The Best AI Tools for Due Diligence in 2024: Streamlining Investigations
In today’s fast-moving business and legal environment, thorough due diligence is essential. Whether you are evaluating a merger or acquisition, vetting a business partner, reviewing investment opportunities, or meeting regulatory obligations, the volume of information can be difficult to manage.
That is where AI is changing the process. AI-powered tools can review large datasets, identify patterns, flag potential risks, and extract key information faster than traditional manual methods. For legal teams, analysts, and compliance professionals, the result is a more efficient and more consistent due diligence workflow.
This guide covers some of the best AI tools for due diligence and how to choose the right one for your needs.
Why AI Is Changing Due Diligence
Traditional due diligence is often manual, time-consuming, and vulnerable to human error. Lawyers, financial professionals, and compliance teams may spend hours reviewing documents, searching databases, and cross-checking facts. That slows down deals and increases the risk of missing critical issues.
AI helps automate many of those tasks. Machine learning and natural language processing can review legal text, detect anomalies, organize documents, and surface information that might otherwise be overlooked. That means faster document review, stronger risk assessment, and more time for higher-value analysis.
For businesses, AI can support quicker decisions, lower operational risk, and better deal execution. For legal teams, it can reduce repetitive work and improve coverage across large document sets.
Best AI Tools for Due Diligence
The right tool depends on your workflow, budget, and the type of due diligence you need to perform. Below are several leading options that are commonly used across legal and compliance-focused work.
1. Kira Systems (now part of Litera)
What it does: Kira is a contract analysis platform that uses AI to extract, analyze, and organize key data from legal documents. It is especially useful for identifying clauses, terms, and provisions in contracts, leases, and other complex legal texts. Its machine learning models can be trained to recognize provisions relevant to due diligence, such as change of control clauses, indemnification obligations, and force majeure language.
Why it is useful: In M&A due diligence, reviewing thousands of contracts can become a major bottleneck. Kira helps speed up the process by automatically identifying and categorizing relevant contractual data. That gives legal teams a faster way to assess exposure, spot risks, and confirm compliance with deal terms. It is also useful after a transaction when teams need to centralize contract information for integration work.
Best fit: M&A due diligence, contract review, compliance checks, and portfolio analysis of agreements.
Pros: Highly accurate, extensive clause library, customizable, strong for large-scale contract review, integrates well with legal tech workflows.
Cons: Can be expensive, may require training to use effectively, and is focused more on document review than broader investigation.
2. Luminance
What it does: Luminance is an AI-powered legal document review platform that can analyze large volumes of legal text. It is designed to understand legal language, identify clauses and anomalies, and compare documents against patterns or precedent to flag potential concerns.
Why it is useful: For due diligence, Luminance supports fast and detailed document review. It can highlight unusual terms, detect deviations from standard language, and summarize critical points, reducing the time needed for manual review. Its pattern recognition can also help uncover issues that may not be obvious at first glance.
Best fit: Transactional due diligence, large document repositories, contract risk review, and compliance checks.
Pros: Strong legal-text analysis, fast review, intuitive interface, handles multiple document types, good for identifying risk.
Cons: Primarily focused on document review, pricing may be challenging for smaller firms, and it may require substantial input data for best results.
3. Everlaw
What it does: Everlaw is an e-discovery platform with AI-powered features for document review and analysis. Its capabilities include near-duplicate detection, clustering, predictive coding, and search tools that help teams organize and review large datasets.
Why it is useful: In due diligence matters involving large amounts of electronic data, Everlaw can reduce the number of documents that need manual review. Predictive coding learns from reviewer decisions and helps identify similar documents, which can improve consistency and speed. Its collaboration tools also make it useful for team-based reviews.
Best fit: Large-scale electronic document review, overlapping litigation and due diligence work, internal records review, and pattern identification across large datasets.
Pros: Strong for large data volumes, effective for document reduction and categorization, good collaboration features, user-friendly.
Cons: Built primarily for e-discovery, so it may need customization for clause extraction or other due diligence-specific workflows, and it can feel complex to new users.
4. Casetext with CoCounsel
What it does: Casetext, through CoCounsel, offers an AI legal assistant that can draft documents, summarize case law, and perform legal research. In due diligence, it can help gather background information on regulatory issues, relevant case law, and legal questions tied to a transaction or target company.
Why it is useful: Due diligence often includes a research-heavy component. CoCounsel can speed up that work by summarizing laws, regulations, and decisions that may affect a deal. It can also help draft initial due diligence questions or research memos, which is useful when evaluating a company operating in a regulated industry.
Best fit: Legal research, regulatory compliance, risk assessment, and drafting due diligence questionnaires.
Pros: Strong for research and summarization, helpful for first drafts, accessible for smaller firms and individual practitioners.
Cons: Less focused on direct contract review than specialized tools, more research-oriented than clause-extraction tools, and may not offer the same depth for granular document analysis.
5. AuditBoard
What it does: AuditBoard is a cloud-based platform for audit, risk, and compliance management. Although it is best known for internal audit and SOX workflows, it can support due diligence by helping teams evaluate internal controls, risk posture, and compliance processes.
Why it is useful: Buyers and investors often want to understand a target company’s operational and compliance health. AuditBoard can help centralize audit evidence, identify control gaps, and assess whether internal risk management practices are effective. That makes it especially helpful for financial and operational due diligence.
Best fit: Internal controls review, financial reporting integrity, operational due diligence, and compliance assessment.
Pros: Broad GRC capabilities, strong risk visualization, good collaboration features, integrates with other systems.
Cons: Not a primary document review platform, AI features are tailored to audit and risk workflows, and it may require configuration to fit a specific due diligence process.
6. Exafluence
What it does: Exafluence provides AI-powered data extraction and analysis solutions that can help structure information from unstructured sources such as financial reports, contracts, and customer records. It also offers identity verification and background check capabilities.
Why it is useful: Due diligence often involves pulling together information from many formats and sources. Exafluence can help automate that process by extracting and organizing key data points. Its identity verification and background check features are also valuable in early-stage diligence and onboarding workflows.
Best fit: Data extraction from financial and operational documents, identity verification, background checks, and data enrichment.
Pros: Strong data extraction capabilities, scalable for large data volumes, customizable, useful for identity-related checks.
Cons: May be more service-based than self-serve software, pricing can vary by project, and it is less focused on legal clause analysis than dedicated legal AI tools.
How to Choose the Right AI Tool for Due Diligence
Choosing the best AI tool depends on the type of diligence you perform and the information you need to review.
Scope of work: If your process is contract-heavy, tools like Kira and Luminance are strong choices. If research and regulatory analysis matter more, Casetext with CoCounsel may be a better fit. For operational and compliance review, AuditBoard is more relevant.
Data volume and complexity: For large document sets, platforms such as Everlaw and Luminance can help reduce review time. If your work involves extracting structured data from mixed formats, Exafluence may be more appropriate.
Budget and resources: AI tools vary widely in price. Some are subscription-based, while others involve project pricing or enterprise contracts. Make sure the tool fits both your budget and your internal capacity to implement it.
Integration needs: Check whether the platform works with your existing legal or business systems. Integration can make a major difference in workflow efficiency.
Specific AI capabilities: Focus on the features that solve your main problem, whether that is natural language processing, predictive coding, anomaly detection, or clause extraction.
Ease of use and training: Some platforms are easier to deploy than others. Consider how much training your team will need and what support the vendor provides.
Pricing and Value Considerations
AI due diligence tools can range from relatively affordable subscriptions to expensive enterprise platforms, depending on the vendor, features, and scale of use. The key is to evaluate value, not just price.
These tools can provide value by:
- Reducing time spent on manual review
- Lowering external legal and internal labor costs
- Improving consistency and accuracy
- Surfacing patterns and risks that may be missed in manual review
When comparing pricing, look at:
- Subscription models: Monthly or annual plans based on users, volume, or features
- Project-based pricing: Common for custom extraction, training, or managed services
- Hidden costs: Setup, training, support, and storage fees
- Scalability: Whether the pricing structure can grow with your needs
Frequently Asked Questions About AI Tools for Due Diligence
Can AI completely replace human reviewers in due diligence?
No. AI is best used to augment human review, not replace it. It is effective at repetitive tasks and pattern recognition, but human judgment is still needed for interpretation and final decisions.
How accurate are AI tools for due diligence?
Accuracy depends on the tool, the training data, and the specific task. Leading platforms can be highly effective for clause identification and document review, but human oversight is still important.
What types of data can AI tools analyze for due diligence?
AI tools can analyze contracts, financial statements, emails, internal documents, legal filings, public records, and more. The exact range depends on the platform.
Is it difficult to implement AI due diligence tools?
It depends on the platform. Some tools are designed for straightforward setup, while others may require more technical configuration or customization. Many providers offer onboarding and training.
How do I protect sensitive data when using AI tools?
Choose vendors with strong security controls, including encryption, access management, and compliance with relevant privacy requirements. Review data handling policies carefully before implementation.
Are AI tools cost-effective for small firms or businesses?
They can be. Some tools are designed for smaller teams, while enterprise products may be expensive. The best approach is to compare the time saved and risk reduced against the total cost of ownership.
Conclusion
AI is reshaping due diligence by making document review, research, and risk assessment faster and more efficient. Tools like Kira and Luminance can accelerate contract analysis, Everlaw can help manage large document sets, Casetext with CoCounsel can support legal research, and AuditBoard can improve operational and compliance review.
The best ai tools for due diligence are the ones that fit your workflow, data types, and budget. Used well, they can help legal and business teams work faster, reduce risk, and make better decisions. AI should not replace human judgment, but it can make the due diligence process more focused, efficient, and scalable.