Knowledge work automation

7 Best AI Contract Review Tools: Buyer’s Guide [2024]

7 Best AI Contract Review Tools: Buyer’s Guide [2024]

17 min read

Nov 19, 2024

Casimir Rajnerowicz

Casimir Rajnerowicz

Product Content Writer

Imagine this: A major law firm spends six grueling months attempting to develop an in-house IDP system for reviewing and analyzing legal contracts. The goal? To automate the extraction of key clauses, compare contract terms against previous agreements, and ensure compliance with local regulations.

But despite their best efforts, their internal team encounters significant roadblocks. Then—like a plot twist in a legal drama—they learn about a new AI platform for document processing and request a demo. The solutions engineer they're introduced to builds a functional prototype in just three hours.

What a time to be alive, right?

The firm's legal team is astounded by the speed and accuracy of the AI. They're now eager to implement it immediately, planning to expand its use to contract risk assessment and automated document comparison across various legal workflows. Best of all, they can now manage and scale these processes on their own.

Does the scenario, or at least the beginning of it, sound familiar?

If you're trying to implement AI contract review in your firm's processes, you're in the right place.

In this article, we'll explore:

  • What is automated contract review, and what's all the fuss about?

  • How does it work, and what technologies are used behind the scenes?

  • What are the best AI contract analysis solutions available today?

If you are impatient to find out what is the best AI contract review software, check the comparison table right below:

A table comparing features and pricing models of various legal AI tools like V7 Go, Hebbia, Kira, goHeather, Juro, LEGARTIS, and Legly, including details about their functionalities such as contract review workflows, semantic search, and clause extraction.

For a more detailed overview of the platforms, and for more information on contract analysis with AI, keep reading the guide.

Introduction to automated contract review with AI

According to a 2023 Thomson Reuters survey, 31% of legal departments are already using AI for contract analysis and review, with another 24% planning to implement it within the next 12 months. A recent report by OneAdvanced, confirms about 70% of law firms are either using or researching the use of AI in their daily operations.

As Richard Tromans, founder of Artificial Lawyer, notes: "We're seeing a significant uptick in the use of AI for contract review. What was once viewed as experimental technology is now becoming an essential tool for many legal teams." And there are many success stories of early bird companies that started to drive value from legal AI fast.

An infographic listing various legal AI use cases, including contract search and extraction, legal claims classification, compliance checks, document summarization, and insurance policy review.

If you want to take a closer look at how these problems are solved with AI, visit:

What are the key benefits of using AI for contract analysis?

While there are several advantages, the main benefit boils down to one crucial point: efficiency. AI saves your firm a lot of time, and by extension, money. Studies show that 68% of contract professionals search for completed contracts at least once a week, often spending over two hours per contract just to locate specific clauses. AI-powered platforms can drastically reduce this time by enabling instant retrieval of key information.

As the legal industry recognizes the benefits of AI, the market for contract review solutions is poised for significant growth. According to Grand View Research, the global legal AI market is projected to grow significantly, with estimates indicating that it could reach $3.89 billion by 2030, driven by increased demand for automation in legal applications, including contract review.

The spike in both adoption rates and market value for AI tools for lawyers is quite sudden. While solutions such as AI-based OCR software and IDP tools have been around for quite some time, the last three years have seen more progress in document processing than in the previous decade.

So, what has changed?

This:

A custom-built workflow automation process for legal contracts, showing conditional logic paths for sections like compensation, benefits, and confidentiality, with flagged clauses routed to human review.

The picture above shows a WYSIWYG AI workflow designer in V7 Go. Anyone can use it for building multi-step contract reviews and advanced automations powered by AI models. What once required teams of engineers can now be set up by an intern.

Let’s take a closer look at technologies used in legal AI tools.

How does AI-based automated contract review work?

There are many things that AI is good at and quite a bit that it still struggles with. If there is one thing that it has proven to be surprisingly good at is extracting relevant information from massive volumes of text and do basic reasoning based on the insights—which is just a perfect thing if you happen to run a law firm.

Modern AI contract review solutions leverage large language models (LLMs), retrieval augmented generation (RAG), and machine learning to automate traditionally manual review processes.

A flowchart illustrating an AI-powered process for document analysis, starting from document upload and OCR scanning, proceeding through LLM analysis and RAG (retrieval-augmented generation), and ending with a user-requested output.

In case you need a quick refresher on core technologies employed:

Step 1: OCR (Optical Character Recognition)

When dealing with scanned legal documents, such as contracts, OCR is used to convert images or PDFs into machine-readable text. This is essential because legal firms often work with physical documents or scanned copies, and digitizing these is the first step toward making them searchable.

Step 2: LLMs (Large Language Models)

Once the documents have been converted into text using OCR, an LLM steps in. LLMs are capable of understanding the content and legal language. A user can ask the AI questions such as, "Find clauses related to termination in these contracts," and the LLM can comprehend this query in natural language.

Step 3: Vector Databases

As LLMs may struggle with handling massive legal documents or maintaining context across long passages, vector databases store the content of these documents as mathematical vectors. This allows the system to perform similarity searches based on the semantic meaning of the query, rather than just keyword matching. Vector databases provide highly relevant passages from the contract database to the LLM.

Step 4: RAG (Retrieval Augmented Generation)

RAG ties everything together. It takes the user’s natural language query and breaks the process into two parts: retrieval and generation. First, the RAG system uses the vector database to retrieve the most relevant sections from thousands of legal documents. Then, using an LLM, it generates a response or summary based on the retrieved information, ensuring it answers the query in a coherent and contextually appropriate manner.

A Generative AI tool that automates knowledge work like reading financial reports that are pages long

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A Generative AI tool that automates knowledge work like reading financial reports that are pages long

Knowledge work automation

AI for knowledge work

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Now, the big question is—

Let’s take a few steps back.

A few years ago, AI could classify documents or route them to different legal teams. It could search for specific keywords and perform basic NLP analysis, like analyzing the frequency of certain words or phrases to glean insights from documents. These solutions were rule-based, using conditional logic, and not good for working with nuanced or unstructured data.

Fast forward to 2024, and we have:

  • AI that can pass the most difficult legal exams (in fact, a GPT model passed the Uniform Bar Exam in 2022, although there are some controversies around the methodology)

  • AI systems can detect complex patterns and cross-reference thousands of documents with deep understanding of unstructured data.

  • LLM orchestration tools and AI workflow designers that allow you to connect multiple models to perform complex reasoning.


An example of employee contract review workflow in V7 Go

AI’s performance benchmarks rise year after year, or rather month by month. While typically, domain-specific knowledge and solving complex tasks, wasn’t the forte of many models, this is changing very quickly. For instance, OpenAI's o1 model, currently in preview, can provide complex, step-by-step reasoning designed for solving domain-specific problems, including legal reviews.

A bar chart displaying MMLU performance scores across categories like Global Facts, College Chemistry, Professional Law, and Formal Logic, comparing baseline and AI-enhanced results.

Does all this mean that AI will replace lawyers?

By no means. On the other hand, as Erik Brynjolfsson of the Stanford Digital Economy Lab observes: lawyers using AI will definitely replace lawyers who don't use AI.

Now—

Does using tools like ChatGPT for summarizing a contract count? Are there tools like ChatGPT but designed specifically for lawyers and much more accurate? As a matter of fact, you may ask yourself: why can't I use ChatGPT for free to process legal documents?

If something is free, it often means you are the product. OpenAI uses your conversations to fine-tune and improve its model's performance. Technically, this means that pairs of user prompts and AI-generated responses are collected and fed back into the model during training. By using these pairs, the model adjusts its internal weights—the parameters that influence how it generates text—to better respond to similar inputs in the future. This process enhances the model's capabilities but doesn't imply that it memorizes every piece of data it receives. Ideally, the model generalizes from the data rather than storing specific instances.

However, there are cases where the model may inadvertently produce responses that reveal sensitive information or indicate that the training data was exceptionally specific. The legal considerations surrounding this issue are still not fully explored or clearly understood by policymakers. Therefore, it's wise to think twice before sharing confidential or sensitive information on a free plan.

Can ChatGPT redline a contract? ChatGPT cannot directly redline or visually highlight parts of a contract. For more advanced contract analysis, consider specialized tools like V7 Go. When using GPT models within V7 Go, you can visually highlight and flag specific sections of documents, explain the AI's reasoning, and create searchable references for quick inspection.

That's why you should consider professional solutions that meet regulatory requirements, keep your data private, and handle matters like non-disclosure agreements (NDAs) with extreme caution.

So—

If ChatGPT is not the answer, what is the best AI for contract review?

Best AI contract review software

Choosing the right AI contract review tool can be daunting with so many options available. How do you know which one is right for your specific needs? Let's explore some of the top contenders in the market:

V7 Go

A detailed interface for reviewing confidentiality and non-compete clauses in contracts, highlighting both existing clauses and potentially missed clauses like non-competition and intellectual property rights.

V7 Go is an all-rounder AI document processing platform used in critical fields like legal and finance. It offers impressive features such as AI citations for easy verification of information (something ChatGPT can't do.) V7 Go can redline your documents and mark critical insights, although the actual highlights happen to be purple.

V7 was showcased as one of Google's top 100 GenAI startups at Google Next 2024. It was also picked as the top GenAI SaaS company in the 2024 Sifted’s annual ranking of the most promising B2B companies.

Pros:

  • Custom document processing and contract review workflows

  • Intuitive interface and top LLM models available out of the box

  • Easy integration with other tools and frameworks

  • Supports multimodal data (text, PDF, images)

Con:

  • As an end-to-end document processing platform, it may have a slightly steeper learning curve. However, you can also start by exploring templates before trying to create your own project from scratch.

Key differentiators:

  • AI citations and information highlights for easy verification of AI-generated responses

  • Advanced reasoning capabilities and LLM orchestration tools for multi-step workflows

  • Long document support and powerful document comparison features

How to try it out:

V7 Go offers a free plan to get started. You can create a free account and try an example legal document workflow. The platform also offers a Pro plan at $249/month and custom Enterprise pricing for larger organizations.

Hebbia AI

A screenshot of Hebbia's document analysis tool, showing a project focused on an American Airlines meeting

Hebbia AI is a powerful document search tool designed for enterprises, particularly those dealing with large datasets and complex workflows. By leveraging advanced AI capabilities such as large language models (LLMs) and machine learning, Hebbia enables firms to perform semantic searches, extract metadata, and synthesize insights from a wide range of document types, including PDFs, spreadsheets, and legal contracts.

Key features of Hebbia include real-time indexing, cross-document semantic search, and the ability to handle multi-step workflows. Its strength lies in transforming vast volumes of information into actionable insights, making it a popular choice for legal due diligence, financial deal analysis, and regulatory reviews. Moreover, Hebbia is tailored for enterprise-level security, ensuring data privacy and compliance with legal frameworks.

Hebbia's pricing is customized based on the scale of use and specific business needs, with no public fixed pricing available.

Litera AI (Kira)

A webpage for Litera, highlighting Kira’s AI-driven contract review features

Kira, now part of Litera, is an AI-powered contract review software that has become a staple for legal professionals focused on due diligence and compliance. Known for its robust machine learning capabilities, Kira automates the identification and extraction of over 1,400 different clauses and key data points from contracts and legal documents, allowing teams to review contracts efficiently while maintaining accuracy. It also groups related documents like contracts and amendments for a streamlined review process.

One of Kira’s standout features is Smart Summaries, a generative AI integration designed to summarize contract terms and clauses quickly, making contract review even faster and more precise. This feature enables lawyers to generate concise summaries at the click of a button without sacrificing reliability or detail. Kira also supports collaborative workflows, allowing multiple team members to tag, track, and visualize contract data, making it an ideal tool for large-scale M&A transactions and compliance checks.

Kira’s pricing is not publicly listed and is available upon request, typically customized for law firms and large organizations based on their needs​

goHeather AI

A landing page for goHeather, showcasing its AI-driven contract review features, including lawyer-trained analysis and risk level assessments

goHeather AI is a cutting-edge contract analysis tool designed specifically for legal professionals. It offers real-time contract analysis powered by AI that has been trained by experienced lawyers, ensuring a high level of accuracy and relevance in the legal context.

One of goHeather's standout features is its user-friendly drag-and-drop interface, making it accessible even to those who aren't tech-savvy. The platform excels in risk assessment and issue spotting, providing lawyers with valuable insights that can save time and reduce potential oversights.

Juro AI

Juro AI, showcasing its AI assistant for faster contract drafting, summarizing, reviewing, and data extraction

Juro AI has positioned itself as a leading player in contract lifecycle management (CLM), aiming to simplify the entire contract process from creation to execution. Recognized as a standout in the legal tech space, Juro’s intuitive AI Assistant automates tasks such as drafting, summarizing, and redlining contracts, making it easier for businesses to reduce manual labor and focus on high-value work.

Juro’s AI-powered repository provides advanced post-signature insights, transforming contracts into valuable data assets. This enables teams to instantly access and act on key contractual details, offering a significant advantage for tasks like compliance monitoring and due diligence, all while ensuring data privacy through SOC2-compliant security​.

Legartis AI

A webpage for LEGARTIS

Legartis AI is another notable player in the AI contract review landscape, particularly designed for contract data extraction and compliance. With a focus on accessibility for non-lawyers, its interface simplifies contract management, making it easier for a broader range of business professionals to use. The platform’s AI engine extracts key clauses and legal terms from contracts automatically, ensuring users can quickly identify risks, obligations, and critical deadlines.

Legartis is also known for its user-friendly design, making it accessible for teams without a strong technical or legal background. This ensures quick onboarding and usage across multiple departments, not just legal teams, which can help companies avoid bottlenecks in their contract management processes.

Legly AI

A landing page for Legly featuring its AI contract review solution, emphasizing saving time on contract reading to focus on customer engagement, with an interface showing contract analysis.

Legly AI is geared toward legal compliance checks and contract clause recommendations, offering legal professionals and organizations a quick way to ensure contracts meet industry standards. The tool is designed for speed and simplicity, allowing users to upload contracts in various formats and receive automatic insights on potential legal risks or missing clauses.

One of Legly’s core strengths is its ease of use, designed for teams that need quick onboarding and minimal setup. Its AI-driven recommendations allow users to ensure that contracts meet their organization’s internal standards, with a focus on compliance and risk management. Whether dealing with NDAs, employment contracts, or vendor agreements, Legly’s automated checks help to flag issues that could be overlooked in manual reviews.

Key considerations for choosing the right AI contract review tool

When selecting an AI contract review tool, it is essential to consider several key factors that can significantly impact the effectiveness and reliability of the solution. Below are critical considerations that should guide your decision-making process.

Transparency

Transparency is vital in ensuring that users can trust the AI tool's outputs and processes.

  • Verifiable results. The tool should provide clear, verifiable results that allow users to validate the AI's findings. This includes easy navigation features to see highlights, identify potential problems, and understand how conclusions were reached.

  • Traceable processes. Users should have access to a detailed view of the AI’s reasoning process, including the actual prompts, inputs, and outputs. This prevents the "black box" effect often associated with AI systems, where users cannot see how decisions are made.

  • User control. A transparent tool empowers users to adjust parameters and refine queries, leading to more accurate results tailored to specific needs.

Compliance

Compliance with data protection regulations is non-negotiable when choosing a contract review tool.

  • Data protection standards. Ensure that the tool adheres to relevant data protection regulations such as GDPR in Europe or CCPA in California. This includes understanding how data is collected, stored, and processed.

  • Audit trails. The tool should maintain comprehensive audit trails that document all interactions with sensitive data, allowing organizations to demonstrate compliance during audits.

  • Third-party certifications. Look for tools that have undergone third-party audits or certifications related to security and compliance, as this adds an extra layer of assurance.

Accuracy

The accuracy of an AI contract review tool is paramount for effective legal analysis.

  • Performance evaluation. The tool should offer features that allow users to evaluate its performance easily. This could include metrics on accuracy rates, error frequencies, and user feedback mechanisms.

  • Incremental improvement. Choose a solution that enables continuous learning and improvement. Features such as user feedback loops or retraining options can help enhance the quality of outputs over time.

  • Benchmarking. Some tools may provide benchmarking against industry standards or past performance metrics, helping users gauge their current accuracy levels.

A screenshot showing AI accuracy improvements for tasks using reinforcement learning, progressing from 71% to 95% with increased training samples.

Security

Security is a critical consideration due to the sensitive nature of legal documents.

  • User roles and permissions. The tool should allow for customizable user roles and permissions to ensure that only authorized personnel can access sensitive information. This helps mitigate risks associated with internal data breaches.

  • Data encryption. Ensure that the platform uses robust encryption methods for both data at rest and in transit. This protects sensitive information from unauthorized access during storage and transmission.

By carefully evaluating these key considerations—transparency, compliance, accuracy, and security—organizations can select the most suitable AI contract review tool that meets their specific needs while safeguarding their sensitive data and ensuring regulatory compliance.

The future of AI contract analysis

Legal contracts form the backbone of countless transactions, partnerships, and agreements. They delineate responsibilities, protect interests, and establish the rules of engagement between parties. However, as businesses scale and the volume of contracts increases, managing them efficiently becomes a herculean task.

The integration of AI in contract analysis is not merely about replacing human effort; it’s about augmenting it. Legal professionals who embrace these tools can focus on high-value tasks such as strategic decision-making and client interactions, while routine reviews are handled efficiently by AI.

"When measuring the return on investment of a work AI platform, it’s important to measure productivity gains more carefully than cost reductions. AI products are notorious for helping reduce cost, then inadvertently leading to a decreased quality of service. Knowledge work AI mitigates this by putting employees in control of the AI workflows which act as their copilot." - Alberto Rizzoli

While not replacing experienced lawyers, AI tools offer game-changing advantages in contract review. By breaking down complex legal processes into manageable tasks, current AI can analyze documents with remarkable accuracy. The challenge for law firms now is how to effectively orchestrate these AI capabilities within their workflows.

This technology is gaining traction among law firms, with reports indicating that nearly 90% of in-house legal teams have adopted some form of AI tools for tasks like contract analysis and document review. If you want to try one of the best legal AI solutions, with ready-to-use workflow templates for contract reviews, you can sign up for a free V7 Go account now or book a demo.

References

American Bar Association - Quotable Quotes on the Impact of AI on the Legal Profession

OneAdvanced - The Faster Law Firm: Why Firms Are Quick to Try Generative AI

Thomson Reuters Legal Insights Europe - Buyer’s Guide: Artificial Intelligence in Contract Analysis Software

NYSBA - Why ChatGPT-4’s Score on the Bar Exam May Not Be So Impressive

CLOC - 4 Statistics That Will Change Your Mind About Contract Analytics and AI

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Casimir Rajnerowicz

Casimir Rajnerowicz

Product Content Writer at V7

Casimir Rajnerowicz

Casimir Rajnerowicz

Product Content Writer at V7

Casimir is a tech journalist and content writer with a keen interest in all things AI. His main areas of focus are computer vision, AI-generated art, and deep learning. He's also a fan of contemporary digital art and photography.

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