AI Legal Document Review: A Buyer’s Guide for 2025

Legal professionals live in documents. Briefs, petitions, contracts, case law – each one demands precision, speed, and the ability to back every claim. Reviewing them is essential but expensive in hours, and deadlines rarely leave breathing room.

AI promises to ease that load, but “AI for lawyers” is a crowded label. Some tools only summarise or translate. Others draft 20-page petitions and pull citations from millions of cases. Choosing the right one starts with knowing how it will slot into your existing workflow.

In this article, we’ll look at what AI legal document review software actually does in practice, from intake to final draft, and highlight features that solve specific pain points – like multi-file uploads, compliance tracking, or AI-assisted case law search. You’ll also get a quick-hit checklist to match capabilities to your caseload, so you can cut evaluation time and move straight to a working solution. 

Benefits and capabilities of AI legal document review software

Most AI tools for law sound impressive in a demo. The real test is whether they help you perform tasks without adding new steps. When choosing your tool, focus on the day-to-day outputs that keep cases on track. 

Core tasks where AI for legal document review should deliver value:

• Triage: Quickly sort through large sets of emails, contracts, or filings to surface what’s worth a closer look.
• Search: Find the right clause, date, or fact without combing through hundreds of pages.
• Summarize: Turn dense rulings or multi-page exhibits into clear, scannable overviews.
• Extract facts/clauses: Pull out entities, key terms, or obligations for direct use in arguments or reports.
• Draft first versions: Generate a starting point for petitions, briefs, or statements of fact, using your templates and style.
• Translate: Produce accurate, word-for-word translations for evidence or filings in other languages.
• Organize: Rename, categorize, and sequence exhibits so nothing gets lost. 
• Package deliverables: Assemble complete, court- or agency-ready packets. 

Also, AI should be able to produce content in the formats lawyers actually use – memos for partners, timelines for hearings, privilege logs for productions, petition packets for USCIS, and redlined clauses for negotiations. If it can’t deliver work in these forms straight out of the tool, you’ll burn the time you saved reformatting and restructuring the output.

In the next section, we’ll focus on what matters in these features when applied to real lawyers’ workflows – to see which capabilities make a difference in practice. 

AI legal document review for litigation and investigations

In litigation and investigations, the first pass is often the heaviest lift – tens of thousands of documents that must be screened, tagged, and organized before any strategy work begins. Done manually, it can drain weeks from the timeline. The right AI tools should take on most of that burden. 

Common lawyers’ pain points:

• Management of large-scale first-pass reviews under tight deadlines.
• Identification and tagging of privileged material early in the process.
• Construction of timelines from scattered pieces of evidence.
• Drafting initial statements of fact without losing important nuance.

Helpful features:

• Bulk tagging and notes to speed up initial categorization.
• Entity extraction that automatically maps people, places, and dates.
• Custodian and thread views to follow the flow of conversations in emails or chats.
• Auto-summaries with citations so you can jump directly to the relevant source.
• Privilege term banks to flag sensitive material before it slips through review.
• Privilege log export that produces a court-ready format in one step.

Typical output:
A complete, brief-ready statement of facts and a fully organized index of all the supporting documents or evidence that will be submitted alongside a legal filing, hearing, or trial. 

AI legal document review for contracts and corporate law

Contract-heavy work is less about sheer volume and more about precision. Every clause needs to be correct, consistent, and aligned with both legal requirements and internal business rules. You need to scan for risk, check compliance with playbooks, and present changes in a way business teams can act on quickly.

Common pain points:

• Comparison of similar clauses across multiple agreements to spot subtle differences.
• Identification missing or non-standard terms that could introduce risk.
• Cross-checking that all language complies with internal playbooks or regulatory requirements.
• Creating redlines that clearly show changes without confusing non-legal readers.

Helpful features:

• Clause extraction for rapid review and comparison across contracts.
• Automatic highlighting of risk factors according to playbooks.
• Side-by-side comparisons to quickly see differences between versions.
• Summary sheets that translate legal risk into plain language for non-legal stakeholders. 

Typical output:
A clear, prioritized issue list with suggested replacement language – ready for negotiation, sign-off, or internal approval.

AI legal document review for immigration law

Immigration practices often center on assembling long, detailed petition letters backed by carefully ordered exhibits. The work is highly repetitive – similar templates, recurring document types, and multilingual evidence appear across many cases. The challenge is to keep accuracy and completeness high while moving at the speed clients and filing deadlines demand.

Common pain points:

• Drafting petition letters that can run 20+ pages.
• Collection, ordering, and labeling of dozens or hundreds of exhibits.
• Creating expert letters across multiple matters.
• Translating evidence while preserving precise legal meaning.
• Adapting templates for different visa categories without starting from scratch.

Helpful features:

• Bulk upload with auto-categorize and rename to instantly organize exhibits.
• Petition letter drafting based on firm-approved templates.
• Expert letter generation for repeatable, structured content.
• Word-for-word translation for multilingual evidence in one workspace.
• Packet preparation tools to assemble a court- or agency-ready submission.

Typical output:
A complete petition packet – letter, exhibits, and translations – ready for attorney review and immediate filing. 

Best AI legal document review tools

With dozens of legal AI platforms on the market, we narrowed the field to five of the most talked-about solutions and put their strengths and trade-offs under the microscope – here’s how they stack up.

CoCounsel Legal

CoCounsel is Thomson Reuters’ AI legal document analysis tool. At the core is Deep Research, a multistep agent that can draft a research plan, run authority checks, and surface the most on-point cases or statutes. CoCounsel also offers functionality within Word, where it suggests clause edits, inserts hyperlinks to governing law, and lets you pull Practical Law checklists without leaving the document. For litigators, an upload panel can help analyze complaints or motions, highlighting quoted law, spotting mischaracterizations, and flagging potential “hallucinated” citations. 

Pros

• Tight integration with Westlaw & Practical Law; minimal change management for firms already in that ecosystem.
• Word add-in embeds KeyCite, clause suggestions, and playbooks directly in documents.
• Built-in hallucination and misquote detection increases confidence in AI outputs.

Cons

• Subscription pricing requires or assumes Westlaw licenses; could duplicate costs for firms on Lexis.
• Research and drafting shine, but bulk doc handling (e.g., mass exhibit renaming) is limited.
• Less configurability than newer agentic systems; workflows largely follow Thomson-defined paths.

Harvey AI

Harvey markets itself as a “legal coworker” rather than a narrow tool. The platform runs on domain-specific large language models, then layers an agentic Workflow Builder that lets knowledge managers chain tasks (e.g: clause extraction → playbook check → precedent insertion) into one-click routines. Its Vault integration syncs iManage, SharePoint, or local drives, so drafting in Word pulls real firm precedents. In Harvey AI, each answer links to source passages and shows the agent’s decision path, so you can audit or tweak logic mid-stream.

Pros

• Highly configurable workflows; firms can encode their own playbooks and clause-banks.
• Deep Word integration: redline entire documents, rewrite sections, ask questions in place.
• Transparent “reasoning view” eases risk teams’ concerns about black-box AI.

Cons

• Flexibility means longer setup; non-technical users may need training to design workflows.
• Pricing is enterprise-oriented and can climb quickly with large knowledge bases.
• No built-in eDiscovery module – litigation teams still need a separate review platform.

Legora

Legora positions itself as a bespoke AI workspace designed “by lawyers, for lawyers.” Its hallmark is the Tabular Review engine: drop tens of thousands of PDFs and the system lines up clauses, dates, or entities in spreadsheet-like views for rapid scanning. A natural-language Workflow Builder turns firm standards – style guides, red-line rules, approval chains—into reusable agentic flows that think through tasks the way a senior associate would. Word add-ins handle inline drafting, precedent lookup, and translation without the browser toggle. 

Pros

• “Embed your DNA” approach: clause libraries, playbooks, and logic live inside every workflow.
• Large-scale review tables excel at fund documents, LPAs, or bulk NDAs.
• Strong DMS integrations (iManage, SharePoint) and source-cited outputs for auditability.

Cons

• Heavier on configuration; small teams may find the blank-canvas builder daunting.
• Newer ecosystem: fewer third-party plug-ins and learning resources than TR or Microsoft.
• Pricing tiers scale with user count plus workflow volume – costs rise on firm-wide rollouts.

Diligen

Diligen focuses narrowly on contract review, aiming to cut diligence hours rather than overhaul an entire workflow. Out of the box, its pre-trained models recognize hundreds of standard provisions – assignment, liability caps, change-of-control – across leases, vendor agreements, or NDAs. A side panel shows extracted clauses with one-click links to the source, while a project dashboard tracks review status across documents. Teams can train custom models on niche language (e.g., biotech licensing) in a no-code interface. Integrations with Clio, NetDocuments, and Box let firms keep files where they already live.

Pros

• Fast time-to-value: upload docs and see clause hits within minutes.
• Lightweight UI works for paralegals and junior attorneys—little training needed.
• Custom clause-training bridges gaps when reviewing industry-specific agreements.

Cons

• Limited to contracts; no litigation, research, or drafting modules.
• Extracts what’s present but offers minimal risk scoring or playbook enforcement.
• On-prem options lag behind cloud feature updates; security reviews can slow deployment.

Everlaw + EverlawAI Assistant

Everlaw is already a heavyweight in cloud eDiscovery; EverlawAI Assistant layers generative AI onto its review, analytics, and trial-prep suite. Everlaw AI generates coding suggestions, clusters topics, and provides instant summaries with sentiment and entity extraction. For storytelling, Storybuilder links evidence to outlines, deposition prep, and argument memos.FedRAMP and StateRAMP authorizations make Everlaw a go-to for public-sector matters. Every GenAI output is citation-anchored: click a statement and the underlying passage opens for verification, which reduces hallucination risk.

Pros

• End-to-end litigation stack from legal holds to trial boards.
• Scales to multimillion-document cases without choking search speed.
• Government-grade security plus transparent, source-grounded AI answers.

Cons

• Built for big matters; pricing and UI may feel heavyweight for small disputes.
• Drafting features live inside Storybuilder, not Word – may disrupt counsel who draft only in Microsoft.
• AI modules are add-ons; legacy Everlaw users must budget separately for Assistant seats.

AI legal document review buying guide

Choosing an AI legal document review platform isn’t about chasing the longest feature list – it’s about matching capabilities to the problems you need solved.

• If you triage thousands of emails or chats: Look for batch summarization, automatic entity timelines, and custodian/thread views to map conversations without manual sorting.
• If you assemble long petitions or packages: Prioritize bulk exhibit upload and handling, template-aware drafting, and in-platform translation so you can move from intake to filing without extra tools.
• If you compare contracts all day: Focus on clause extraction, playbook compliance checks, and side-by-side comparison views to flag risk and deviations instantly.

For any workflow, always confirm:

• How AI for document review handles private data—and whether it’s ever used to train public models.
• Whether it can export in the formats your team actually uses (Word, PDF tables, privilege logs).
• How quickly your team can get started with simple, non-disruptive onboarding.

When to consider custom AI legal software

Off-the-shelf AI legal document review tools cover a lot, but there are situations where custom-built software can give a law firm a sharper edge:

• Highly specialized workflows: If your matter types require steps or outputs no standard platform supports.
• Deep integration needs: You want the AI to work directly inside your DMS, CRM, or case management system without extra clicks.
• Unique data assets: Your firm has proprietary precedent libraries, clause banks, or research datasets that could power more precise AI outputs.
• Compliance and privacy mandates: You operate under regulations that require full control over hosting, model training, and data storage.
• Brand-specific client experience: You want client portals, reporting dashboards, or branded deliverables that reflect your firm’s identity. 

A custom solution lets you design for your exact process, connect with existing systems, and maintain full control over data handling – all while avoiding the compromises that come with general-purpose platforms. 

Example: VisaLaw.ai for immigration-specific workflows

Some custom or niche platforms focus on a single area of practice. VisaLaw.ai is one example – designed for immigration professionals who deal with high-volume, evidence-heavy matters.

Core capabilities include:

• Immigration-specific legal research and caselaw search.
• Document Q&A on firm libraries with secure “PrivateGPT”-style queries.
• Summarization and precise translation for multilingual exhibits.
• Petition letter drafting from templates (20+ pages).
• Bulk exhibit upload with auto-categorize and rename.
• Optional expert letter generation and packet assembly tools.

Apiko’s role: building Prompt.Law for VisaLaw.ai

When VisaLaw.ai needed a platform to host and search a large library of standardized legal prompts, they turned to us. The goal was to give immigration lawyers a structured, easy-to-navigate prompt database that could accelerate drafting and keep outputs consistent. 

Our AI software development company managed the entire project from design to delivery, building:

• A fully functioning Prompt.law website centered around an online database.
• Advanced data upload capabilities to handle complex prompt sets.
• Powerful search and browse tools so users can find exactly what they need, fast.

The result was a streamlined, accessible resource that fits perfectly into VisaLaw.ai’s broader workflow automation tools. 

Conclusion

AI for legal document review removes friction from the workflows that matter most to your practice. Whether you’re triaging evidence, comparing contracts, or assembling complex petition packets, the right platform should save time, deliver outputs in the formats you actually use, and fit into your team’s processes.

For some firms, off-the-shelf tools will check all the boxes. For others, custom software – built around unique workflows, data assets, and compliance needs – offers the control and precision generic platforms can’t match.

The takeaway is simple: map features to real pain points, measure the impact in hours saved and errors avoided, and choose (or build) a solution that becomes part of the way you work. 

FAQ

Can AI analyze legal documents?
Yes. Modern AI tools can ingest PDFs, emails, spreadsheets, chat logs, and scanned images; run OCR to make everything searchable; and then classify, summarize, extract entities (names, dates, clauses), flag privilege, or draft first-pass versions of briefs and contracts. Human review is still required for quality control and strategic judgment, but AI now covers much of the heavy lifting.

What is the best legal AI for contract review?
“Best” depends on your needs. If you work with high volumes of standardized agreements, look for platforms with clause extraction, playbook-based risk scoring, and side-by-side comparisons. If you need deep integrations or unique clause libraries, a tailored solution – or a custom build – may outperform any off-the-shelf product.

Can ChatGPT review a legal document?
ChatGPT can summarize, highlight issues, or suggest edits, but it lacks built-in privilege protection, audit trails, and the structured outputs (logs, redlines) most firms need. It’s best used as a drafting or brainstorming aid under strict human oversight, not as a standalone review platform.

Can AI proofread legal documents?
Yes. Many AI tools can spot typos, inconsistent definitions, cross-reference errors, and missing exhibits. Advanced platforms go further, flagging non-standard clauses or terms that deviate from your playbook. As always, final proofreading and strategic sign-off remain human responsibilities.