eDiscoveryDaily

JSON is not a document, it is data… and lots of it!

By:  Trent Livingston

Modern eDiscovery deals with much more than just documents. In 2020, people created 1.7 MB of data every second, and most of that data was likely stored in a database. Now, newer applications like Facebook, Twitter, Slack are storing copious amounts of data ranging from tweets, wall posts, and chats.

Many of these artifacts are stored with complementary data that can include file links, reactions (such as “likes”), and even geolocation information. Accessing this modern data in order to leverage it for a discovery request often requires some sort of archive process from the originating application, and that is when JSON enters the picture.

JSON stands for “JavaScript Object Notation”, but that doesn’t mean you need to know how to write JavaScript (or any code for that matter)!  If you’ve ever dealt with discovery surrounding any of the aforementioned applications, you’ve likely come across a few JSON files. In a nutshell, think of JSON as a relational spreadsheet where one column of data in one tab of your spreadsheet is defined by another column of data in another tab in another spreadsheet.

For example, you might have a column called “Address” in a spreadsheet and that column contains a series of numeric “id” values that reference another tab in that same spreadsheet. In this secondary tab, each address is broken down into values for that address that may include things like “country”, “zip”, or “street”.  All those values that have the same “id” belong to the “address” reference in the previous tab. Simply put, this is structured data. JSON data is no different. However, JSON can contain a multitude of data structures varying from simple to complex.

The problem with JSON is while there are multiple JSON viewers and formatters online, they do not understand the defined data structures within.  Each platform defines these data structures differently, and while the vehicle may be the same, the defined structure is usually different from application to application (as well as the application’s version).  Therefore, the data within the JSON often comes out in an unexpected format when using a generic formatting tool, and the relationships between the data are often lost or jumbled. (By the way, you should never use any online “free” tool to format potentially confidential or privileged information).

Therefore, it is important to work with someone who understands JSON as an eDiscovery data source.  A single JSON file just a few megabytes in size may represent hundreds, if not thousands of messages, contain numerous links to files, as well as key data relevant to your investigation or litigation. Contained within a JSON file could be any number of nested data formats, including:

  • Strings: a sequence of zero or more Unicode characters, which could include emojis in a Unicode format, usernames, or an actual text message.
  • Numbers: a numeric value that can represent a date, intrinsic value, id, or potentially a true/false value represented as “1” or “0”.
  • Objects: a series or collection of one or more data points represented as named value pairs that create meaning as a whole, such as longitude, latitude, elevation, rate of speed, and direction that make up the components of a device’s location.
  • Arrays: a collection of values or elements of the same type that can be individually referenced by using an index to a unique identifier, such as the choices of a color of a car on a website or a set of canned response values listed in a software chat application.

The thing to remember is the JSON file is actually one big “object”, which is the parent to all of the named value pairs beneath it.  Within this object, you can have more objects that contain numbers, strings, arrays, and yet even more objects. Confused yet?

Not to worry! It is understandable that all this JSON data can quickly become a source of frustration!  The question that remains is, “How do I make sense of all of this structured data and present it for review in a reasonably usable format?” 

Here are some tips:

  1. Make sure you do not overlook JSON as part of your electronic discovery protocol
  2. Leverage an experienced team to help you understand the JSON output
    • Document the source application whenever possible (some JSON include access keys that can expire or be terminated at any time, such as Slack)
    • Preserve the JSON file as you would any other evidentiary data source
    • Document the chain of custody for the JSON file (originating application and version of that application, who conducted the export, as well as any access keys that may be transitory or temporary and their date of expiration)
    • Treat each JSON file and associated content as a potential source of PII, confidential, and/or privileged information given the breadth of data that each may contain
  3. Work with a team and a product that can parse, ingest, and subsequently present JSON data in a usable format for review and production

While there is not an off-the-shelf solution for every JSON file in existence, CloudNine ESI Analyst is a platform designed for the multitude of data types that can be extracted from just about any JSON file out there. Many of which can be easily mapped to a data type construct within our SaaS application that allows for presentation, review, and production in a reasonably usable format.

Contact us today for a demonstration and further detail!

Three Use Cases to Navigate Modern Data in eDiscovery

In litigation, knowing the full picture is the only way to effectively represent your clients. The only problem is most of the story is often stored on electronic devices like smartphones, laptops, or tablets.

While eDiscovery can be dated back to 1981 and the first substantial use of email in litigation (Governors of United State Postal Service v. United States Postal Rate Commission), integrating newer, modern data types like text messages, computer activity, and financial data, has been a bit more challenging. These challenges relate back to how eDiscovery has historically worked and why modern data sources don’t fit nicely into that process. 

When eDiscovery was introduced with email and electronic documents as the primary source of information, simple messages and documents were sufficient to tell the story in a linear document review workflow. But, with sophisticated technology like Slack, chat applications and smartphone messaging where communications occur in real time, the conversion to documents for review hinders a proper evidence analysis.

Making sense of all that data only works when it is presented in the way it was originally communicated. The old documentation process simply doesn’t provide the insight you need to leverage modern data in litigation.

Case Study 1: Tackling Disparate Modern Data from Multiple Sources

No matter how small or large your case is, reviewing modern data can be challenging. Between smartphones, laptops, social media apps, and other connected devices, there’s a plethora of data to sift through to find the evidence you need to support your case. This process becomes even more complicated when the data is presented through the lens of traditional eDiscovery meaning, in traditional document format. What once worked for simple electronic communications no longer tells the whole story within complex, real-time and editable messaging technologies like WhatsApp, Slack and social media.

So what happens when you have to produce data from hundreds of international sources, and need it to tell the story of what actually happened? Let’s look at a case study of a construction company who had to do exactly that.

The Problem:

One of the largest construction companies in the world required the collection of modern data from 300 international sources. While the sheer number of sources was a challenge in itself, the real difficulty was working with disparate data from so many different sources.

Each business unit within the company used different technology so data had to be collected from a vast number of sources – local desktops, laptops, smartphones, tablets, and backup servers.

Plus, because so many BYOD devices were used, legal, data privacy, IT, and risk & compliance departments had to be consulted throughout the collection and review process to ensure no U.S. or international privacy laws were broken.

The Solution:

Ultimately, our client needed to understand who said or did what, and when. Basic documents with communications from readily available sources wouldn’t be enough, because they couldn’t easily identify the critical timeline of events or the intentions of each party. In the end, CloudNine ESI’s actor normalization function was the key to finding the evidence needed.

The Results:

By matching specific individuals to different aliases and phone numbers, attorneys were able to identify a handful of photos shared from the vast amount of data collected that proved the construction company was at fault. These photos were presented to the court in the form of inline bubble messaging that was easy to read and view.  To learn more about this use case, click here.

Case Study 2: Overcoming the Personal Device eDiscovery Challenge

There’s an expected, inherent trust between a company and its employees which means employees typically won’t do work that’s a conflict of interest with their current employer. Unfortunately, that trust is sometimes broken by actors that take advantage of their position.

The Problem:

When a heavy equipment manager became the target of a moonlighting case that cost his company money, attorneys were discouraged when they couldn’t find any evidence of wrongdoing. There were no documents, emails, or invoices to be found through traditional eDiscovery.

The Solution:

Fortunately, the key to the case was the manager’s smartphone.

By gaining access to his phone, attorneys were able to secure tens of thousands of text messages directly related to the case. This helped them discover how he operated his illegal side hustle. They also learned he was sharing confidential, copyrighted, and proprietary information through photos sent via text message.

The Results:

Through CloudNine ESI Analyst, attorneys were able to create conversation threads which were easy to review and produce. These threads not only helped them identify other involved parties, but let them produce messages, including embedded images, videos, GIFs, and emojis.

Without the ability to review and analyze the bad actor’s smartphone data, the case likely would not have gone forward.  

To learn more about this use case, click here.

Case Study 3: Protecting Company Data with Modern eDiscovery

The average American holds 12 jobs in their lifetime so it’s safe to say you will lose employees from time to time. Whether purposeful or accidental, the odds are good their personal devices will contain confidential or proprietary information when they walk through the door for the final time.

So what if you could examine their devices and remove all sensitive material before they left?

The Problem:

An employee spent six months working from home on a personal laptop before announcing his resignation to work for a competitor. If the employee was allowed to leave without a device review, he’d likely be leaving with documents that would benefit both him and his new employer.

Whether he would ever used those documents or not, chances are he’d find himself in the middle of a long, expensive trade secrets case which would also impact his new employer.

The Solution:

The representatives of the employee’s current company needed a way to access his personal laptop and identify any confidential or proprietary documents to be destroyed before he went to work for their competitor. They sought out a solution to easily identify these risks to protect their company, the employee and the employee’s future company.

The Results:

With CloudNine ESI Analyst, company representatives were able to access his personal laptop, create a chain of custody and review the data found on it. This allowed them to find confidential and proprietary data and remove it before the employee left for his new position, protecting all parties involved.

By doing this in advance, you preserve the data and protect it without relying on your employees to remember if they have sensitive information on their devices or not.

To learn more about this use case, click here

CloudNine ESI Analyst – A Modern eDiscovery Solution for Modern Data Review

While most law firms, corporations, and LSPs are challenged to review modern data through traditional eDiscovery tools, they struggle to pull the true value out of the data. Each text and corporate chat message are recreated as stand-alone documents, leaving you to piece them all together like a giant legal jigsaw puzzle with missing pieces and others that simply don’t fit the storyline.

With a robust and flexible modern eDiscovery tool like CloudNine ESI Analyst, you have access to alternative data to help you put the puzzle together through linear storytelling that creates a digital trail of evidence, including some of these popular sources:

  • Text messages (SMS and MMS)
  • Call logs
  • Voicemails
  • Messenger applications (Slack, Teams, WhatsApp, Messenger, etc.)
  • Computer activity
  • Financial transactions
  • Geolocation

Modernize your investigations and litigation by effectively managing the data in a single platform instead of wasting time managing a menagerie of documents in siloed systems.

Every case is unique and requires you to find the facts and context to tell the complete story. Contact CloudNine and learn how we can help you leverage all the data to get to the truth of the matter. Contact us to learn more.

Modern Data Discussions by Leading Experts at The Master’s Conference in DC

Last week, CloudNine Senior Director Rick Clark, VP Rob Lekowski and industry thought leaders convened in Washington, DC for The Master’s Conference first in-person event since early 2020. The two-day event tackled the latest challenges in eDiscovery, cybersecurity, and information governance. Managing modern data was the most popular recurrent topic with four distinct panels on the subject.

Smartphones, collaboration apps, and social media platforms all store a plethora of relevant information and is where today’s most important evidence resides. By avoiding or mismanaging this evidence, lawyers miss out on critical insights. So, how should legal teams incorporate modern data into investigations? Rick Clark addressed this question and more during the panel titled “Telling The Full Story: Leveraging the Data Between the Documents” with panelists Dave Rogers, Kroll; Kevin Albert, PAE; and Sonya Judkins, T-Mobile.

Here are three key takeaways from the panel discussion:

Modern data types can no longer be ignored – Emails and traditional documents are always going to be a part of discovery and investigations, but key data has moved away from these platforms. Conversations in Slack, MS Teams, device chat applications and text messages are additional communications needed to follow the conversation. Nowadays, modern data expands above communications into geolocation, social media posts, user activities and offer the largest insights. Recent case decisions have proven that judges are open to admitting modern data so long as the evidence is relevant and properly authenticated.

 Data shouldn’t be treated like documents – One reason why legal teams avoid modern data is linear document review. Imaging and exporting modern data leads to issues like missing metadata, families, threads, and file types. This method also requires legal teams to review evidence without any threading, deduplication, or link-analysis tools. Instead, large volumes of data are analyzed document by document. Linear document review is tedious, inefficient, and time-consuming but most important is legal teams who use linear document review also run the risk of overlooking important details. By opting for link analysis, litigants can connect various data points together to find relevant information faster.

“There just isn’t a good solution out there” – NOT TRUE – Four panels at the Master’s Conference discussed the challenges of modern data, but only Rick Clark’s panel offered a solution. CloudNine ESI Analyst is the only software that renders modern data in a near-native state. The platform uniquely offers users the ability to ingest and investigate multiple data sources within a single platform. Attendees of the CloudNine breakout session were given a full demonstration of ESI Analyst’s capabilities. Through timelines and 24-hour threads, ESI Analyst enables native analysis of communications, transactions, and computer activities.

Missed the Washington, DC event? Join us May 18th, 2022 for the next Master’s Conference in Chicago, Illinois.

Click here to learn more about how CloudNine ESI Analyst can help you manage your modern data.

BlueStar Accelerates Modern eDiscovery with ESI Analyst – CloudNine Podcasts

It’s a challenge to produce relevant evidence for large cases, especially when they feature non-traditional data types. JSON and PST formats simply don’t do modern data justice. The unwieldy files don’t possess threading or deduplication options. Instead, large amounts of irrelevant data are stretched across a multitude of pages and folders. Finding a team to manually review that data slows production speeds and raises discovery costs. It’s time to stop forcing a square peg into a round hole.

As the CTO and Managing Partner at BlueStar, Jeremy Schaper has seen an uptick of non-traditional data in the last five years. He and his team found CloudNine’s ESI Analyst while searching for an eDiscovery solution to process both traditional and modern data types. Jeremy joined Rick Clark for our CloudNine 360 Innovate Podcast to discuss how BlueStar leveraged ESI Analyst in large cases involving SMS, Slack, and Microsoft Teams data.
Click here to listen to the podcast and learn more.

The Challenges of Modern Discovery – CloudNine Webinar

In the past, attorneys relied on printed pages and forensic imaging to produce and review traditional documents. Neither method is capable of telling the whole story. By treating data as documents, legal teams are unable to draw context from metadata, families, and threads. Static documents also don’t permit the deduplication or isolation of messages at the individual level. These shortcomings lead to slowed review speeds, excessive redactions, and the loss of relevant information.

Since then, the eDiscovery landscape has broadened to encompass modern data types such as text, geolocation, and social media data. When exported by other eDiscovery providers, the data is displayed in unwieldy spreadsheets and JSON files. Lawyers who opt to export modern data face many of the same challenges as they would with traditional discovery measures. As an alternative, a lawyer may try to produce modern ESI in the form of screenshots. Screenshots are mistakenly viewed as an easier production form because they offer clear images of conversations and provide details such as contact names and messaging times. However, several judges have rejected their admission in court due to authenticity concerns. Nowadays, it’s very easy to fabricate text conversations.

As the amount of modern ESI grows, developing an efficient and defensible discovery process becomes paramount. Rob Lekowski and Rick Clark from the CloudNine team joined Kevin Thompson from the Chicago Bar Association to discuss how CloudNine ESI Analyst uniquely tackles the pitfalls of modern discovery. Rob and Rick also provided insight into common questions such as:

  • How should legal teams deal with deleted documents?
  • What are the estimated costs and duration times for small, medium, and big cases?
  • Can you still collect evidence with CloudNine ESI Analyst if you don’t have access to the physical device?
  • How should an attorney negotiate keyword searches with opposing counsel?

To learn how to process and review modern data types in a single platform, watch the webinar here.

CloudNine’s LegalWeek 2022 Recap

Last week, the CloudNine team visited New York City to provide virtual and in-person demos during LegalWeek 2022. Rick Clark, Robert Lekowski, Clint Lehew, and Jess Moore were able to share the capabilities of CloudNine ESI Analyst with over 50 attendees.

As the industry’s only near-native investigative platform, CloudNine ESI Analyst simplifies the discovery of mobile, chat, social, and geolocation data from collection to production. Through our platform, users can filter, search, and tag items at the individual level. Messages can also be viewed through our 24-hour thread feature which increases review speeds by permitting the numbering, tagging, and production of individual messages while displaying the full context of a conversation. The key difference between ESI Analyst and traditional review is our way of processing modern data. Traditional review turns all data into documents without providing sufficient means for filtering and searching conversations. Each message or thread must be reviewed page by page. By rendering messages and media inline, ESI Analyst allows legal teams to piece evidence together at a faster rate.

During LegalWeek, the CloudNine team was able to speak to our clients directly and learn how our platform changed their tactics on approaching data and case strategies. Clients like Phil Hodgkins raved about the user-based pricing and clarity that ESI Analyst offers in telling the whole story. While conducting an internal investigation, Phil’s team found that ESI Analyst saved time and yielded better insights than two traditional review platforms. Since then, Phil has encouraged lawyers to stop cramming mobile data into document-based spaces.

“If [our clients] start talking about mobile data [and getting] into the nuts and bolts of a laptop or any device, we immediately start talking about your tool. It allows you to gain insights much more quickly than putting the data into a typical review space” – Phil Hodgkins, Director of Data Insights and Forensics at Kroll. To learn more about Phil’s experiences with ESI Analyst, click here.

Missed out on CloudNine’s LegalWeek demos? Book a demo today to learn how our software simplifies and accelerates modern data discovery.

Inaugural Symposium on eCrime – Dealing with Multiple Data Sources

Studies show that the average person generates about 100 megabytes of data per minute. While most people leverage technology for work and personal activities, it can also be a tool for criminal offenses. On February 28, 2022, the Henry C. Lee Institute of Forensic Science held a virtual symposium on e-crime. The symposium covered topics such as cell phone forensics, email investigations, and deep fakes. CloudNine Senior Director Rick Clark was featured on a panel alongside Amber Schroader, CEO of Paraben Software, and Christa Miller, managing editor at Forensic Focus. The panel addressed how data from multiple sources can aid an investigation or discovery workflow.

Panel Discussion Points:

  • Concerns from stakeholder perspectives (particular focus on HR, legal, and IT teams)
  • Case studies involving modern data in criminal cases
  • Data privacy and ownership
  • The “human” element of the generation and interpretation of data

Managing multiple data sources doesn’t have to be stressful. To address your concerns in anticipation of your next investigation, click here.

Discover the Power of ESI Analyst During LegalWeek 2022

The past two days have been a blast for the CloudNine team. From now until Friday, March 11, CloudNine is offering in-person and virtual demos while we visit New York during LegalWeek 2022. We would love to see you there as we reconnect with long-time clients and welcome new faces. The CloudNine team is also eager for the opportunity to showcase our latest eDiscovery innovation, ESI Analyst.

Modern discovery is more than documents, it’s about telling the story. Nowadays, emails and Microsoft Office files aren’t enough to piece a narrative together. Large amounts of information can be obtained from financial transactions, geolocation data, social media activity, text messaging, and more. Through customer feedback and client experiences, we recognized how taxing modern data types could be without the right tools. As an emerging solution for modern investigations, ESI Analyst uniquely offers users the ability to ingest and investigate multiple data sources within a single platform. CloudNine’s recent acquisition of ESI Analyst allows us to provide our customers with an in-depth solution for collecting, processing, and reviewing modern data.

Ready to learn more about our latest updates and solutions? There’s still time to schedule a demo. Virtually or in-person, our team is excited to provide demonstrations on the latest integration between CloudNine Review and ESI Analyst. Meetings will also feature updates on CloudNine Review’s other integrations with LAW, Concordance, and Explore via CloudNine’s Discovery Portal. Click here to book a demo before the end of LegalWeek. Or click on the banner below to request a virtual demo later this month.

Managing the Unpredictability of eDiscovery Costs

Client fees are the lifeblood of the legal industry which means unpredictability isn’t congruent to the financial stability of a successful law firm. This means your eDiscovery document review solution can be as much of a liability as it is an asset when striving to remain profitable.

As every case differs in the volume and type of data collected, processed, and reviewed, the costs associated with it can be unpredictable. Without a balanced and consistent cost structure, the result can lead to an undesirable profit loss.

When eDiscovery was first utilized in the late 1990s, it was only in special cases involving email correspondence. Today, the American Bar Association (ABA) estimates that eDiscovery accounts for more than 80% of costs.  That translates roughly to $42 billion a year, with 70% of costs directly associated with document review.

Today’s eDiscovery has evolved further to include device data derived from multiple sources which can quickly inflate expenses and severely impact your operating budget.

At CloudNine , we are dedicated to guiding you towards eDiscovery cost recovery through our streamlined and optimized data solutions; read on for more of our tips to getting to the truth and your revenue goals more efficiently.

Get to The Truth Faster: The Biggest Challenges to Profitable eDiscovery

Controlling eDiscovery costs and charging your clients appropriately comes with certain challenges.

eDiscovery Insourcing vs Outsourcing: The profitability between these two options isn’t always black and white. There are a variety of factors when considering if outsourcing eDiscovery is the right choice for you, including:

  • What pricing models do vendors offer?
  • Are there additional fees?
  • How do hosting costs change over time?
  • Does the vendor own their technology or do they lease it?
  • What’s the full extent of capabilities the vendor has to offer?

By understanding the hidden costs of outsourcing, you can determine if it will allow you to balance cost and functionality effectively.

Delays in Court Proceedings: According to an article in the Washington Post, district attorneys are facing some of the longest case backlogs in living memory due to the COVID-19 pandemic. These delays mean more costs for longer hosting and storage times for important eDiscovery data, especially when being billed by the gigabyte.

Unpredictable Timing: The Sixth Amendment to the U.S. Constitution guarantees a person accused of a crime the right to a speedy trial. That means by federal law, a criminal case must proceed to trial within 70 days of indictment. However, felony trials can sometimes linger for well over a year.  The unpredictability of time between indictment and trial means costs can run higher than expected.

Managing Multiple Vendors and/or Systems: With many vendors specializing in different features and functions, it’s difficult to find a one-stop shop for all your eDiscovery solution needs. To compensate, you’ll need to engage with different vendors resulting in more contracts, more fees, and more time wasted learning how to operate the different systems.

By using a single solution to collect and assemble multiple modern data types, you can better retain the relevant context and timeline to tell the whole story. Putting together all the pieces of the puzzle becomes simpler, faster, and more strategic.

Making eDiscovery Costs More Predictable: A consistent cost recovery model can help predict and recuperate many eDiscovery expenses, but you’ll want to evaluate the pros and cons to identify the model best suited for your firm.

Examples of common cost recovery models include:

Billable Hours: The majority of law firms traditionally charge clients the billable hours they spend performing processing and project management. This model results in the least amount of pushback from clients as they’re paying strictly for the attorneys’ time. However, this can become less profitable if your law firm is forced to host its eDiscovery data long-term due to delays in court proceedings.

Billable Hours + Hosting Fees: To compensate for increased expenses, your law firm can add hosting fees to billing statements in addition to billable hours. However, clients often push back as they may not view hosting fees as actual legal work. These fees, usually charged per gigabyte, can help you recoup eDiscovery costs, but only if the client is willing to pay.

Third-Party Vendor Style: Another option for cost recovery is to invoice your clients with line items similar to how a third-party eDiscovery vendor would operate. You can include billing for individual items such as:

  • The number of gigabytes processed
  • The volume of data hosted
  • Any analytics applied to the data
  • Any licensing fees for software used

While some clients may be familiar with this model based on their experience with eDiscovery vendors, others may balk at these types of expenses. Learn more about how to optimize your eDiscovery cost recovery by downloading our eBook: Optimize eDiscovery Cost Recovery: 6 Steps to Make Your Review Process More Profitable.

Streamline with CloudNine. Optimize eDiscovery in Minutes.

As a proven leader in eDiscovery, CloudNine has provided innovative data collection and review solutions for hundreds of law firms and legal service providers since 2002.

Regardless of the type of cost recovery model you choose, CloudNine’s eDiscovery platform delivers a complete and flexible suite of solutions at a predictable and affordable price. Some of the benefits include:

  • SaaS Hosting for All Data – CloudNine’s SaaS offering allows analysis and review of all modern data types to include email, text messages, corporate chat applications, and geolocation.
  • Data and Storage Control – Right-size your data by culling it upfront to reduce your storage needs and control your costs.
  • User-Friendly Solutions – Every CloudNine solution is easy to use and operates on a self-service basis including smartphone collection data.
  • Dedicated Support – Our services teams are always available if you need additional support.
  • Flexible Storage – Optimize your spending whether you choose our all-in storage option or choose to pay for storage as needed.
  • Low Overall Pricing – Get predictability and affordability without compromise and leverage the features you need without paying for the ones you don’t.

Improve and optimize your eDiscovery by simplifying and streamlining the process. You’ll make it easier on your clients and more profitable for your firm.  Reach out and book a demo to  learn how CloudNine can make your eDiscovery most cost-efficient.

Perin Discovery Streamlines Workflow Through ESI Analyst: CloudNine Podcasts

For legal teams, the race to production may seem never-ending. The journey begins with some data mapping to discern who owns the data and where it is located. Once the identification process is successful, legal teams are often stopped by the first roadblock. They need to find a vendor that can collect modern data types such as text messages, tweets, and videos. After the data is collected, another roadblock stands in the way. A second vendor is needed to carry out review and production. Stopping and restarting between each step is frustrating and time-consuming, yet few LSPs offer means for a continuous workflow.

Recognizing this issue, Peter Smith and Erin Perczak launched Perin Discovery to provide a one-stop shop for both digital forensics and eDiscovery. The co-founders joined Rick Clark for our 360 Innovate Podcast to explain how they leverage ESI Analyst to engage their clients in a smooth workflow. To learn how our platform has improved their data and case strategies, visit this link: https://cloudnine.com/webcasts/perin-discovery-podcast/?pg=ediscoverydaily/collection/perin-discovery-streamlines-workflow-through-esi-analyst-cloudnine-podcasts