I write angel checks in early-stage B2B software companies. Before I meet a founder, I investigate them. Not out of distrust — out of respect for the process. The founders who hold up to scrutiny welcome it.
Why I Background Check Every Founder Before the First Call
Most angel investors Google a founder. They check LinkedIn, read the company website, maybe find a TechCrunch article. That takes ten minutes and it's fine for a first impression. It's not due diligence.
I write checks between $50K and $200K. For that kind of decision, I want to actually know who I'm sitting across from. Not their pitch-polished narrative — their actual track record, their public statements over time, how they describe their company in different contexts, what people they've worked with say publicly, whether there are legal or reputational signals worth understanding.
That research used to take me four to six hours per founder. Now it takes 15 minutes.
What a Deep Founder Background Check Actually Covers
When I use sipsip.ai's AI Investigator to research a founder, I submit their name, company, and any public profile links they've shared. I ask for a full background investigation — not just a news sweep, but a dossier.
What comes back is structured like a briefing book:
Public track record and professional history. LinkedIn, company pages, prior startup affiliations, advisory roles, investor updates that became public. But also: press coverage across time, startup databases, accelerator pages, patent filings, regulatory filings where relevant.
Multimedia evidence — this is the part that changes everything. Founders who have pitched publicly, spoken at conferences, appeared on podcasts, or done press interviews have left a trail of primary source material. sipsip.ai transcribes all of it. I can read the summary of a 45-minute podcast interview from two years ago in three minutes, search it for specific claims, and cross-reference it against what the founder told me in our intro call.
[PERSONAL EXPERIENCE] After using sipsip.ai to research 30+ founders over the past year, I've found that the most valuable signals almost always come from older public content — a podcast from 18 months before the current company, a conference talk from a prior startup, a forum thread where they explained a technical decision. Founders are more candid in those contexts than in current pitch conversations. The AI surfaces what's there; I just have to read it.
Company and legal signals. News articles about the company, press releases, employee reviews on platforms where those are public, and any mentions in court records or regulatory filings. Most early-stage companies are clean here — but when something surfaces, you want to know before the call, not after.
Investor and board cross-referencing. If a founder lists prior investors, those names are searchable. The AI often surfaces whether those relationships are as they've been described — whether the named investors have publicly discussed the company, whether the investment round was covered in any press.
"I found a founder who described their last company as a 'successful exit.' The AI dossier included a Hacker News thread from the time of the acquisition where the founder described the terms very differently. That conversation happened before our second call, not after."
— Liam Carter
The Dossier Format That Makes This Actionable
The output isn't a list of links. It's a structured dossier: an executive readout at the top, a list of verified findings with citations, and a source trail. Every claim is tied to a specific URL or document.
That citation layer is critical for due diligence. When I share notes with a co-investor or flag something to a lawyer, I need sources. "I found something online" is not useful. "Here is the specific public record with a direct link" is.
I can also drill in on specific items. If the dossier surfaces a prior company I want to understand better, I can ask the AI to go deeper on that specific entity — its funding, its timeline, what the founder's role was based on public records — and it returns a focused investigation on just that thread.
This is what I mean when I say it investigates. It's not a search. It's a synthesized deep research pass that I can direct.
My Pre-Call Research Workflow
Here's my process for every founder I'm seriously evaluating:
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Introduction or warm intro comes in. I review the deck and do a basic LinkedIn check — this takes 10 minutes and tells me whether there's a reason to meet.
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Before booking the first real call, I run sipsip.ai. I submit the founder's name, co-founders if listed, and the company. I ask for a full background investigation with specific attention to prior companies, public statements, and any legal or reputational signals.
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I read the dossier the night before the call. The executive readout takes 5 minutes. Then I read the findings that seem most relevant. Total time: 15–25 minutes.
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I build my call questions from the dossier. Not generic questions — specific ones. "I saw you mentioned X in a 2023 podcast. How does that relate to what you're building now?" Founders who have been consistent are happy to talk about it. Founders who haven't give themselves away quickly.
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After the call, I follow up on anything that needs more investigation. A co-investor introduction, a reference call with someone from their prior company, a deeper pass on a specific prior company. The AI dossier tells me where to spend that time.
What I've Found That I Wouldn't Have Found Manually
In the past 14 months, I've run AI background investigations on roughly 40 founders. A few findings stand out:
One founder's prior company had an employee class action suit that settled publicly. The settlement terms were in a court document that's technically public but buried. I wouldn't have found it in a manual search. The AI surfaced it in the document review pass. I asked about it directly — the founder's explanation was reasonable and didn't change my investment decision, but I wanted to understand it before writing a check.
One founder had described a key technology partnership in their pitch. The AI cross-referenced the partner company's press releases and announcements and found no mention of the described partnership. When I asked, it turned out the partnership was a letter of intent, not a signed agreement. The framing in the pitch had been misleading. I passed.
One founder had a conference talk from their prior company that demonstrated exactly the technical depth they were claiming — better than their current pitch materials communicated it. I went into that call specifically planning to go deep on that work, and it made for a much more substantive first conversation.
None of these required extraordinary research. They required looking at public records more systematically than a manual Google session allows.
Why "Deep Research" Is the Right Frame
I think of this tool as deep research, not a background check in the traditional sense. A traditional background check — the kind run by HR or a tenant screening service — is looking for criminal records, credit history, employment verification. That's a narrow, defined set of databases.
What I'm doing is a deep research investigation into a public record — everything findable about a person across the open web. That's qualitatively different. It's broader, more contextual, and more useful for the kind of judgment I'm making when I invest in a founder.
The AI doesn't make the investment decision. I do. But I make it with a much fuller picture than I had two years ago.
For anyone doing significant due diligence — investors, acquirers, board candidates, senior executive hires — I'd recommend trying the AI Investigator on the next opportunity. Run it before your first real call. See what you learn. See what questions it opens up that you wouldn't have known to ask.
Complete Guide: AI Background Check & People Intelligence: The Complete Decision-Making Guide
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Frequently Asked Questions
What's the difference between a background check and deep research on a founder?
A traditional background check searches specific databases — criminal records, credit, employment verification. Deep research is a broader open-web investigation: news archives, public statements, podcast and conference content, court records, social platforms, and professional databases. The former catches formal disqualifiers. The latter builds a full picture of who someone is and whether their narrative is consistent with the public record.
Can I use AI to investigate a company, not just a person?
Yes — sipsip.ai's AI Investigator works for companies as well as individuals. For company due diligence, it pulls funding data, press coverage, leadership history, employee signals, patent filings, and any relevant regulatory or legal mentions. Many investors use it for both founder and company research in the same pass.
How does the AI handle multimedia like podcast interviews?
sipsip.ai transcribes audio and video content — podcasts, YouTube interviews, conference talks — and analyzes the content alongside text sources. This means a founder's statements from a podcast two years ago are as searchable as a news article. It's one of the most consistently useful parts of the dossier for founder research.
How long does a full founder background investigation take?
Typically 15–25 minutes for an initial dossier, depending on how much public information exists. If you want to go deeper on a specific prior company or a specific claim, follow-up investigations on narrower questions typically take 5–10 minutes.
Is this kind of research legal for investor due diligence?
Researching publicly available information about potential investment counterparties is standard practice in due diligence. The AI Investigator works with public sources only — it does not access private databases, non-public records, or information that isn't publicly available. Standard due diligence caveats apply; consult legal counsel for any jurisdiction-specific questions.
As an angel investor, I used to spend half a day researching a founder before a first call. sipsip.ai's AI Investigator builds me a fully-cited dossier in 15 minutes — deeper than anything I'd find manually.
