner and sponsor of eDiscovery Today
Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by my employer, my partners or my clients. eDiscovery Today is made available solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscovery Today should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.