Mastering Ediscovery with This Comprehensive Guide From Everlaw: EDiscovery Best Practices

Why It Matters

The guide equips legal teams with actionable best practices and cutting‑edge technology insights, helping them reduce costs, mitigate risk, and stay competitive in a data‑intensive litigation environment.

Key Takeaways

• Guide covers full eDiscovery lifecycle.
• Highlights AI and generative AI applications.
• Emphasizes duty to preserve and legal hold triggers.
• Details TAR 2.0 continuous active learning workflow.
• Discusses challenges of big data volume, velocity, variety.

Pulse Analysis

The rapid expansion of electronically stored information has transformed litigation, making eDiscovery a critical, resource‑intensive function for law firms and corporate legal departments. Traditional manual review processes struggle to keep pace with the sheer volume, velocity, and variety of data sources—from email archives to collaboration platforms like Slack and Teams. As a result, practitioners are turning to structured frameworks and technology solutions that can streamline preservation, collection, and analysis while ensuring compliance with evolving privacy regulations.

Everlaw’s new guide provides a comprehensive roadmap that blends foundational legal principles with advanced technological tactics. It demystifies the duty to preserve, outlines the meet‑and‑confer requirements of FRCP Rule 26(f), and dives deep into predictive coding, specifically the TAR 2.0 continuous active learning model that eliminates static training phases. The guide also showcases how generative AI can accelerate document review, automate privilege logging, and improve summarization accuracy, all while emphasizing prompt engineering and security safeguards.

For the broader legal market, the guide signals a shift toward greater automation and AI integration across the eDiscovery workflow. Firms that adopt these best practices can expect lower review costs, faster early case assessments, and stronger defensibility against data‑privacy challenges. Moreover, the discussion of emerging data sources—such as IoT devices and agentic AI—prepares organizations for the next wave of discovery demands, positioning Everlaw as a thought leader in the evolving eDiscovery landscape.

Mastering Ediscovery with this Comprehensive Guide from Everlaw: eDiscovery Best Practices

Mastering Ediscovery: Your Guide to Rules, Workflows, and Advanced Tools · by Doug Austin, eDiscovery Today

Everlaw has published a comprehensive guide for mastering eDiscovery. The guide, titled Mastering Ediscovery: Your Guide to Rules, Workflows, and Advanced Tools, is available for download here. Below is an overview of the chapters:

• Chapter One – Introduction to eDiscovery

  Explains the evolution of the discovery phase from English common law to modern eDiscovery, the impact of electronically stored information (ESI), and key terms such as legal holds and metadata.

• Chapter Two – Data Preservation and Legal Holds

  Discusses the duty to preserve data when litigation is “reasonably foreseeable,” and outlines events that trigger this duty (e.g., demand letters, internal investigations).

• Chapter Three – ESI Protocols and the Meet and Confer Process

  Covers the FRCP Rule 26(f) meet‑and‑confer process, which provides a structured environment for parties to address eDiscovery challenges and negotiate ESI exchange terms.

• Chapter Four – Document Review

  Describes why document review is the most discussed and costly phase of eDiscovery, including challenges such as human error, privilege protection, and regulatory compliance.

• Chapter Five – Early Case Assessment

  Defines Early Case Assessment (ECA) as a strategic process for rapidly investigating evidence, and distinguishes it from Early Data Assessment (EDA) per the Sedona Conference Glossary.

• Chapter Six – Predictive Coding

  Introduces Predictive Coding (Technology‑Assisted Review, TAR) and explains the preferred TAR 2.0 (Continuous Active Learning) workflow, which eliminates a fixed training phase.

• Chapter Seven – eDiscovery Software

  Highlights the importance of selecting appropriate eDiscovery software to handle data from sources like Slack and Teams, and notes the role of AI and predictive coding in review efficiency.

• Chapter Eight – Generative AI’s Impact on eDiscovery

  Explores how generative AI automates tasks such as document review acceleration, summarization, and privilege logging, emphasizing prompt engineering, security, and quality‑control checkpoints.

• Chapter Nine – Current eDiscovery Considerations and Challenges

  Addresses the “Three V’s” of Big Data (volume, velocity, variety), mobile device and personal‑device privacy hurdles, and complexities introduced by enterprise collaboration apps (e.g., hyperlinked files).

• Chapter Ten – Conclusion and Additional Resources

  Summarizes seven key trends shaping the future of eDiscovery, including expanding use cases, emerging data sources (IoT, GenAI), and increased automation via Agentic AI, while stressing compliance with data‑privacy and cross‑border transfer rules.

The guide spans 151 pages and can be read chapter‑by‑chapter online or downloaded for offline reference.

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Disclosure: Everlaw is an Educational Partner and sponsor of eDiscovery Today.

Disclaimer: The views expressed are solely those of the author and do not necessarily reflect the views of the author’s employer, partners, or clients. eDiscovery Today provides general educational information and is not a substitute for legal advice from a qualified attorney.