Quick Summary
- AI adoption in legal is accelerating, with tools now handling work that was once entirely manual
- Platforms vary widely from contract drafting add-ins to full enterprise litigation suites
- Contract-focused tools like Spellbook, Ironclad, Kira, and Luminance serve different firm sizes and deal types
- Research platforms like Westlaw and CoCounsel combine verified legal databases with conversational AI
- Harvey and Everlaw are pushing toward agentic and analytics-driven workflows for complex matters
- Lex Machina gives litigation teams data on judges, outcomes, and opposing counsel before they file
- DoNotPay shows how legal AI can extend beyond firms to serve everyday consumer legal needs
AI tools for legal teams have moved well beyond early experiments; handling work that once required hours of manual effort, including contract review, legal research, due diligence, and document drafting. Law firms and in-house legal departments are turning to these platforms to cut review time, lower outside counsel costs, and bring more consistency to high-volume work.
The technology varies quite a bit from one platform to the next. Some tools use supervised machine learning trained on legal datasets. Others rely on large language models to generate and analyze text. Most enterprise-grade platforms now bundle document review, natural language search, and workflow automation into a single interface. Still, adoption is uneven across the profession, and choosing the right AI tools for legal teams depends heavily on practice area, firm size, and workflow.
This article breaks down ten of the most widely used AI platforms in the legal space today, what they do well, and who they are best suited for.
1. Spellbook
Founded: 2020 | Headquarters: Toronto, Canada
Spellbook is a contract drafting and review tool that lives inside Microsoft Word as an add-in. It uses large language models, including GPT-4, to suggest contract language, flag missing clauses, and accelerate first-draft generation without asking lawyers to leave the environment where they already work.
The platform is aimed primarily at small and mid-sized law firms working with standard commercial contracts such as NDAs, service agreements, and employment contracts. Its focus is deliberately narrow. Rather than trying to manage an entire legal operation, Spellbook zeroes in on one workflow: getting a solid contract draft done faster. For firms that need deeper automation across the full contract lifecycle, a more comprehensive enterprise platform may be a better fit.
2. Everlaw
Founded: 2010 | Headquarters: Oakland, California
Everlaw is a cloud-based eDiscovery platform used by law firms, corporations, and government agencies. It is built for the data-intensive work of litigation, where legal teams may need to review tens or hundreds of thousands of documents in a short timeframe.
The platform uses AI-driven analytics including predictive coding, document clustering, topic detection, and batch summarization to help reviewers identify relevant evidence faster. Its AI Assistant feature supports question-and-answer interactions with large document sets, which can surface key information without requiring attorneys to read every file manually. Everlaw is consistently recognized as a leader in the eDiscovery space for its combination of analytical depth and usability.
3. Luminance
Founded: 2016 | Headquarters: Cambridge, United Kingdom
Luminance is an AI platform built for contract review and due diligence. It uses machine learning trained on legal documents to read, categorize, and surface anomalies across large volumes of contracts. Corporate lawyers frequently rely on it during mergers and acquisitions, where hundreds of agreements may need to be assessed quickly.
One often-cited example: international law firm Bird and Bird used Luminance to review nearly 200,000 employment documents, increasing review rates from 79 to 3,600 documents per hour. In 2023, the company launched Luminance Autopilot, which takes contract automation a step further by handling routine negotiation end-to-end, sending revised drafts and tracking counterparty responses in real time. The platform also supports multiple languages, which makes it useful for cross-border transactions.
4. Harvey
Founded: 2022 | Headquarters: San Francisco, California
Harvey is a legal AI platform built on large language models and used by major law firms including A&O Shearman. It supports contract analysis, due diligence, regulatory research, and document drafting across a broad range of practice areas. More than 142,000 legal professionals currently use the platform worldwide.
What distinguishes Harvey from some other tools is its move toward agentic workflows. In 2025, Harvey launched AI agents capable of handling antitrust filing analysis and loan document review with limited human intervention. The platform also includes Harvey Vault for document storage and bulk analysis, and Harvey Workflows for building repeatable, firm-specific automation. It integrates with the tools attorneys already use, allowing teams to work within familiar environments while benefiting from AI-assisted research and drafting.
5. Westlaw (Thomson Reuters)
Founded: 1975 | Headquarters: Eagan, Minnesota
Westlaw is one of the most established legal research platforms in the world. It provides access to US case law, statutes, regulations, secondary sources, and international legal content. Over the years, Thomson Reuters has layered AI capabilities into the product, including natural language search and citator tools through KeyCite.
Following Thomson Reuters’ acquisition of Casetext in 2023 for $650 million, the CoCounsel AI assistant was incorporated into the Westlaw product suite. Attorneys can now run research memos, review documents, and analyze contracts through a conversational interface built on top of Westlaw’s existing database. Thomson Reuters also offers Lex Machina, a legal analytics tool acquired in 2015 that provides data on litigation outcomes, judge tendencies, and law firm performance.
6. Casetext / CoCounsel
Founded: 2013 | Headquarters: San Francisco, California
Casetext began as a legal research platform and evolved into one of the early pioneers of AI-powered legal assistance. Its CoCounsel product, built on GPT-4, supports a wide range of practical legal tasks: research memos, document review, deposition preparation, and contract analysis, all through a conversational interface that feels more like working with a knowledgeable colleague than querying a database.
Since the Thomson Reuters acquisition, CoCounsel has been deeply integrated into Westlaw Precision and Practical Law, giving attorneys access to Deep Research capabilities alongside Microsoft 365 integration. Firms such as Polsinelli have rolled out CoCounsel firmwide to reduce research hours and improve accuracy. For legal teams already subscribed to Westlaw, adding CoCounsel has become one of the more straightforward ways to introduce AI-assisted workflows.
7. Ironclad
Founded: 2014 | Headquarters: San Francisco, California
Ironclad is a contract lifecycle management platform designed for in-house legal teams that handle high volumes of contracts across multiple business units. Rather than focusing on a single task like drafting or review, it manages the entire contract process from initial intake to signature to renewal.
A Forrester Total Economic Impact study documented 314% ROI over three years for Ironclad customers, with $1.2 million in labor cost savings and a 65% improvement in end-to-end contract efficiency. The platform includes workflow automation, a digital repository for executed agreements, and an AI Research Agent that can answer questions about contracts stored in the system. It is best suited for enterprise legal departments that need visibility and control across a large and ongoing contract portfolio.
8. Kira Systems
Founded: 2012 | Headquarters: Toronto, Canada
Kira Systems uses machine learning to identify and extract information from contracts. It recognizes more than a thousand clause types out of the box and can be trained to identify custom provisions specific to a firm’s work. Legal teams use it primarily for due diligence, contract review, and compliance checks during transactions.
The platform integrates with document management systems that many legal teams already have in place, including iManage, which reduces friction during implementation. Like Luminance, it is frequently used during M&A transactions where speed and consistency in contract review are critical. For firms working on complex transactional matters with large document sets, Kira offers a reliable and well-established option.
9. Lex Machina
Founded: 2010 | Headquarters: Menlo Park, California
Lex Machina is a legal analytics platform that gives attorneys data-driven insight into litigation. Its database contains millions of court documents, and it uses that data to surface patterns in judicial behavior, law firm performance, and case outcomes across different courts and practice areas.
Litigation teams use Lex Machina for tasks like estimating case timelines, assessing the tendencies of specific judges before a filing, and evaluating potential outside counsel based on their track record in relevant matters. In-house legal teams use it to support settlement decisions and build more informed litigation strategies. It is now part of the Thomson Reuters portfolio, which has integrated its data into the broader Westlaw ecosystem.
10. DoNotPay
Founded: 2015 | Headquarters: San Francisco, California
DoNotPay is a consumer-facing legal automation platform founded by Joshua Browder. It started as a tool for contesting parking fines and has since expanded to cover subscription cancellations, small claims filings, letter generation, and other routine legal tasks. The platform serves millions of users looking for accessible and low-cost alternatives to traditional legal assistance.
DoNotPay occupies a different space than the enterprise platforms on this list. It is not designed for law firms or in-house counsel managing complex transactions. Instead, it demonstrates what AI can do when applied to the everyday legal friction that most people encounter at some point. For legal teams thinking about client-facing automation or access to justice initiatives, DoNotPay offers a useful model for how AI can simplify routine processes at scale.
Conclusion
The AI tools for legal teams covered here reflect how varied the needs of legal professionals actually are. A litigation team preparing for discovery has different requirements than a transactional lawyer drafting NDAs or a consumer navigating a dispute on their own. The platforms on this list each solve a specific part of that spectrum, and the right choice depends on the size of your team, your practice area, and the workflows you want to improve.
What is clear across all of them is that AI in legal work is no longer experimental. These tools are in active use at major law firms, in-house departments, and government agencies worldwide. For legal professionals still evaluating where to start, the most practical approach is to identify your highest-volume, most time-intensive task and look for a tool built specifically to address it.
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