Free AI Due Diligence: Screen Any Company with AI, for Free
Free AI due diligence means using AI to do the tedious middle of a background check — finding the right records, reading them, and drafting the write-up — without paying for enterprise software. The data was always public; what AI changes is the hours. Instead of opening twenty tabs across SEC EDGAR, the USPTO, CourtListener and a handful of government watchlists, you name a company and a model assembles the sourced first draft. OpenDD does exactly this, free for personal and company use.
It helps to separate the hype from what actually earns its keep. AI is genuinely strong at four things in diligence, and weak at a fifth that matters just as much.
What "AI due diligence" really means
The phrase gets used loosely, so it's worth being precise. AI due diligence is not a secret database and not a credit-bureau feed — it's a model pointed at the same public records a careful analyst would open by hand, doing the fetching, reading and drafting far faster than a person can. It queries those sources, extracts the facts that answer a diligence question, and writes them up with a link back to each one, while the judgment about what the facts mean stays with you.
The public records an AI reads
Most of what matters about a U.S. company is already filed with an agency, and the useful models read straight from those registers rather than second-hand summaries. Financials and corporate structure come from the SEC's EDGAR system, where public registrants file audited 10-Ks, quarterly 10-Qs and material-event 8-Ks.
Intellectual property comes from the USPTO's patent and trademark registers, including the assignment records that show who currently owns a given right. Litigation comes from federal court dockets, much of it mirrored free through CourtListener's RECAP archive, where a case's nature-of-suit code hints at whether it's routine.
Sanctions and export exposure come from government watchlists: OFAC's sanctions lists on the Treasury side and the Bureau of Industry and Security's export lists at Commerce. A sweep across all of these sources is what turns a bare name into a picture — the same set of primary records behind our free corporate due diligence checks.
Where AI actually helps
The first win is retrieval: knowing that a company's real financials live in its 10-K and pulling the right one, rather than the wrong subsidiary's. The second is summarizing — a risk-factors section runs for pages, and a model condenses it without you reading all of it. The third is extraction: lifting the current owner off an assignment record, the officers off a proxy, the numbers off a filing, into a clean table. The fourth is triage in adverse-media screening, where AI grades a wall of search hits so a Reuters story about an indictment doesn't get buried next to an angry blog post. If you're new to the underlying checks, our overview of what due diligence is covers the six types AI is speeding up here.
Where a human still has to look
The thing AI can't hand off is judgment. A watchlist "hit" is a name match until a person confirms it's really the same John Smith; a clean result means "no match found," not "no risk." And whether a finding actually matters — is this lawsuit routine or existential? — depends on the decision you're making, which the model doesn't know. This is why the only trustworthy version of AI diligence is the grounded kind: every claim linked back to the primary record, and honest flags where a source was blocked or coverage is thin. An answer with no citation is a guess, however fluent it sounds.
What AI changes — and what it doesn't
It's easy to overstate what the technology does. AI does not create new information about a company; the 10-K, the assignment record and the docket exist whether or not a model reads them. What changes is only the time it takes to gather and digest them.
A task that once meant an afternoon of tab-juggling — finding the right registrant, reading the risk factors, matching an owner, grading a wall of news hits — compresses into a single pass, which is what makes it realistic to run a check before a small deal rather than skip diligence entirely.
What doesn't change is the ceiling set by the underlying data. If a private company files little, or a source is out of date, the AI can only report what's there. Treat the speed as a way to look at more, not as a reason to trust any single result more.
Why source citations matter more than the prose
The single feature that separates a useful AI report from a plausible-sounding one is the citation. When every figure and finding links to the filing or docket it came from, you can verify it in a click and defend it to a partner, an investor or a court.
Citations also change how you read the report. A cited claim invites a quick check; an uncited paragraph asks you to take the model's word, and general-purpose chatbots are known to state wrong facts confidently and even invent references. Treat an unsourced assertion as unverified until you've traced it yourself.
Citations are also the honest way to handle gaps. A trustworthy tool tells you when a watchlist search returned no match or when a source throttled it, because in diligence, knowing what you couldn't confirm is part of the answer.
How to get a useful AI report in one pass
Feed it a precise subject and let it work in the order a professional would: confirm the legal entity, read the financials, verify the IP and its chain of title, check litigation and sanctions, then scan the news. That's the same sequence we lay out in the guide to running due diligence for free — AI just does the fetching and drafting while you make the calls. When the stakes rise, the report becomes the brief you hand to counsel, not a replacement for them; nothing here is legal advice.
So can AI do due diligence? For the search-and-summarize layer, yes, and doing it free removes the only real reason not to run a check before a deal. For the interpret-and-decide layer, AI is your fastest analyst, not your final one — which is exactly how you'd want it.