Tag Archives: infogov

December 16, 2025 · 9:13 AM

AI Without Data Movement: X1’s Webinar Reveals the Future of Secure Enterprise AI

By John Patzakis

X1’s recent webinar announcing the availability of true “AI in-place” for the enterprise was both highly attended and strongly validated by the audience response. The session did more than introduce a new feature; it articulated a fundamentally different architectural approach to enterprise AI—one designed explicitly for security, compliance, and scalability in complex, distributed environments. Our central message was simple: enterprise AI adoption has been constrained not by lack of interest, but by architectural and security requirements that existing platforms have failed to address.

That reality was most powerfully captured in a quote shared on the opening slide from a Fortune 100 Chief Information Security Officer, which set the tone for the entire discussion:

“Normally AI for infosec and compliance use cases is a non-starter for security reasons, but your workflow and architecture is completely different. This allows us – all behind our firewall — to develop our own models that are trained on our own data and customized to our specific security and compliance use cases and deployed in-place across our enterprise.”

This endorsement crystallized the webinar’s core insight: AI becomes viable for the most sensitive enterprise use cases only when it is deployed where the data already lives, rather than forcing data into external or centralized systems.

The technical foundation that makes this possible is X1’s micro-indexing architecture. Unlike traditional platforms built on centralized, resource-intensive indexing technologies, X1 deploys lightweight, distributed micro-indexes directly at the data source. This allows enterprises to index, search, and now apply AI analysis without mass data movement. As emphasized during the webinar, centralized indexing is not just expensive and slow—it is fundamentally misaligned with how modern enterprise data is distributed across file systems, endpoints, cloud platforms, and collaboration tools.

The session then highlighted how this architectural distinction resolves a long-standing problem in discovery, compliance, and security workflows. Legacy platforms require organizations to collect and centralize data before they can analyze it, introducing delays, high costs, and significant risk exposure. X1 reverses that workflow. By enabling visibility and AI-driven classification before collection, organizations can make informed, targeted decisions—collecting only what is necessary, remediating issues in-place, and dramatically reducing both risk and operational overhead.

The discussion also demystified large language models (LLMs), explaining that while model training is compute-intensive, models themselves are increasingly commoditized and portable. Critically, LLMs require extracted text and metadata— processed from native files—to function. This aligns perfectly with X1’s existing capability, as text and metadata extraction are already integral to our micro-indexing process. AI models can therefore be deployed alongside these indexes, operating in parallel across thousands of data sources with massive scalability.

The conversation then connected this architecture to concrete, high-value use cases. In eDiscovery, AI in-place enables faster early case assessment and proportionality by analyzing data where it resides. In incident response and breach investigations, security teams can immediately scope exposure across distributed systems without waiting months for data exports. For compliance and governance, AI models can continuously identify sensitive data, enforce retention policies, and surface risk conditions that were previously impractical to monitor at scale.

In addition to a live product demo showcasing this new capability, we concluded the webinar with several clarifying points and announcements. First, we emphasized that X1 does not access, monetize, or host customer data. Also, AI in-place is not an experimental add-on but an enhancement to a proven, production-grade platform. And notably, there is no additional licensing cost for the AI capability itself—customers simply deploy models within their own environment. With proof-of-concept testing beginning shortly and production deployments targeted for April 2026, the webinar made clear that AI in-place is not a future vision, but an imminent reality for the enterprise.

You can access a recording of the webinar here, and to learn more about X1 Enterprise, please visit us at X1.com.

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Filed under Best Practices, Corporations, Cybersecurity, Data Audit, Data Governance, ECA, eDiscovery, eDiscovery & Compliance, Enterprise AI, Enterprise eDiscovery, ESI, Information Governance

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September 16, 2025 · 9:12 AM

X1 Expands Its Leadership in Microsoft Teams eDiscovery Collection

X1 Enterprise MS Teams Collection

By John Patzakis and Chas Meier

The rapid growth of Microsoft 365 has fundamentally changed the eDiscovery landscape. Among its most prominent data sources, Microsoft Teams now generates vast volumes of business-critical communications that must be identified, collected, and reviewed in litigation, regulatory, and compliance matters.

Yet most eDiscovery tools still rely on outdated methods: bulk copying massive amounts of sensitive data and transferring it to proprietary processing or review platforms. This approach is slow, costly, and disruptive. Bulk transfers frequently trigger Microsoft’s throttling controls, adding significant delays. More importantly, organizations that have invested heavily in Microsoft 365 do not want their data routinely exported out of its secure, native environment every time an eDiscovery matter or compliance investigation arises.

Recognizing these challenges, X1 has built upon its industry-leading Microsoft 365 collection capabilities to deliver unmatched support for Microsoft Teams—alongside OneDrive, Exchange, and SharePoint.

Key Benefits of X1’s Teams Collection Capabilities
• Precision targeting of Channels at scale – Quickly search all available channels, select, and target specific Teams channels, even in organizations with tens of thousands of them. This feature is not even available in Microsoft Purview!
• Granular control – Target individual custodians and message threads, avoiding unnecessary mass downloads.
• Contextual collections – Automatically include a designated number of preceding and subsequent messages, preserving conversational context.
• Seamless review integration – One-click upload of fully formatted in-context results directly into review platforms—no manual processing required.
• Unified approach – Search and collect across Teams, OneDrive, SharePoint, Exchange, laptops, and file shares from a single interface.
• In-place indexing – Leverage X1’s patented technology to index, search, and process data where it resides, eliminating reliance on expensive third-party processing.
• True automation – A software-based solution that reduces dependency on manual, service-heavy workflows.

No other independent software provider matches the speed, precision, and scalability of X1’s Microsoft Teams eDiscovery collection. Our customers consistently report significant gains in efficiency, cost savings, and defensibility compared to legacy approaches.

As Teams usage continues to surge, legal and compliance professionals need solutions that deliver targeted, defensible collections without the inefficiencies of bulk exports. X1’s enhanced Teams support ensures organizations can meet these demands with speed, accuracy, and minimal disruption.

Seeing is believing—watch our short demo video to experience X1’s Teams capabilities in action.

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Filed under Best Practices, Cloud Data, Corporations, ECA, eDiscovery, eDiscovery & Compliance, Enterprise eDiscovery, Enterprise Search, ESI, Hybrid Search, Information Governance, m365, MS Teams, OneDrive

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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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