AI Startup Aims to Automate M&A Research

Published by The Daily Scout

What happened

A startup called DiligenceSquared is using AI and voice agents to make M&A research more affordable. The platform aims to democratize a critical part of the dealmaking process that has historically been expensive and labor-intensive. This follows a broader trend of AI tools disrupting professional services workflows.

Why it matters

DiligenceSquared was founded by former Blackstone principal Frederik Hansen, ex-BCG principal Søren Biltoft, and former Google engineer Harshil Rastogi. The trio combines deep experience in buying, selling, and building the technology behind M&A research. The startup recently closed a $5 million seed round led by Relentless, a new firm from former Index Ventures partner Damir Becirovic. The company's platform utilizes AI-moderated voice agents to conduct in-depth interviews with a target company's customers and executives. This approach aims to automate the commercial due diligence process that has been a costly and manual staple of private equity for decades. A human-in-the-loop quality review by senior consultants ensures the final analysis is accurate before delivery. Traditional M&A due diligence can be a lengthy and expensive process, often taking 60-90 days and costing anywhere from $150,000 to over $500,000 for middle-market deals. These costs, which can represent 1-3% of the total purchase price, are not reimbursed if a deal falls through, creating significant financial risk for potential buyers. The market for AI in mergers and acquisitions is projected to grow by $2.53 billion between 2024 and 2029, with a compound annual growth rate of 37.5%. This growth is driven by AI's ability to enhance the efficiency and accuracy of due diligence, potentially accelerating transaction timelines by up to 50%. Natural language processing (NLP) is a key technology in this space, enabling the analysis of vast amounts of unstructured data from documents like 10-K filings to identify trends, risks, and even predict potential M&A targets. Tools powered by NLP can extract themes, analyze sentiment, and quantify qualitative signals from earnings calls. This automation trend is reshaping consulting workflows, particularly for entry-level roles that traditionally focused on manual research and data collection. A Harvard Business School and BCG experiment found that consultants using GPT-4 completed 12.2% more tasks, 25.1% faster, and with a 40% improvement in quality. DiligenceSquared is not alone in this emerging field. Competitor Bridgetown Research raised a $19 million Series A in February 2026, indicating growing investor confidence in AI-driven solutions for M&A research. These startups are part of a broader movement of AI-native firms predicted to challenge traditional consulting giants by offering more dynamic and data-centric strategic advice.

Key numbers

  • The startup recently closed a $5 million seed round led by Relentless, a new firm from former Index Ventures partner Damir Becirovic.
  • Traditional M&A due diligence can be a lengthy and expensive process, often taking 60-90 days and costing anywhere from $150,000 to over $500,000 for middle-market deals.
  • These costs, which can represent 1-3% of the total purchase price, are not reimbursed if a deal falls through, creating significant financial risk for potential buyers.
  • The market for AI in mergers and acquisitions is projected to grow by $2.53 billion between 2024 and 2029, with a compound annual growth rate of 37.5%.

What happens next

  • The company's platform utilizes AI-moderated voice agents to conduct in-depth interviews with a target company's customers and executives.
  • This approach aims to automate the commercial due diligence process that has been a costly and manual staple of private equity for decades.
  • Natural language processing (NLP) is a key technology in this space, enabling the analysis of vast amounts of unstructured data from documents like 10-K filings to identify trends, risks, and even predict potential M&A targets.

Quick answers

What happened in AI Startup Aims to Automate M&A Research?

A startup called DiligenceSquared is using AI and voice agents to make M&A research more affordable. The platform aims to democratize a critical part of the dealmaking process that has historically been expensive and labor-intensive. This follows a broader trend of AI tools disrupting professional services workflows.

Why does AI Startup Aims to Automate M&A Research matter?

DiligenceSquared was founded by former Blackstone principal Frederik Hansen, ex-BCG principal Søren Biltoft, and former Google engineer Harshil Rastogi. The trio combines deep experience in buying, selling, and building the technology behind M&A research. The startup recently closed a $5 million seed round led by Relentless, a new firm from former Index Ventures partner Damir Becirovic. The company's platform utilizes AI-moderated voice agents to conduct in-depth interviews with a target company's customers and executives. This approach aims to automate the commercial due diligence process that has been a costly and manual staple of private equity for decades. A human-in-the-loop quality review by senior consultants ensures the final analysis is accurate before delivery. Traditional M&A due diligence can be a lengthy and expensive process, often taking 60-90 days and costing anywhere from $150,000 to over $500,000 for middle-market deals. These costs, which can represent 1-3% of the total purchase price, are not reimbursed if a deal falls through, creating significant financial risk for potential buyers. The market for AI in mergers and acquisitions is projected to grow by $2.53 billion between 2024 and 2029, with a compound annual growth rate of 37.5%. This growth is driven by AI's ability to enhance the efficiency and accuracy of due diligence, potentially accelerating transaction timelines by up to 50%. Natural language processing (NLP) is a key technology in this space, enabling the analysis of vast amounts of unstructured data from documents like 10-K filings to identify trends, risks, and even predict potential M&A targets. Tools powered by NLP can extract themes, analyze sentiment, and quantify qualitative signals from earnings calls. This automation trend is reshaping consulting workflows, particularly for entry-level roles that traditionally focused on manual research and data collection. A Harvard Business School and BCG experiment found that consultants using GPT-4 completed 12.2% more tasks, 25.1% faster, and with a 40% improvement in quality. DiligenceSquared is not alone in this emerging field. Competitor Bridgetown Research raised a $19 million Series A in February 2026, indicating growing investor confidence in AI-driven solutions for M&A research. These startups are part of a broader movement of AI-native firms predicted to challenge traditional consulting giants by offering more dynamic and data-centric strategic advice.

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