January 31, 2023 · 12:11 PM

A.I. Bot ChatGPT Explains How Corporate Legal Can Streamline eDiscovery Processes

By John Patzakis

Over the weekend I was about to write a blog post on how corporate legal departments can streamline and improve their internal eDiscovery processes. I instead asked ChatGPT to write it. ChatGPT did a better job of it. So If anyone needs me this week, I will be at the beach.


Here is the full transcript:


My Prompt: Please write a memo explaining how corporate legal departments can streamline their eDiscovery processes to reduce costs and improve compliance.


Response from ChatGPT:

Subject: Streamlining eDiscovery Processes for Corporate Legal Departments

Dear All,

As technology continues to advance and the amount of electronic data generated by companies grows, the eDiscovery process can become increasingly complex and costly. However, there are steps that corporate legal departments can take to streamline their eDiscovery processes and reduce costs while also improving compliance.
1. Invest in eDiscovery Technology Solutions: Utilizing technology solutions, such as automated data collection and review tools, can help reduce the time and cost associated with manual review processes. These solutions can also improve accuracy and consistency in data collection and review, reducing the risk of non-compliance.
2. Establish Clear Protocols and Guidelines: Having clear protocols and guidelines in place for data collection and preservation will help ensure that relevant data is preserved and collected in a timely manner, reducing the risk of spoliation and ensuring compliance with legal obligations.
3. Employee Training: Regular training for employees on best practices for managing electronic data will help ensure that data is properly preserved and collected, reducing the risk of non-compliance.
4. Regular Process Reviews: It is important to regularly review and update processes to ensure they align with changes in regulations and technology. This will help ensure that eDiscovery processes remain efficient and effective, reducing costs and improving compliance.
5. Consider Alternative Service Providers: Utilizing alternative service providers, such as managed eDiscovery service providers, can help reduce costs while also improving compliance. Negotiating service level agreements that meet both cost and compliance goals will ensure that eDiscovery initiatives are managed in a cost-effective and compliant manner.
6. Utilize Project Management Techniques: Using project management techniques, such as setting clear goals, tracking progress, and monitoring budgets, will help keep eDiscovery initiatives on track and within budget, reducing costs and improving compliance.
In conclusion, streamlining eDiscovery processes can help reduce costs and improve compliance. By utilizing technology solutions, establishing clear protocols and guidelines, training employees, regularly reviewing processes, considering alternative service providers, and utilizing project management techniques, corporate legal departments can ensure that their eDiscovery processes are efficient and effective.

If you have any questions or would like to discuss these recommendations further, please do not hesitate to reach out.

Best regards,
[Your Name]

Couldn’t have said it better myself. And if you agree with ChatGPT’s recommendation to invest in automated collection technologies to reduce costs and reduce the risk of non-compliance, please see this information about our X1 Enterprise Collect platform.

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Filed under Best Practices, Cloud Data, Corporations, eDiscovery, Enterprise eDiscovery, ESI

January 10, 2023 · 11:43 AM

Move to the Left and Targeted Collection Featured Widely as a Key 2023 eDiscovery Trend

By John Patzakis

It is prediction season for trends in the eDiscovery space for 2023. While many good eDiscovery scribes have published their prognostications in recent days, the annual predictions and overall analysis from Doug Austin in eDiscovery Today are invariably insightful. As a top industry analyst, Austin is in constant contact with eDiscovery executives and professionals and thus has a good finger on the industry pulse.

One of his key predictions this year, which notably appears in several trending 2023 forecasts, centers around the upstream focus on information governance and targeted collection. “I’m hearing more legal and eDiscovery professionals than ever talk about the importance of information governance, early data assessment (EDA) and targeted collections in discovery,” reports Austin, who then poses a very good question about the ramifications of this trend: “What happens when eDiscovery professionals are no longer routinely collecting the entire data corpus of custodians to sort out downstream? The growth of data for eDiscovery hosting providers to host slows dramatically – which jeopardizes growth in hosting revenue that is based on gigabytes (GBs) online.”

There is a lot going on in terms of takeaways from this paragraph. The “collect everything and sort it out later” is still the dominant model for service providers and, as Austin points out, it can be difficult for them to pivot from this economic model. However, this highlights a key reason why many in house legal departments are now routinely deploying in-house collection and EDA solutions. There are significant cost savings and efficiencies to be gained by narrowing the data funnel upstream before the data is sent out for data hosting. And this approach is favored by the courts in applying the principles of proportionality now ensconced in the Federal Rules of Civil Procedure, with a wealth of case law establishing that ESI preservation efforts should be reasonable, proportionate, and targeted to only relevant information, as opposed to being overly broad and unduly burdensome.

While there is keen awareness of proportionality in the legal community, attaining the benefits requires the ability to operationalize workflows as far upstream in the eDiscovery process as possible. The case law and the Federal Rules provide that the duty to preserve only applies to potentially relevant information, but unless you have the right operational processes in place, you’re losing out on the ability to attain the benefits of proportionality. And with the proliferation of enterprise cloud data sources, it’s important that holistic and targeted collections encompass Microsoft 365 data as well as laptops and file shares.

To answer this unmet critical need, X1 has added MS 365 data connectors to our X1 Enterprise Collect platform. X1 Enterprise Collect provides users the unique ability to search and collect MS 365 data in-place. X1’s optimized approach of iterative search and targeted collection enables organizations to apply proportionality principles across both cloud and on-premise data sources with clear and consistent results for effective eDiscovery. The search results are returned in minutes, not weeks, and thus can be highly granular and iterative, based upon multiple keywords, date ranges, file types, or other parameters. This approach typically reduces the eDiscovery collection and processing costs by at least one order of magnitude (90%).

The X1 Enterprise Collect Platform is available now from X1 and its global channel network in the cloud, on-premise, and with our services available on-demand. For a demonstration of the X1 Enterprise Collect Platform, contact us at sales@x1.com. For more details on this innovative solution, please visit www.x1.com/x1-enterprise-collect-platform.

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Filed under Best Practices, Cloud Data, Corporations, eDiscovery, Enterprise eDiscovery, Information Governance, Preservation & Collection, proportionality

December 6, 2022 · 10:23 AM

Significant Microsoft 365 eDiscovery Challenges Require a New Approach

By John Patzakis

The adoption of cloud-based Microsoft 365 (“MS 365”) by enterprises continues to grow exponentially, with the company recently reporting 300 million monthly active users, and the addition of over 100 petabytes of new content each month. There is no question that MS 365 is now a major data source for eDiscovery, second only to file-shares and laptops, and as such provides challenges to every legal and eDiscovery practitioner.

While MS 365 includes built-in eDiscovery tools in the Security and Compliance Center, many users look to third party alternatives due to the high cost, perceived concerns over the accuracy of search results, and other key challenges. However, most non-MS eDiscovery tools collect from MS 365 by simply making bulk copies of data associated with individual accounts, and then attempting to transfer that data en masse to their own proprietary processing and/or review platform. This problematic approach is counter-productive to the very purpose of why you put data in the cloud.

Such an effort is very costly, time consuming, and inefficient for many reasons. For one, this bulk transfer triggers data transfer throttling by Microsoft, causing significant time delays. But the main problem is that clients who are investing in MS 365 do not want to see all their data routinely exported out of its native environment every time there is an eDiscovery or compliance investigation. Organizations are fine with a targeted set of potentially relevant ESI leaving MS 365. What they do not want is a mass bulk export of terabytes of data at great expense because eDiscovery and processing tools need to first broadly ingest that data in their disparate platform in order to even begin the indexing, culling and searching process.

Additionally, organizations, especially larger enterprises, rarely house all or even most of their data within MS 365, with hybrid cloud and on-premise environments being the norm. MS 365 eDiscovery tools can only address what is contained within MS 365. Any on-premise data, including on-premise Microsoft sources (SharePoint, Exchange) cannot be readily consolidated by MS 365, and neither can data from other cloud sources such as Google Drive, Box, Dropbox, etc. And of course, laptops and file-shares are critical to eDiscovery collections and are also not supported by the MS 365 eDiscovery tools, with Microsoft indicating that they do not have any plans to address all of these non-MS 365 data sources.

So, eDiscovery software providers need to have a good process to perform unified search and collection of MS 365 and non-MS 365 sources. To achieve requisite efficiency and the minimization of data transfer, this process should be based upon a targeted search and collection in-place capability, and not simply involve mass export of data out of MS 365 for downstream processing and searching.

To answer this unmet critical need, X1 has added MS 365 data connectors to our X1 Enterprise Collect platform. X1 Enterprise Collect provides users the unique ability to search and collect MS 365 data in-place. X1’s optimized approach of iterative search and targeted collection enables organizations to apply proportionality principles across both cloud and on-premise data sources with clear and consistent results for effective eDiscovery. The search results are returned in minutes, not weeks, and thus can be highly granular and iterative, based upon multiple keywords, date ranges, file types, or other parameters. This approach typically reduces the eDiscovery collection and processing costs by at least one order of magnitude (90%).

The X1 Enterprise Collect Platform is available now from X1 and its global channel network in the cloud, on-premise, and with our services available on-demand. For a demonstration of the X1 Enterprise Collect Platform, contact us at sales@x1.com. For more details on this innovative solution, please visit www.x1.com/x1-enterprise-collect-platform.

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Filed under Best Practices, Cloud Data, Corporations, Data Audit, ECA, eDiscovery, eDiscovery & Compliance, Enterprise eDiscovery, ESI, Information Governance, Information Management, OneDrive, Preservation & Collection, SharePoint

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November 8, 2022 · 12:58 PM

10 Unique and Compelling Features of X1 Social Discovery

by John Patzakis

The legal field is seeing very strong demand for social media evidence collection software and services. However, Facebook, the most widely used social media platform, recently rolled out a completely new interface and data format to all of their 2.4 billion users. This caused a major disruption of eDiscovery and compliance workflows. In response, social media evidence collection tools either exited the market, changed their model to services, or provided flat file screen shots as their output.

Flat file screen shots of social media are of very limited value, as what they generally entail is a screenshot pdf image file without searchable text or metadata, other than what is visible on the image itself. For this reason, X1 made a substantial investment in research and development, so that our users would have native, post-level collection and parsing to ensure accuracy, key metadata collection, court authentication, and evidentiary completeness of the collected data with X1 Social Discovery. Nothing short of those capabilities are acceptable.

As a result of these efforts and ongoing support, users of X1 Social Discovery enjoy numerous benefits and advantages not available with any other tool on the market. To best illustrate this, we have compiled a list of the top 10 unique and differentiating features of X1 Social Discovery. While X1 Social users enjoy many additional compelling features and benefits from the software, this is a list of the unique strengths of the software that no other provider on the market can claim.

  1. True Native file Collection of Social Media Items and Web pages. Flat file pdfs are not searchable and do not support review, authentication, and analysis workflows. X1 collects native html at the post level. The court in Edwards v. Junior State of America Foundation, No. 4:19-CV-140-SDJ, (US Dist. CT, E.D. TX 2021), specifically ruled that only html or JSON social media collections are defined as native collection. Flat PDFs are not.
  2. Robust Post-Level Metadata Capture. X1 Captures over a dozen unique item level metadata fields. Other tools only record general URLs of the bulk collection, a hash of the entire “all or nothing” bulk pdf export containing up to hundreds of individual posts, with no individual hash values or metadata fields specific to any of those posts.
  3. Instant Searchability of Collected Items. X1 Social Discovery features a patented, powerful search across all collected items in a case. Foreign language and emojis are also searched. No Optical Character Recognition (OCR) is required (which is inaccurate and out of context). Other tools collect by converting searchable native originals to non-searchable PDF images, and then apply OCR to the bulk export. While OCR is acceptable when the original source is in a non-searchable image format, this intentional degradation from native to image, which then requires OCR, is not consistent with best practices and raises defensibility concerns.
  4. Federated Search and Review. With X1, multiple social media and web feeds are searched, sorted, and reviewed in a unified manner. No other tools on the market have an integrated review capability.
  5. Post Level Collection, Filtering and Production. The ability to tag, sort, authenticate (with their own hash value), and produce individual posts with X1 is essential for an efficient and effective workflow. Other tools require “all or nothing” production & hash of the flat PDF output.
  6. Analytics Support. Only X1 collects full text & post-level metadata needed by analytics engines. Using other tools is a decision to not use analytics on your case for social media evidence.
  7. Integrated Processing and Load File Generation. Only X1 can filter and export individual social media items with all associated comments and web pages directly into a load file. This saves extensive time and eliminates need for expensive additional processing required by other “less expensive’ tools.
  8. Deep Integration with Relativity for Review. X1 custom-developed a Relativity .RAP file that enables social media data to be displayed natively – at the post level — in full context in Relativity, the same as it appears in X1 Social Discovery. All metadata is overlayed, and the comments are kept in line and in context. Importantly, each post collected by X1 is treated as an individual record in Relativity, instead of the bulk export from other tools being a single record. This enables efficient review as well as robust data analytics of social media evidence in Relativity.
  9. Simultaneous Collection and Review. X1 can run multiple collections at the same time. For instance, a web crawl collection, a Facebook and a YouTube collection can be run at the same time. Data can be reviewed and analyzed immediately as it populates.
  10. Scheduled Monitoring and Search of Websites. With X1, websites can be automatically searched with targeted collection on a scheduled basis. Web and YouTube pages with specific keyword hits can be collected in a targeted manner. X1 features a web crawler (not just one page captures), that can collect thousands of pages from a single website. This supports monitoring and robust compliance workflows.
  • (tie) Flexible Cloud or On-Premise Deployment. X1 Social can be installed on-premise, or hosted by X1, your law firm, or a 3rd party service provider. This provides critical deployment flexibility demanded by government and legal industry users.

X1 Social Discovery is the only eDiscovery solution applicable to these numerous, critical features and benefits. To learn more about this important functionality, please contact us for a technical briefing.

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Filed under Authentication, Best Practices, eDiscovery, Enterprise eDiscovery, ESI, Preservation & Collection, Social Media Investigations, Social Media Metadata

November 1, 2022 · 11:42 AM

Proportionality in eDiscovery is Ideal, but Difficult to Realize Without an Optimized Process

By John Patzakis

(Originally published October 24, 2022 by JD Supra and EDRM)

Image: Kaylee Walstad, EDRM

Proportionality-based eDiscovery is a goal that all corporate litigants seek to attain. Under Federal Rule of Civil Procedure 26(b)(1), parties may discover any non-privileged material that is relevant to any party’s claim or defense and proportional to the needs of the case. Litigants that take full advantage of the proportionality rule can greatly reduce cost, time and risk associated with otherwise inefficient eDiscovery.

While there is a keen awareness of proportionality in the legal community, realizing the benefits requires the ability to operationalize workflows as far upstream in the eDiscovery process as possible. For instance, when you’re engaging in data over-collection, which in turn incurs extensive labor and processing costs, the ship has largely sailed before you are able to perform early case assessments and data relevancy analysis, as much of the discovery costs have already been incurred at that point. The case law and the Federal Rules provide that the duty to preserve only applies to potentially relevant information, but unless you have the right operational processes in place, you’re losing out on the ability to attain the benefits of proportionality.

However, traditional eDiscovery services typically involve manual collection, followed by manual on-premises hardware-based processing, and finally manual upload to review. These inefficiencies extend projects by often weeks while dramatically increasing cost and risk with purposeful data over-collection and numerous manual data handoffs. The good news is that solutions and processes addressing the first half of the EDRM involving collection and processing are now far more automated than they were even a few years ago.

Recently EDRM hosted a webinar addressing these issues – “Operationalizing your eDiscovery Process to Realize Proportionality Benefits” – and more specifically, as the title reflects, explored how to operationalize your eDiscovery process to achieve lower costs, improve early case strategy, realize faster time to review and reduce overall legal risk.

Here are some key takeaways from the webinar:

  • A detailed legal analysis was provided highlighting the case of Raine Group v. Reign Capital, (S.D.N.Y. Feb. 22, 2022), which applied proportionality at the point of identification and collection, not just production. The court endorsed the use of detailed and iterative keyword searches to identify and preserve potentially relevant ESI.
  • A demonstration was shown on how to enable detailed and proportional search criteria, applied in-place, at the point of collection. Such a capability is key to realizing the blueprint for targeted and proportional ESI collection outlined in Raine Group.
  • The speakers also discussed how organizations should move upstream to focus on information governance to reduce the data funnel as soon as possible. The new generation of eDiscovery technology in the areas of collection, identification, analytics, and early data assessment, enables enterprises to operationalize proportionality principles.

The webinar culminated with the notion that an optimized process that applies proportionality upstream at the collection and identification stage reduces the data volume funnel by as much as 98 percent from over-collection models, yet with increased transparency and compliance. A link to the recording from the webinar can also be accessed here.

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Filed under Best Practices, Case Law, Case Study, ECA, eDiscovery, Enterprise eDiscovery, ESI, Preservation & Collection, proportionality

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