The Shift to Continuous eDiscovery: What Always-On Readiness Looks Like

Continuous eDiscovery uses AI tools to help human teams review and process legal data. It streamlines workflows to be ongoing and multi-phased rather than linear, ensuring that stages can overlap whenever most efficient.

ComplexDiscovery reports that 60-80% of all eDiscovery spending goes toward review. Cutting those costs is essential, and making the most of your funds is just as important. Using a continuous eDiscovery platform makes review easier and allows for quality early case assessment eDiscovery.

Read on to learn how organizations can adopt continuous eDiscovery processes to remain prepared for litigation, audits, or investigations at any time.

What Is Continuous Active Learning?

Continuous active learning (CAL) is an advanced eDiscovery method. Also known as continuous eDiscovery, this form of technology-assisted review (TAR) uses AI constantly.

The AI trains an algorithm in tandem with the human developers who code documents and create metadata. When this happens, the machine learning model can predict:

• How relevant other documents are to eDiscovery
• Which documents should be tagged for review
• What datasets custodians should look into deeply

This means real-time updates as the algorithm reviews data. It's quicker and more cost-effective since relevant information is easy to prioritize. This lets legal teams prepare for litigation or court cases more quickly since large datasets are organized better.

How Does Continuous eDiscovery Work?

As with all AI models, continuous eDiscovery with CAL starts with a human being. A legal review professional starts coding documents within their database as relevant vs not relevant.

As they do that, the pre-established AI algorithm tracks their movements. It makes note of what the reviewer has marked important and creates a model for determining documents' relevance based on those human selections.

The human reviewer keeps coding documents, and the AI keeps tabs at all times. Because of this constant monitoring and continuous learning, the AI gets faster and smarter.

Then, the algorithm ranks every document by importance and tells the reviewer what to prioritize.

At a certain point, the model will become advanced enough for people to apply it to an entire data set. This eliminates the need for costly and time-consuming manual review.

The Benefits of Continuous eDiscovery SaaS Software

Real-time data analysis with CAL ensures that all information is accurate and updated. This is better able to produce defensible results that legal teams can offer up in court. Experts can provide better testimony that stands up in the face of cross-examination and questioning, which helps professionals have better case outcomes.

These benefits begin at the get-go since AI starts as an early case assessment eDiscovery tool. CAL accelerates review processes early in the game and only gets faster as the machine model updates over time.

This saves money because the time needed for manual review decreases!

CAL is especially important for larger datasets. This is because it can tag and index a lot of material at once while organizing it over time.

Information Week reports that 64% of companies hold over a petabyte of data, and 41% have at least 500 petabytes of information stored within their databases.

This encompasses a lot of different files from various sources. Luckily, Reveal's AI-powered tool makes reviewing this information easier by providing the best CAL eDiscovery strategies out there.

How Does Reveal Prioritize Continuous eDiscovery and Retention?

Reveal software is made with continuous active learning tools. First, teams can use drag-and-drop features to move data from various applications into an all-in-one dashboard. Connectors sync to several data sources, including:

• Google Docs
• Microsoft 365
• Outlook
• Teams
• Slack
• Clio
• Dropbox

The platform supports over 900 file types and can be configured to even the most complex data sets!

All your data goes into one easily searchable location. Once that's done, AI tools scan the integrated information to find keywords and subjects relevant to your eDiscovery investigations.

The AI will then add tags based on:

• The application that generated the data
• Where data was originally stored
• File types for relevant information
• Subjects and content discussed in documents
• People involved in correspondence (recipients, senders, etc.)

As it sifts through and tags datasets, the AI becomes smarter and more efficient.

A Model That Grows With You

AI isn't just for searching up data. Beyond recognizing keywords, an intelligent AI system will also pick up context within documents. It will infer meaning from your requests to ensure that it pulls all relevant hits.

This is because AI grows when it spots patterns. It can use context to find information that a human reviewer might overlook, which allows for a more nuanced and comprehensive review.

Reveal's AI also assists in review by understanding users. It sees how people tag and correct information by reviewing the history of datasets. This allows for better, quicker growth.

AI also becomes stronger when you ask it to help you conceptualize data. It can normalize unstructured data by putting it into consistent file formats. Eliminating duplicates is also a simple task for CAL models.

You can also streamline review by asking Reveal to:

• Generate AI summaries of complex documents
• Transcribe audio and video files
• Take the text out of images it's embedded in
• Produce charts and graphs for easy visualization
• Create heatmaps and clusters of complex documents
• Help you build a case with existing information

Everything you do helps Reveal become stronger and better tailored to your legal team's individual needs.

Streamline Data Management With Top-Notch Legal Technology

Now that you know the ins and outs of continuous eDiscovery, it's time to streamline your data management workflow ASAP. Reveal offers scalable packages to law firms and corporate legal teams of all sizes.

Our suite of comprehensive, AI-driven tools is made especially to meet the needs of those going through all steps of the discovery process. Continuous learning models ensure that AI operates at maximum efficiency, so review teams can rely on auto-filtering and AI-generated insights to present a compelling case during litigation processes.

As of summer 2025, we've been granted High Performer awards in both mid-market and business uses as well as Grid Leader recognition. Schedule a demo of our technology to learn more about digital transformation in eDiscovery!