How to Use AI for Discovery Review: A Practical Guide for Lawyers
Discovery review is one of the most time-consuming parts of litigation. Legal teams may need to sort through emails, files, chats, spreadsheets, and other electronically stored information to find what matters, protect privileged material, and build a defensible review process.
AI can make that work faster and more manageable. Used well, it can reduce manual review, improve consistency, and help teams focus on the documents most likely to matter. This guide explains how to use AI for discovery review, what to look for in a tool, and which platforms are commonly used by law firms and legal departments.
Why AI Matters in Discovery Review
Modern litigation often involves large volumes of data. Manual review alone can slow matters down, increase client costs, and make it easier to miss important evidence.
AI helps legal teams handle discovery more efficiently by using technologies such as natural language processing and machine learning to analyze, categorize, and prioritize documents.
Key benefits include:
- Faster review timelines: AI can process large datasets much more quickly than manual review alone.
- Lower review costs: Automating part of the workflow can reduce the number of hours spent on first-pass review.
- More consistent results: AI can apply the same logic across large datasets, which helps reduce reviewer inconsistency.
- Better issue spotting: AI can surface likely relevant documents, communication patterns, and other useful themes earlier in the process.
- More time for higher-value work: Lawyers and review teams can spend less time on repetitive sorting and more time on strategy, privilege decisions, and case analysis.
The most effective approach is usually not “AI instead of lawyers.” It is AI plus human oversight.
Best AI Tools for Discovery Review
Different tools are built for different matters, team sizes, and budgets. Below are several widely used options in the legal discovery market.
1. RelativityOne
What it does:
RelativityOne is a cloud-based e-discovery platform with tools for processing, review, analytics, and case management. Its AI features include Technology Assisted Review (TAR), active learning, clustering, concept searching, and visualization tools.
Why it is useful:
It is built for end-to-end e-discovery and is well suited to large matters with substantial document volumes. Its AI features help prioritize likely relevant documents and reduce the amount of material that needs manual review.
Best fit:
Large law firms and corporate legal departments handling complex litigation or investigations.
Pros:
- Broad functionality
- Strong AI and analytics capabilities
- Scales well for large datasets
- Strong security and compliance features
- Integrates with other legal tech tools
Cons:
- Can be complex for smaller teams
- Higher cost than more focused tools
- May require more implementation support
2. Logikcull
What it does:
Logikcull is an e-discovery platform focused on making discovery simpler and more accessible. It uses AI to help automate document review, identify privileged material, and categorize documents by content.
Why it is useful:
It reduces manual effort and is easier to adopt than many enterprise platforms. Teams can upload, process, and review data with less setup and less technical complexity.
Best fit:
Small and mid-sized firms, solo practitioners, and in-house legal teams looking for a straightforward tool.
Pros:
- Easy to use
- Fast setup and processing
- AI-driven coding and insights
- More affordable for smaller teams
- Good collaboration features
Cons:
- Less customizable than enterprise platforms
- Smaller integration ecosystem
- Less focus on deep forensic analysis
3. DISCO
What it does:
DISCO is an AI-powered discovery platform with search, review, analytics, legal hold, and case management features. It uses TAR and predictive coding to help identify relevant documents more efficiently.
Why it is useful:
DISCO combines advanced functionality with a relatively user-friendly interface, which makes it useful for teams that want strong AI without a steep learning curve.
Best fit:
Law firms of all sizes that want a balanced mix of AI capability, usability, and case management.
Pros:
- Intuitive interface
- Strong search and relevance ranking
- TAR and active learning capabilities
- Solid customer support
- Good overall feature set
Cons:
- Can be more expensive than niche tools
- Smaller integration ecosystem than some larger vendors
- Performance may vary with very large datasets
4. Everlaw
What it does:
Everlaw is a cloud-native e-discovery platform with AI features for document review and analysis. It offers predictive coding, auto-categorization, concept clustering, and collaboration tools.
Why it is useful:
Everlaw is designed to make discovery easier for legal teams that need to work together across matters. It reduces the amount of manual review while keeping the workflow organized and accessible.
Best fit:
Medium to large firms and in-house teams that value collaboration and ease of use.
Pros:
- Strong user experience
- Collaborative workflow
- Useful AI and analytics features
- Fast search and processing
- Transparent pricing approach
Cons:
- Requires reliable internet access
- Fewer specialized forensic tools than some alternatives
- Less customization than some enterprise systems
5. Iris Data Solutions and Relativity Tools
What it does:
Within the Relativity ecosystem, specialized tools such as Relativity Trace and Relativity Review can help monitor communications, analyze documents, and identify patterns that may signal risk, compliance issues, or misconduct.
Why it is useful:
These tools go beyond standard relevance review. They can help teams spot communication patterns and potential issues that might not appear in a keyword-only review.
Best fit:
Corporate legal departments and firms handling compliance matters, internal investigations, or cases centered on large communication datasets.
Pros:
- Strong communication-pattern analysis
- Integrates with the broader Relativity environment
- Can help uncover issues missed by basic searches
- Useful for investigations and compliance reviews
Cons:
- May require more setup and data preparation
- Often priced as a premium solution
- Best used by teams with experience in configuring review workflows
6. X1 Discovery
What it does:
X1 Discovery offers tools for legal holds, collection, and e-discovery. Its AI features support data classification, document identification, and early review workflows.
Why it is useful:
It can help teams manage the early stages of discovery more efficiently by combining collection and initial review in one workflow.
Best fit:
Law firms and legal departments that want to streamline legal holds, collection, and early assessment.
Pros:
- Strong legal hold and collection capabilities
- Useful for early case assessment
- Streamlined interface
- Can reduce the need for multiple tools
Cons:
- Less advanced analytics than some larger review platforms
- AI review depth may be narrower than specialized TAR systems
- Integration should be checked carefully for complex workflows
How to Choose the Right AI Tool for Discovery Review
The best tool depends on the type of matter you handle, your budget, and how your team works.
Consider the following:
- Case complexity and data volume: Large, complex matters often need a platform like RelativityOne. Smaller matters may fit better with Logikcull or DISCO.
- Budget: Pricing may be based on storage, processing volume, user seats, or feature tiers. Make sure you understand the total cost, not just the headline price.
- Ease of use: If your team wants a simpler learning curve, choose a platform with a cleaner interface and stronger onboarding support.
- AI features: Some tools are better for TAR and predictive coding, while others are stronger for communication analysis, clustering, or early case assessment.
- Workflow integration: Check how well the platform fits with your document management system, practice management tools, and existing review process.
- Scalability: Choose a product that can support future growth if your matters become larger or more complex.
- Support and training: Good implementation support matters, especially when introducing AI into an established review workflow.
Pricing and Value Considerations
AI discovery tools can be priced very differently. Some are affordable for smaller teams, while enterprise platforms may require a larger commitment.
Common pricing models include:
- Subscription pricing: Monthly or annual fees, sometimes tied to user count or feature level.
- Per-GB pricing: Charges based on the amount of data processed or stored.
- Feature-based pricing: Higher-tier plans may include more advanced AI or analytics tools.
- Add-on costs: Some products charge separately for ingestion, support, advanced analytics, or additional modules.
When evaluating cost, look at value as well as price:
- Time savings: How much manual review time can AI reduce?
- Review efficiency: Can the platform help your team move faster without sacrificing quality?
- Risk reduction: Can it help avoid missed documents or inconsistent coding?
- Client impact: Faster and more efficient review can improve client satisfaction.
If possible, test the platform with a real matter or request a demo before committing.
How AI Helps in the Discovery Review Workflow
If you are trying to understand how to use AI for discovery review in practice, the workflow usually looks like this:
1. Collect and process the data
Bring in emails, documents, chats, and other ESI, then process it into a reviewable format.
2. Apply AI-assisted sorting
Use TAR, clustering, concept searching, or auto-categorization to group related material and surface likely relevant documents.
3. Prioritize review
Focus human reviewers on the documents most likely to matter, while AI helps push less relevant material down the queue.
4. Review for relevance and privilege
Lawyers or trained reviewers validate key documents, check for privilege, and make final responsiveness decisions.
5. Refine the workflow
Review results can be used to improve the model or adjust search logic as the matter develops.
Frequently Asked Questions About AI for Discovery Review
How accurate is AI compared with human reviewers?
AI can be very effective at repetitive review tasks and can often outperform manual review in speed and consistency. It is still best used with human oversight, especially for final privilege and relevance decisions.
Do I need to be a technology expert to use these tools?
No. Most modern discovery platforms are designed for legal professionals, not technical specialists. Basic e-discovery knowledge helps, but deep technical expertise is usually not required.
What types of documents can AI review?
AI can review emails, Word documents, PDFs, spreadsheets, presentations, and other common file types. OCR can also help make scanned images searchable.
Can AI help with privileged documents?
Yes. Many tools can flag potentially privileged or confidential material using rules, keywords, and machine learning. Human review is still important before final production.
Can AI assist with early case assessment?
Yes. AI can help identify themes, key custodians, timelines, and likely important documents early in the matter, which supports better strategy and planning.
Is AI use in discovery review acceptable from an ethical standpoint?
Generally, yes, when used competently and with appropriate supervision. Lawyers remain responsible for the work product, so AI should support professional judgment, not replace it.
Conclusion
AI is changing how discovery review gets done. For law firms and legal departments, it offers a practical way to reduce review time, control costs, and improve consistency across large datasets.
The right platform depends on your matter size, budget, team structure, and workflow needs. Enterprise teams may need a robust solution like RelativityOne, while smaller firms may prefer a simpler platform like Logikcull or DISCO. Everlaw, X1 Discovery, and specialized Relativity tools can also fit specific use cases.
If you are evaluating how to use AI for discovery review, start by matching the tool to your workflow. With the right setup, AI can help your team work faster, review more efficiently, and spend more time on the legal work that matters most.