Best AI Tools for Due Diligence: A Practical Guide for Legal and Transaction Teams
Due diligence is one of the most important parts of any transaction, but it is also one of the most time-consuming. Whether you are working on an M&A deal, an investment round, a financing transaction, or a commercial partnership, you need to review large volumes of documents and identify risks quickly and accurately.
That is where AI tools can help. The best AI tools for due diligence can speed up document review, extract key terms, surface red flags, and support more consistent analysis across legal, financial, and operational materials. For lawyers, investors, and in-house teams, these tools are becoming an essential part of the workflow.
Why AI Matters in Due Diligence
Due diligence often involves reviewing contracts, financial statements, regulatory filings, emails, reports, and other unstructured documents. Manual review is slow, expensive, and vulnerable to human error, especially when deadlines are tight.
AI can improve the process in several ways:
- Accelerating document review: AI can process large document sets much faster than manual teams.
- Improving consistency: It can identify key clauses, terms, and issues in a repeatable way.
- Reducing missed risks: AI may surface anomalies, compliance issues, or unusual provisions that could otherwise be overlooked.
- Saving time and resources: Automation reduces repetitive work and lets professionals focus on judgment-heavy tasks.
- Supporting deeper analysis: Some tools can help with summarization, risk identification, and data extraction across large and complex datasets.
The right platform depends on the type of diligence you are doing, the document volume involved, and how much legal versus financial analysis you need.
Best AI Tools for Due Diligence
Here are some of the leading AI-powered tools used for due diligence work.
1. Casetext and CoCounsel
Casetext, through its AI legal assistant CoCounsel, is designed to support legal research and document analysis. It can review and summarize documents, extract key information, identify potential issues, and help draft initial reports.
Why it is useful:
Casetext is particularly helpful for legal due diligence, where teams need to review contracts, assess risk, and identify relevant legal issues quickly. It can reduce the time spent on first-pass review and help lawyers focus on higher-value analysis.
Best fit:
- M&A legal due diligence
- Contract review
- Litigation risk assessment
Pros:
- Strong legal research capabilities
- Useful for document review and summarization
- Intuitive interface
Cons:
- More focused on legal work than broader financial or operational diligence
- May need to be paired with other tools for full transaction support
2. LexisNexis AI Solutions
LexisNexis offers AI-powered tools such as Lexis+ AI and diligence-focused solutions that support legal research, summarization, drafting, and risk analysis. These tools draw on LexisNexis’s large legal content base.
Why it is useful:
LexisNexis tools are valuable when diligence requires strong legal and regulatory context. They can help teams assess issues more efficiently while leveraging trusted legal resources.
Best fit:
- Law firms
- Corporate legal departments
- Legal and regulatory due diligence
Pros:
- Deep legal content library
- Strong summarization and analysis features
- Established platform with robust security and compliance features
Cons:
- Premium pricing
- Broad feature set may require training
3. Kira Systems
Kira Systems, now part of Diligent, is known for contract analysis. It uses machine learning to identify and extract provisions from legal documents, making it useful for large-scale contract review.
Why it is useful:
Kira is a strong choice when a deal involves many contracts and you need to understand obligations, exceptions, and deviations from standard language. It is especially helpful for contract abstraction and clause review.
Best fit:
- M&A transactions
- Real estate diligence
- High-volume contract review
Pros:
- Specialized in contract analysis
- Accurate extraction of key clauses and data points
- Familiar to legal teams
Cons:
- Primarily contract-focused
- Broader diligence usually requires additional tools
4. Eigen Technologies
Eigen Technologies is built to extract and analyze data from complex unstructured documents, including financial statements, legal agreements, and operational reports.
Why it is useful:
Eigen is well suited to diligence workflows that involve mixed document types and the need to turn unstructured information into structured data. That can support faster analysis, reporting, and model building.
Best fit:
- Financial institutions
- Private equity firms
- Complex legal and financial diligence
Pros:
- Handles complex document sets well
- Strong data extraction capabilities
- Can fit into existing workflows
Cons:
- May require upfront configuration
- Can have a steeper learning curve
5. Onit
Onit offers legal operations and contract management solutions, including AI-powered contract analysis. Its tools can review contracts, extract key data, flag risks, and help monitor compliance.
Why it is useful:
Onit is useful for organizations that want AI support within a broader legal operations workflow. It can help standardize contract review and identify deviations more efficiently.
Best fit:
- Corporate legal departments
- Contract managers
- Compliance teams
Pros:
- Combines contract management with AI analysis
- Scales well for enterprise use
- User-friendly for legal operations teams
Cons:
- Strong for contract review, but less specialized for broad transaction diligence
- May not cover all diligence needs on its own
6. Verity by EA
Verity is an AI-powered platform for reviewing contracts and legal documents. It uses natural language processing and machine learning to extract clauses, identify risks, and check consistency across large document sets.
Why it is useful:
Verity is helpful when you need to spot non-standard terms, flag compliance issues, and review a high volume of agreements efficiently. That makes it useful in M&A, financing, and compliance projects.
Best fit:
- M&A
- Commercial lending
- Contract-heavy legal reviews
Pros:
- Good clause identification and extraction
- Helps flag contractual anomalies
- Practical interface for review teams
Cons:
- Mainly focused on contracts
- Broader diligence may require other tools
How to Choose the Right AI Tool for Due Diligence
The best AI tool for due diligence depends on your workflow, the type of transaction, and the documents you need to review. A few practical factors matter most:
- Define your scope: Are you focused on legal, financial, operational, or mixed diligence?
- Match the document type: Large contract sets call for contract-focused tools, while more varied document collections may require broader extraction capabilities.
- Check integration: Make sure the tool fits with your existing systems and review process.
- Test the AI quality: Look at how well the platform understands context, identifies issues, and extracts relevant data.
- Consider usability: A tool is only valuable if your team can use it efficiently.
- Review security features: Due diligence often involves highly sensitive information, so security and confidentiality should be a priority.
Pricing and Value
AI due diligence tools can be a meaningful investment, but they may save time and reduce costly review errors.
Common pricing models include:
- Subscription pricing: Often based on users, volume, or feature access
- Per-project pricing: Useful for specific transactions or high-volume matters
- Enterprise agreements: Better for larger teams with ongoing diligence needs
When evaluating price, focus on practical return on investment. Consider time saved, reduced manual effort, better consistency, and the potential to catch risks earlier. In many cases, a pilot project is the best way to test value before rolling out a tool more broadly.
Frequently Asked Questions
Can AI replace human due diligence professionals?
No. AI is best used to support and speed up the process, not replace human judgment. Lawyers and other professionals are still needed to interpret findings, assess risk, and make final decisions.
How accurate are AI due diligence tools?
Accuracy depends on the platform and task. Many tools perform well on document summarization and data extraction, but important findings should still be reviewed by a human.
What kinds of documents can these tools review?
Most can handle a mix of structured and unstructured data, including contracts, financial statements, reports, regulatory filings, emails, and news sources.
Is sensitive data secure on AI platforms?
Reputable vendors generally offer encryption, access controls, and compliance features. Security should always be reviewed before adoption.
Do these tools require technical expertise?
Usually not. Most modern platforms are built for legal and business users, though setup and integration may involve IT support.
Conclusion
AI is changing how due diligence is done. Instead of relying only on manual review, legal and transaction teams can use AI tools to process more documents, identify risks faster, and work more efficiently.
The best AI tools for due diligence are not one-size-fits-all. Casetext and LexisNexis are strong options for legal research and review. Kira, Verity, and Onit are useful for contract-heavy workflows. Eigen is better suited to more complex document extraction needs.
If you are evaluating AI for due diligence, start by defining your use case, testing the tool on real documents, and confirming that it fits your workflow and security requirements. The right platform can make due diligence faster, more consistent, and more actionable.