The Best AI Tools for Due Diligence: Streamlining Investigations
Due diligence is a critical step in major business transactions, including mergers and acquisitions, investment rounds, vendor selection, and compliance reviews. It requires a careful investigation of facts, risks, obligations, and potential red flags before a deal moves forward.
Traditionally, due diligence has been slow and labor-intensive. Teams often have to review large volumes of contracts, financial records, regulatory filings, internal communications, and other documents by hand. AI is changing that process by making review faster, more consistent, and easier to scale.
For lawyers, investors, business leaders, and compliance teams, the best AI tools for due diligence are becoming essential. These tools can automate repetitive work, surface issues that might otherwise be missed, and help teams focus on higher-value analysis and decision-making.
Why AI Is Changing Due Diligence
The core challenge in due diligence is information overload. A typical review may involve thousands of documents across multiple formats and data sources. Manual methods such as keyword searches, spreadsheet analysis, and line-by-line reading can take weeks or months, and they leave room for human error.
AI tools use technologies such as natural language processing, machine learning, and data analytics to process this information more efficiently. They can:
- Automate document review by categorizing and analyzing large document sets
- Identify risks by flagging clauses, anomalies, compliance gaps, and unusual patterns
- Extract data points such as names, dates, amounts, obligations, and termination terms
- Improve consistency by applying the same review logic across all documents
- Surface insights from unstructured data that would be difficult to identify manually
The result is faster review, better coverage, and more time for legal and business teams to focus on judgment and strategy.
The Best AI Tools for Due Diligence
The market includes tools built for contract analysis, document review, financial analysis, and risk screening. The right choice depends on the type of due diligence work you need to support.
1. Kira Systems (now part of Litera)
Kira Systems is an AI-powered contract analysis platform that uses machine learning and natural language processing to review legal documents quickly. It is designed to identify and extract key clauses, terms, dates, parties, and other critical data from contracts.
Why it stands out:
Kira is especially useful when due diligence centers on large contract portfolios. It can help teams review NDAs, lease agreements, loan documents, employment contracts, and other legal agreements with far less manual effort.
Best fit:
M&A transactions, real estate deals, financing transactions, and other matters involving extensive contract review.
Pros:
- Strong clause and data extraction
- Built for legal workflows
- Pre-trained models for common contract types
- Useful reporting features
Cons:
- Can be expensive
- Focused primarily on contract review
- May require training to use advanced features effectively
2. Relativity AI (part of RelativityOne)
Relativity is a well-established e-discovery platform with AI capabilities that help legal teams analyze large volumes of unstructured data. Its features include conceptual search, clustering, and active learning, which can improve review speed and relevance.
Why it stands out:
Relativity AI is valuable when due diligence involves large document collections, investigations, or litigation support. It can help teams identify relevant documents, organize information, and uncover themes or patterns across data sets.
Best fit:
Large-scale investigations, regulatory reviews, litigation support, and due diligence involving substantial electronic data.
Pros:
- Scales well for large data volumes
- Strong search and analytics tools
- Integrates with e-discovery workflows
- Active learning improves results over time
Cons:
- Can be complex to learn
- More suited to document review than broader due diligence needs
- May require technical support for effective administration
3. Gapless
Gapless is an AI-powered platform focused on financial due diligence in M&A. It analyzes financial statements, transactional data, and related documents to identify anomalies, risks, and potential issues that may affect deal terms.
Why it stands out:
Financial due diligence often requires careful reconciliation and trend analysis. Gapless helps automate those tasks and brings attention to unusual patterns, inconsistencies, and possible accounting concerns.
Best fit:
M&A transactions, private equity investments, venture capital diligence, and other financial review processes.
Pros:
- Designed specifically for financial due diligence
- Helps identify financial risks and opportunities
- Automates data extraction and analysis
- Produces practical, actionable insights
Cons:
- Focused mainly on finance
- Does not cover all legal or operational diligence needs
- Less established than some broader platforms
4. Eigen Technologies
Eigen Technologies provides AI tools for extracting structured data from unstructured documents. It uses NLP and machine learning to read and process contracts, financial reports, legal filings, and other document types.
Why it stands out:
Eigen is useful when teams need to convert large volumes of documents into structured, searchable information. It can help populate databases, support data room workflows, and flag specific clauses or terms across a document set.
Best fit:
Complex M&A transactions, compliance projects, contract management, and other data-heavy due diligence work.
Pros:
- Handles a wide range of document types
- Strong data extraction capabilities
- Can be adapted to custom workflows
- Reduces manual data entry and verification
Cons:
- May require setup and customization
- Can have a steeper learning curve
- Integration may require additional effort
5. Seal Software (now part of DocuSign Insight)
Seal Software, now integrated into DocuSign Insight, offers AI-driven contract discovery and analytics. It helps organizations find, organize, and analyze contracts stored across different systems and formats.
Why it stands out:
A complete view of a company’s contractual obligations is a key part of due diligence. Seal can locate agreements that may be buried in shared drives, repositories, or other disconnected systems, then extract important terms such as termination rights, change-of-control provisions, and indemnity obligations.
Best fit:
M&A due diligence, vendor risk reviews, compliance work, and contract discovery across multiple systems.
Pros:
- Strong contract discovery capabilities
- Useful for identifying key contractual risks
- Integrates with broader contract lifecycle management workflows
Cons:
- Primarily contract-focused
- May need to be paired with other tools for full due diligence coverage
- Pricing may be a challenge for smaller firms
6. Cognito
Cognito focuses on AI-powered risk intelligence and identity verification, with particular relevance for financial services and compliance teams. It helps screen individuals and entities against watchlists, sanctions databases, PEP lists, and adverse media sources.
Why it stands out:
Background screening is an important part of many diligence processes. Cognito automates this work and helps teams spot potential compliance, reputational, and regulatory risks more efficiently.
Best fit:
AML and KYC reviews, investment due diligence, third-party risk management, and client or partner onboarding.
Pros:
- Specialized in risk intelligence and identity verification
- Automates screening across large databases
- Supports compliance workflows
- Reduces manual background-check effort
Cons:
- Not a general-purpose document review tool
- Best used alongside other due diligence platforms
- Focuses on screening rather than broader analysis
How to Choose the Right AI Tool for Due Diligence
The best tool depends on the scope of the review, the type of data involved, and your internal workflow. Key factors to consider include:
- Scope of work: Are you reviewing contracts, financials, background risks, or a mix of all three?
- Data type and volume: Large unstructured data sets may call for a platform like Relativity, while structured extraction may be better handled by Eigen.
- Workflow fit: Consider how well the tool integrates with your existing legal tech stack, document management system, or contract lifecycle platform.
- Ease of use: Some tools are designed for legal teams with minimal technical support, while others require more setup and training.
- Accuracy and customization: Make sure the tool performs well on the document types and issues that matter most to your team.
- Reporting: Look for outputs that are clear, usable, and easy to share with decision-makers.
In many cases, a combination of tools is the most effective approach. For example, a team may use one tool for contract review, another for financial analysis, and a third for screening individuals or entities.
Pricing and Value Considerations
AI tools for due diligence come with different pricing models. Some are sold as monthly or annual subscriptions, while others are priced per project, per document, or through custom enterprise agreements.
When evaluating cost, look beyond the sticker price. The real value often comes from time saved, reduced manual effort, improved accuracy, and better risk detection.
Common pricing structures include:
- Subscription models: Better for ongoing use and predictable budgeting
- Usage-based models: Flexible for occasional projects, but costs can rise with volume
- Enterprise pricing: Usually custom-quoted for larger organizations with complex requirements
A demo or trial can help you assess whether the tool fits your workflow and whether the expected efficiency gains justify the cost.
Frequently Asked Questions About AI Tools for Due Diligence
How accurate are AI tools for due diligence?
AI tools can be highly accurate for specific tasks such as clause extraction, document categorization, and data identification. Accuracy depends on the quality of the model, the training data, and the complexity of the documents. Human review is still important for nuanced legal interpretation.
Can AI tools replace human due diligence professionals?
No. AI tools are meant to support, not replace, legal and business professionals. They handle repetitive and data-heavy work, while human judgment remains essential for analysis, interpretation, and decision-making.
What types of documents can AI tools analyze?
Many tools can analyze contracts, financial statements, regulatory filings, corporate records, emails, and internal reports. The exact document types depend on the platform.
How long does implementation take?
Implementation time varies. Some tools can be deployed in days or weeks, while more complex platforms may take several weeks or months, especially if they require integrations or customization.
Are AI due diligence tools compliant with privacy regulations?
Reputable vendors generally follow data privacy and security standards, including requirements related to GDPR and CCPA. It is still important to review data handling policies, encryption practices, and any relevant compliance certifications.
What do AI due diligence tools cost?
Pricing varies widely. Specialized tools may cost a few hundred dollars per month, while enterprise platforms can run into the tens of thousands annually, depending on features, scale, and support.
Conclusion
AI is reshaping due diligence by making document review faster, more consistent, and more scalable. The best AI tools for due diligence can help legal teams, investors, and compliance professionals identify risks sooner, reduce manual work, and improve the quality of their analysis.
No tool can replace professional judgment, but the right platform can make a major difference in speed, coverage, and confidence. Whether your priority is contract review, financial analysis, document discovery, or risk screening, tools like Kira Systems, Relativity AI, Gapless, Eigen Technologies, Seal Software, and Cognito offer strong options to consider.
Choosing the right solution starts with understanding your specific diligence needs and matching them to the platform that best supports your workflow.