Category Archives: Case Study

June 17, 2025 · 2:56 PM

X1 Enterprise Is the Gold Standard for Data Separation in M&A Matters

By John Patzakis and Charles Meier

X1 is the Gold Standard in Data Separation

Corporate mergers and acquisitions are complex enough on their own — but when a deal involves the divestiture of an entire business unit or a carve-out of specific departments, the stakes for separating data correctly and efficiently become even higher. Legal and IT teams must identify and surgically separate emails, documents, and other unstructured electronic information to ensure that the right data goes to the acquiring party — and that what must be retained remains secure and compliant with privacy and legal requirements.

This data separation exercise is notorious for being time-consuming, extremely expensive, and highly disruptive. This is because traditional methods require heavy lifting by IT teams and service providers, endless back-and-forth with custodians, and mass data collections that literally double the risk. Worse yet, Microsoft Purview, with its known throttling and low throughput challenges for M 365 data, is not up to the task for data separation matters that invariably involve at least dozens of terabytes. These inefficiencies all lead to severe regulatory risks, runaway costs, and critical delays.

There is, however, a far better way — X1 Enterprise. Several major corporations have recently employed X1 Enterprise in high-stakes data separation matters. Once completed, the comments from our customers are the same: There was no other way they could have done it without spending millions of dollars on time-consuming and disruptive services.

Data Separation Is Not Just Another eDiscovery Project

Unlike standard eDiscovery, a divestiture-driven data separation project must carve out large volumes of live, operational data while the business continues to run. Legacy tools and processes require copying and moving the entire subject data set to a separate repository for indexing and searching — adding huge costs, time delays, and operational risk.

X1 Enterprise’s game-changing advantage lies in its distributed micro-indexing architecture and true index-in-place capability. This unique approach allows organizations to instantly search, categorize, and separate or otherwise remediate massive volumes of data where it resides — without duplicating and exporting entire data sets to third-party servers for processing.

In practical terms, this means:

Lightning-Fast Search: X1 Enterprise creates lightweight, local micro-indexes on endpoints and servers across the organization. Search results come back in seconds, no matter where the data lives — on laptops, file shares, or cloud repositories such as M365.

Minimal Disruption: Because the data stays in place, there is no need to duplicate or move sensitive content, minimizing the risk of data leakage, avoiding the bottlenecks that come with data copying and migration for centralized processing, and enabling the actual remediation to be infinitely more effective by working on the live data set. How do you execute data separation when you are working off a stale copy of the data for the categorization effort? The short answer: Up to millions of dollars in manual services to go back to the “original data” and manually separate the data for each employee and their respective data sources.

Scalability and Control: Whether the divestiture involves hundreds or thousands of custodians across geographies, X1 Enterprise scales seamlessly while giving legal and IT teams centralized control and real-time oversight.

Defensible Process: Legal teams can generate audit trails, reports, and logs to demonstrate a precise and defensible chain of custody, which is critical for regulatory and contractual compliance.

The Bottom Line: Much Faster, with Dramatically less Cost and Risk.

When time is money — and delays can put entire deals at risk — organizations cannot afford cumbersome, legacy eDiscovery workflows for carve-out data separation projects. X1 Enterprise’s innovative architecture empowers legal, compliance, and IT teams to execute precise data separations faster, with dramatically lower cost and business impact.

For any organization facing a merger, acquisition, or divestiture, X1 Enterprise is not just an upgrade — it is the modern standard for high-stakes data separation and governance.

Learn more about how X1 Enterprise can streamline your next M&A project. Schedule a demo today at sales@x1.com or visit  www.x1.com/solutions/x1-enterprise-platform.

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Filed under Best Practices, Case Study, Cloud Data, compliance, Corporations, Data Audit, ECA, eDiscovery & Compliance, Enterprise eDiscovery, ESI, GDPR, Information Access, Information Governance, Information Management, m365, Preservation & Collection, Records Management

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February 25, 2025 · 9:34 AM

True Index-in-Place Capability for Global Enterprise eDiscovery and Information Governance Only Possible with Distributed Micro-Indexing Architecture

By John Patzakis and Chas Meier

As legal and compliance teams grapple with exponential data growth, the need for faster, more efficient eDiscovery has never been greater. One key trend emerging from the 2025 State of Industry Report by eDiscovery Today is the growing demand for in-place indexing, with 15.5% of respondents citing it as a critical priority. But achieving true ‘index-in-place’ without bulk data transfers or excessive infrastructure costs—requires a fundamentally different architecture: distributed micro-indexing.

Unlike traditional eDiscovery tools that rely on centralized crawling and bulk data transfers, X1 Enterprise’s distributed micro-indexing architecture allows organizations to search, analyze, and collect data directly at the source—without moving vast amounts of information to a separate processing environment. This means faster insights, lower costs, and reduced security risks.

However, with this capability being highly valued, many vendors have parroted this messaging but have offerings that do not qualify as true index-in-place. Unlike traditional enterprise search or eDiscovery platforms that rely on centralized indexing (e.g., crawling, copying, and transferring all the data into a single repository), X1’s micro-indexing distributes the workload. It creates small, efficient indexes at the data source—whether a user’s laptop, email server, or a cloud source such as Microsoft 365 —and unifies search results on-demand. Transferring data in bulk to a central appliance or server farm via a crawling agent or Robocopy function does not qualify. A true index-in-place using distributed micro-indexes uniquely enables scalability, targeted collection and minimizes security and data governance risks in eDiscovery and information governance matters.

Earlier this year, a Fortune 500 company faced a massive eDiscovery and GDPR compliance challenge: indexing and searching over 70 terabytes of data across Microsoft 365 and on-premises sources—all without disrupting operations. With X1 Enterprise, they accomplished this in just a few weeks—a feat impossible with traditional solutions that rely on slow, centralized processing.

X1’s unique approach is based upon distributed, micro-indexing search and collection capabilities. Below are the top ten benefits of this architecture tailored to eDiscovery and enterprise data governance and how it differs from alternative approaches.

  1. Rapid, In-Place Data Identification: Legal teams can locate relevant documents across endpoints, cloud sources, and network drives instantly—without waiting for slow, centralized crawls. X1’s micro-indexing creates lightweight, decentralized indexes at the endpoint level (e.g., individual laptops, servers, or cloud accounts).
  2. Real-Time Search Across Distributed Systems: Execute complex, Boolean-rich searches across terabytes of data in Microsoft 365, OneDrive, SharePoint, and beyond. X1 enables real-time, federated searches across up to hundreds of terabytes of multiple data sources (e.g., Microsoft 365, local drives, email archives) from a single interface, leveraging micro-indexes updated at the source.
  3. Minimized Over-Collection Risks: X1’s Micro-indexing allows precise targeting of relevant data, minimizing the need to collect entire datasets for review. X1’s granular indexing supports instantaneous keyword searches and metadata filtering at the source.
  4. Lower eDiscovery Costs: By eliminating the need to transfer and reprocess massive datasets, X1 slashes infrastructure and vendor fees. By indexing and searching data in-place (without moving it to a central repository), X1 nearly eliminates reliance on third-party processing tools and expensive manual services, with dramatically reduced time to review.
  5. Optimized M365 eDiscovery Support: Avoids Microsoft Purview throttling, supports modern attachments, and enables cost-effective, high-speed data access. Each custodian is assigned an individual micro-index which enables X1 to achieve unmatched throughput, support modern attachments without premium licensing, address inactive mailboxes and more.
  6. Massive Scalability: X1’s micro-indexing distributes the workload on a parallelized basis, allowing the index and searching of hundreds of terabytes of data in-place at speeds not seen before in the enterprise eDiscovery and information governance industry. Micro-indexes are updated incrementally and in real-time as new data comes in, rather than requiring batch copying and re-indexing of an entire corpus.
  7. Support for Remote and Hybrid Workforces: X1’s endpoint indexing works seamlessly on distributed devices, ensuring data from remote employees or cloud platforms is readily accessible without requiring physical access.
  8. Proactive Compliance & Risk Monitoring: Instantly identify PII, unencrypted sensitive files, and policy violations across the enterprise. With micro-indexes updated in real-time, X1 allows organizations to monitor for policy violations (e.g., PII exposure, unencrypted sensitive files) across endpoints, fileshares and M365 accounts instantly.
  9. In-Place Remediation and Governance: As the data remains in place, remediation is effectively and accurately applied at scale. This contrasts to other “copy and move” processes that are merely working off-site with copies of your data, rendering effective remediation efforts extremely costly and burdensome, if not impossible.
  10. Data Minimization and GDPR Compliance: X1’s capabilities directly map to the GDPR’s proportionality and data minimization requirements. In contrast, tools that require full disc imaging or bulk copy and transfer for basic eDiscovery collection are extremely problematic.

Conclusion
For legal, compliance, and IT teams struggling with slow, expensive, and inefficient eDiscovery workflows, distributed micro-indexing is the future. X1 Enterprise’s unique in-place search ensures rapid results, reduced costs, and ironclad compliance—without moving or duplicating sensitive data. If your organization relies on Microsoft 365, remote workforces, or high-volume data environments, X1 provides the speed, scalability, and security you need.

Ready to Learn More?
Discover how X1 Enterprise can revolutionize your eDiscovery and compliance strategy. Schedule a demo today at sales@x1.com or visit www.x1.com/solutions/x1-enterprise-platform.

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February 12, 2025 · 12:22 PM

X1 Enterprise Successfully Passes GDPR-Mandated Data Protection Impact Assessment

By John Patzakis

The European Union (EU) General Data Protection Regulation (GDPR) requires that subject organizations ensure and demonstrate the protection of personal data under their control. GDPR Article 35 mandates that when implementing new data collection technologies or engaging in a major new project involving significant data collection, an organization must perform a Data Protection Impact Assessment (DPIA).

Recently, a Fortune 500 company with global operations successfully implemented X1 Enterprise to address their eDiscovery and information governance requirements throughout the EU region, involving both Microsoft 365 and on-premises data sources. This implementation required the vetting of X1 Enterprise by auditors and the internal Data Protection Officer through an extensive DPIA process, which X1 passed. The effort provides important industry insights into how our Fortune 500 customer leveraged X1’s unique, on-premises index-in-place and targeted search and collection features, as well as other data minimization capabilities, to meet the DPIA requirements.

The EU provides official guidance and a checklist for conducting an Article 35 DPIA. Among the key requirements is the consideration of the “current state of the technology” in the area and that the technology and collection processes have adequate “proportionality measures” in their collection capabilities to “ensure data minimalisation.” If processes and technology engage in overly broad data collection, the guidance suggests considering alternative technologies and methods.

The team at our Fortune 500 customer emphasized the following unique data minimalization capabilities and features of X1 Enterprise in their DPIA:

  1. Index and Search Data In-Place. X1’s proprietary micro indexes enable the searching of data on laptops, file servers and Microsoft in-place so that only the potentially relevant data is collected for eDiscovery and data audits, which fulfills the GDPR’s proportionality requirements. In contrast, tools that require full disc imaging for basic eDiscovery collection are extremely problematic.

    As the court said in In re Ford Motor Company, 345 F.3d 1315: “[E]xamination of a hard drive inevitably results in the production of massive amounts of irrelevant, and perhaps privileged, information…” Even worse, the collected data is then re-duplicated, often multiple times, by the examiner for archival purposes. And then the data is sent downstream for processing, which results in even more data duplication. Load files are created for further transfers, which are also duplicated. Notably, EU guidance for a DPIA analysis requires that organizations consider alternative data collection technologies and methods that have better “proportionality measures” to “ensure data minimalization.”
  2. Blind Searches and User Enabled Review. Using X1 Enterprise, an administrator can run detailed system wide searches and receive a detailed search result report without having access or possession of the target data. Instead, the administrator can direct X1 to first present the search results to the end-user employee to review and apply tags to identify personal, relevant or non-personal data, thereby applying clear and detailed consent to the subsequent collection of any relevant information.
  3. Segmentation of Data Regions vs. Creation of Central Data Lakes. X1 can be deployed behind an organizations’ firewall or their own private cloud instance in the EU. Each custodian/employee is associated with a single micro-index. This allows X1 to target searches to specific EU counties and segments of users. This contrasts to archiving or other eDiscovery tools that require bulk copying and intermingling of all user data to a central location, where additional back-up copies are made, all which directly run afoul of the data minimalization and proportionality requirements of the GDPR.
  4. Delete Data In-Place. GDPR requires the deletion of non-compliant on demand. Purging data on managed archives does not suffice if other copies are on laptops, unmanaged servers and other unstructured sources. X1’s on-premises distributed architecture uniquely enables the systematic deleting of data in place.
  5. Platform to Enforce GDPR and Privacy Policies. In addition to asserting X1 met the requirements and standards under GDPR mandated DPIA, our Fortune 500 customer noted as further justification in their DPIA that they also planned to utilize X1 Enterprise to enforce privacy policies and provisions under the GDPR. X1 Enterprise is an ideal platform to respond to Data Subject Access requests, proactively audit data sources to identify and remediate personal information, as well as systematically purge unneeded data that may contain personal information of EU data subjects.

    Ready to Learn More?
    For companies navigating complex information governance and eDiscovery requirements, including those involving M365, the  X1 Enterprise Platform ensures compliance while protecting privacy. By implementing X1 Enterprise, organizations can not only reduce costs and save valuable time but also gain a strategic advantage in managing their information governance needs. For a demonstration of the X1 Enterprise Platform, contact us at sales@x1.com. For more details on this innovative solution, please visit www.x1.com/solutions/x1-enterprise-platform.

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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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June 15, 2022 · 12:33 PM

Industry Experts: Proportionality Principles Apply to ESI Preservation and Collection

By John Patzakis

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. Lawyers that take full advantage of the proportionality rule can greatly reduce cost, time and risk associated with otherwise overbroad eDiscovery production. In a recent webinar, eDiscovery attorney Martin Tully of Redgrave LLP, addressed how to use processes and best practices to operationally attain this goal, particularly in the context of preservation and collection. In addition to being a partner at the Redgrave firm, Tully is currently the chair of the Steering Committee of the Sedona Conference Working Group on Electronic Document Retention and Production (WG1), providing additional import to his comments on the subject.

During the webinar, Tully noted that the “duty to preserve is directly aligned with what is within the scope of discovery….so if something is not within the scope of discovery – that is its either not relevant or its not proportional to the needs of the case — then there should not be an obligation to preserve it in the first place.” Tully discussed at length the recent case of Raine Grp. v. Reign Capital, (S.D.N.Y. Feb. 22, 2022), which holds that under FRC 26(a), parties “have an affirmative obligation to search for documents which they may use to support their claims or defenses.” In meeting these obligations, the court provided that a producing party may utilize search methodologies, specifically mentioning search terms. Tully explained that the court—in addressing the concept of reasonable, proportional discovery under the Rules – provides that producing parties are obligated to search custodians and locations it identifies on its own as sources for relevant information as part of its obligations under Rule 26, but that such identification and collection efforts should be proportional.

Further to these points, Tully weighed in on overbroad practice of full-disk imaging, noting that it should not be the default practice for eDiscovery collection: “Too often there is a knee jerk approach of ‘let’s just take a forensic image of everything – just because.’” According to Tully, alternative and more targeted search and collection methods were more appropriate for eDiscovery and can better effectuate proportional efforts: “Indexing in-place is key because it doesn’t just preserve in-place and reduce costs, but it can give you insight (into the data) to further justify your decision not to collect it in the first place, or if you need to, you are in much better shape to go back and collect the data in a tailored and focused way.”

Co-presenter Mandi Ross, CEO of Insight Optix also provided keen insight, outlining her typical workflow applying the aforementioned proportionality concepts through custodian and data source ranking and keyword searching performed in an iterative manner to identify key custodians, data sources, and the potentially relevant data itself. To effectuate this, Mandi noted that the enterprise eDiscovery collection and early data assessment process should enable a targeted, remote, and automated search capability, with immediate pre-collection visibility into custodial data.

In fact, both Tully and Ross emphasized in their comments that none of the cost-saving, targeted collection efforts permitted under the Federal Rules can be realized without an operational capability to effectuate them. Ideally, the producing party can employ a defensible, targeted, and iterative search and collection process in-place, prior to collection to effectuate the proportional discovery process approved by the court in this decision. However, without such a capability, the alternative is an expensive, over-collection effort, where the data is searched post collection. Enabling the search iteration and targeted collection upstream brings dramatic cost savings, risk reduction, and other process efficiencies.

A recording of the webinar on proportionality can be accessed here.

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