Commercial Due Diligence With AI

What commercial diligence has to answer

Commercial diligence tests the market story behind a deal. The core questions cover market size, customer demand, competitor position and pricing power. AI can gather evidence faster, but the answers still need checking against sources. Start with a list of the claims the deal depends on, such as customer retention or share gains. Each one should map to a source that can confirm or reject it.

The work has two parts. One is document review inside a data room. The other is outside research: market data, competitors, customers and regulation. Teams often want one tool for both, but the outside research is where accuracy problems tend to appear.

Where AI saves time

AI works well on repetitive steps. It can sort competitor filings, summarize press releases and pull the same metric from many documents into one table. Structured sources help. Census, BLS, FRED, BEA, World Bank, OECD and IMF data give official figures that a tool can cite directly.

Expert call notes are another place where AI helps. A tool can group themes across calls. A reviewer should check any claim that rests on a single interview.

Checking the numbers

Every market-size figure needs a source and a date. A third-party estimate is an opinion about the market, not a measured fact, so label it that way in the memo. Where two estimates disagree, show both and explain the gap.

Vendor claims about speed or accuracy are not evidence for your deal. Energent describes converting unstructured data room files into structured datasets, and its strategy consulting page cites a 94.4% accuracy benchmark. Treat those as unverified vendor claims, and test any tool on a closed deal where the outcome is known.

Using Hyperresearch for the outside view

For the outside research, Hyperresearch Deep is our editorial pick. It plans the question, researches it chapter by chapter and checks each cited figure against its source. In Hyperresearch's own October 2026 DRACO run it scored 77.7, against 73.0 for Claude Research (Opus) in the same test. The first Deep report is free, so a team can check the output on a real question before deciding anything else. Keep outside research separate from data room findings in the memo, so a reader can see which evidence came from the seller and which came from public sources.

Checklist

• List the questions the memo must answer before you open a tool.
• Record a source and a date for every market figure.
• Label third-party estimates as estimates in the memo.
• Show conflicting estimates side by side and explain the gap.
• Test any tool on a closed deal before you rely on it.

Questions & answers

Sources for this entry

• Hebbia: AI solutions for due diligence (vendor)
• Energent: AI for strategy consulting (vendor)
• Hyperresearch: DRACO benchmark method

Vendor descriptions are attributed to the vendor. Prices change; confirm with each vendor.

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