DiligenceSquared Is Using AI and Voice Agents to Make M&A Research Affordable — and It's Working:
The Problem With M&A Research Today:
Every major acquisition starts with the same expensive, time-consuming problem. Before a private equity firm can confidently pull the trigger on a deal, it needs to understand the market, validate the target company's competitive position, and stress-test its assumptions with real customer data. That means hiring the big names — McKinsey, Bain, BCG — to conduct hundreds of expert interviews, synthesize proprietary market data, and produce exhaustive reports that can run 200 pages or more. The price tag? Anywhere from $500,000 to $1 million per engagement.
What makes that cost particularly brutal is when a deal falls through. External adviser fees are not reimbursed if an acquisition doesn't close — which means PE firms have historically delayed bringing in expensive specialists until they are nearly certain about a target. The result is a research bottleneck baked into the heart of every major deal process: firms wait too long to get the insights they need, and the insights they do get cost a fortune.
Enter DiligenceSquared:
A new YC-backed startup believes AI can break that bottleneck entirely.
DiligenceSquared, which emerged from Y Combinator's Fall 2025 cohort, is offering top-tier commercial research at a dramatically lower price point — claiming it can deliver the same quality of analysis that bulge-bracket consultancies charge $500K–$1M for, at just $50,000 per engagement. That's a 90%+ reduction in cost for one of the most critical inputs in the entire M&A process.
The founders are not outsiders taking a swing at an industry they don't understand. Co-founder Frederik Hansen was previously a principal at Blackstone, where he personally commissioned commercial diligence reports for multiple billion-dollar buyouts. His co-founder Søren Biltoft spent seven years in BCG's private equity practice, leading exactly these types of engagements from the consulting side. The third co-founder, Harshil Rastogi, brings the technical horsepower — a former Google engineer who helped build the platform's AI infrastructure. Together, they have the rare combination of domain credibility and technical capability that this kind of disruption requires.
How the AI Voice Agent Model Works:
At the core of DiligenceSquared's platform is a technology increasingly proving its value across industries: AI voice agents. Rather than deploying teams of junior consultants to schedule and conduct interviews with a target company's customers, DiligenceSquared uses AI to handle the interview process at scale — reaching C-suite executives, procurement leads, and other corporate customers of the company under evaluation, and extracting the commercial insights PE firms need.
The model is not fully automated — and that's by design. To ensure that final outputs meet the quality bar demanded by sophisticated institutional investors, the startup involves senior human consultants who review and verify the accuracy of the AI-generated analysis and commercial insights. It is a hybrid approach: AI does the groundwork at speed and scale; experienced humans apply the judgment and credibility that PE clients require before committing hundreds of millions of dollars to a deal.
Why This Changes the Deal Process:
The implications of a 90% cost reduction go beyond simple savings. When commercial diligence costs $500,000, PE firms reserve it for deals they are nearly certain about — late in the process, after enormous time and internal resources have already been spent. When that same research costs $50,000, the calculus changes entirely. Firms can now engage DiligenceSquared earlier in the deal funnel, before they have high conviction, and use the insights to inform whether a deal is even worth pursuing.
Hansen put it plainly: "We are taking these great insights that were previously reserved for the very big decisions, and now we make them more accessible." For mid-market PE funds — which often lack the resources of a Blackstone or KKR — that accessibility is not just convenient; it is a genuine competitive advantage, giving them research capabilities previously available only to the largest players in the industry.
Early Traction and a $5 Million Seed Round:
Despite only launching in October, DiligenceSquared has already completed multiple projects for several of the world's largest PE firms and mid-market funds. That level of early traction — paying enterprise clients, not just pilots — is a meaningful signal in a market where trust and track record are everything. When your customers are evaluating billion-dollar acquisitions, they don't take chances on unproven vendors.
That traction caught the attention of Damir Becirovic, a former partner at Index Ventures.Becirovic led DiligenceSquared's $5 million seed round out of his new venture firm, Relentless — a vote of confidence from someone who has seen hundreds of enterprise startups up close. For a company that only launched months ago, securing a lead investor of that caliber is a strong early validation of both the team and the market opportunity.
A Crowded but Nascent Market:
DiligenceSquared is applying an AI-interview model that has already gained significant traction in consumer research. Startups like Keplar, Outset, and Listen Labs — the latter of which raised $69 million at a $500 million valuation in January — have demonstrated real appetite for AI-powered qualitative research at scale. But Hansen and Biltoft are quick to draw a distinction: the rigor, output format, and institutional standards demanded by private equity due diligence are fundamentally different from consumer research. The buyers, the stakes, and the methodology are not the same.
Competition in the diligence-specific market is already emerging. Bridgetown Research, DiligenceSquared's most direct competitor, raised a $19 million Series A co-led by Accel and Lightspeed in February 2026 — a sign that the market is attracting serious capital and serious players. The race to own AI-powered M&A research is on, and with the PE industry spending billions on commercial diligence every year, the prize is substantial.
What This Means for the Future of M&A:
DiligenceSquared's emergence signals something bigger than one startup's success story. It reflects a broader shift in how AI is beginning to penetrate the most high-stakes, relationship-driven corners of financial services — not by replacing human expertise, but by making it accessible at a price and speed that changes the economics of entire deal processes.
For private equity firms, the message is clear: the informational advantages that once required a McKinsey retainer are becoming available to anyone willing to work with the right AI-native research partner.
And for the bulge-bracket consultancies that have long owned this space, DiligenceSquared is an early sign of the disruption heading their way.
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