DiligenceSquared, part of Y Combinator's Fall 2025 cohort, claims it can deliver top-tier consultancy-quality commercial research at a fraction of traditional cost. The pitch is simple: use artificial intelligence to do what management consultants charge half a million dollars to do, then have experienced humans verify the work.
The business problem is real. PE firms pay $500,000 to $1 million for McKinsey, Bain, or BCG to interview dozens of corporate customers, including C-suite executives, and produce 200-page reports synthesizing those insights with proprietary market data. DiligenceSquared claims it can provide the analysis for just $50,000. If that margin gap sounds too wide to be true, consider the mechanics: instead of relying on expensive management consultants, the startup uses AI voice agents to conduct interviews with customers of the companies the PE firms are considering buying.
The founders have credibility in this space. Co-founders Frederik Hansen and Søren Biltoft possess deep expertise in private equity due diligence; Hansen was formerly a principal at Blackstone, where he commissioned these reports for multiple billion-dollar buyouts, while Biltoft spent seven years in BCG's private equity practice leading these types of diligence efforts. Since launching in October, their industry experience has helped DiligenceSquared complete multiple projects for several of the world's largest PE firms and mid-market funds.
Where human judgment still matters
Here's where DiligenceSquared guards against the obvious criticism: AI-generated analysis without human review. To ensure the quality of the analysis, DiligenceSquared involves senior human consultants who verify the accuracy and commercial insights of the final output. This hybrid model is deliberate and addresses a legitimate concern about delegating high-stakes decisions to machine-generated recommendations.
The startup is not alone in spotting this opportunity. Its main competitor, Bridgetown Research, raised a $19 million Series A co-led by Accel and Lightspeed in February 2026. The investor appetite signals a genuine market demand for alternatives to traditional consulting models.
The pragmatic middle ground
DiligenceSquared's model reflects a broader truth about AI adoption in professional services. The real value is rarely in replacing human expertise entirely. Instead, it lies in automating time-consuming legwork so experienced professionals can focus on judgment and interpretation. If AI handles structured customer interviews and initial synthesis, human consultants spend their time on the harder questions: what does this data mean for the investment thesis? What risks does the market miss?
This trade-off makes economic sense, particularly for mid-market PE firms facing margin pressure. It also acknowledges an uncomfortable reality for elite consulting practices: many of their traditional due diligence engagements involve significant routine work that technology can handle faster and cheaper. That doesn't devalue expert judgment; it reallocates where that judgment creates genuine advantage.
The test ahead is execution at scale. Can these voice agents truly capture the nuance of customer conversations? Will the human verification layer catch real problems, or will it become a rubber-stamp? These questions matter less in theory and more in the crucible of actual deal outcomes. Investors will ultimately judge DiligenceSquared not by its funding round but by whether its research prevents bad acquisitions and surfaces opportunities consultants miss.