Latest / The Series A Show with Fexingo: Early-Stage Funding, Pitch Decks, and Startup Milestones / How Startups Use AI to Automate Investor Outreach
Transcript
- Lucas: There is a scene playing out in hundreds of seed-stage startups right now that would have sounded like science fiction five years ago. A founder sits down on a Monday morning, opens a custom GPT she built herself, feeds it the bios and investment theses of seventy venture partners, and by Wednesday she has sent two hundred personalized emails — each one referencing a specific portfolio company or a talk the partner gave at a conference. Luna: And the partners don't know they're talking to a machine. Lucas: Exactly. Some of them probably suspect it. But the open rates — and more importantly, the reply rates — are competitive with what a human doing the same work would get. I talked to a founder last week who built exactly this. Her startup is a B2B SaaS in the compliance space, and she used a combination of GPT-4 and a simple CRM automation to target three hundred early-stage VCs. She got a forty percent open rate and three term sheets. Luna: Forty percent is absurd for cold email. Standard is like ten to fifteen. Lucas: Right. And the key is the personalization. She didn't just drop a template with a {{first_name}} tag. The model ingested each investor's recent tweets, their Medium articles, the sectors they'd funded in the last six months, and then generated a two-paragraph email that genuinely felt like it came from someone who had done her homework. The investor writes back, and from that point a human takes over. But the initial outreach — the hardest part — is automated. Luna: I get why founders love this. Fundraising is a grind. But does it work for all stages? I feel like once you're past seed, relationships matter more. Lucas: You're right. This is mostly a seed and pre-seed phenomenon. By the time you're raising a Series A, you should already have a warm network. But for first-time founders who don't have a rolodex, this levels the playing field. And the tools are getting cheaper. There are now half a dozen startups selling 'AI fundraising co-pilots' — things like Octave, Warmly, or even just a custom GPT plus a chrome extension. Luna: Let's talk about the counter-argument though. If every founder starts doing this, VCs will get flooded with ai generated emails that all sound the same. The edge disappears. Lucas: True. But that's always been the case with any new tactic. Early adopters win. Then the signal degrades. The founders I've seen get the best results are the ones who use AI to do the drafting but then spend five minutes editing each email to add a truly personal detail. It's not fully autonomous — it's augmented. They still do the research, but the AI saves them the typing. Luna: So it's more of an efficiency play than a replacement. Lucas: Exactly. And it matters because time is the scarcest resource in a fundraise. A founder who can send two hundred quality emails in two days has more bandwidth to actually take meetings and follow up. There's data on this too. A study from DocSend a few months ago showed that founders who send more than fifty personalized outreach emails per week raise their seed round two months faster on average. Luna: Two months can be the difference between making payroll and not. Lucas: It can be existential. And it's not just email. Some founders are now using AI to pre-qualify investors. They'll have a chatbot on their website that, when an investor fills out a contact form, asks a few questions and assigns a score based on fit. The founder only follows up with the top tier. Luna: That feels a little cold to me. I mean, VCs are people too. If I found out I was being scored by a bot before a founder even spoke to me, I'd be put off. Lucas: I think it depends on how it's framed. Some founders are transparent about it — they'll say, 'We use AI to help us prioritize responses so we can spend more time with the investors who are the best fit.' That's hard to argue with. And VCs are starting to use AI on their side too. There are firms that scan thousands of pitch decks automatically. We're moving toward a world where the early stage fundraising funnel is machine to machine. Luna: What about the content of the pitch deck itself? Are AI tools changing how founders build decks? Lucas: Absolutely. Tools like Tome or Gamma let founders generate a full deck from a one-page brief. I've seen decks that were created in fifteen minutes — and they look good. But here's the catch: they often lack the specific narrative that only a founder can provide. The best decks I've seen still have that human story. The AI can help with layout and formatting, but the 'why now' and 'why this team' still needs to come from the founder. Luna: So the bar for what counts as a 'good' deck might actually be rising. If everyone can make a visually polished deck, the differentiator becomes content. Lucas: Exactly right. And that's healthy. It forces founders to think harder about their thesis. On that note — let me step back for a moment. This show exists because of a small group of listeners who chip in each month to keep it ad-free and independent. If these conversations are useful for what you're building or running, you can find us at buy me a coffee dot com slash fexingo. It's a small thing that makes a big difference — and it's the reason we can do deep dives like this without sponsors. Luna: Yeah, it really does. And it's genuinely appreciated. Alright, back to the topic — I want to get into the downside. What happens when a founder relies too much on AI and sends out something that's clearly automated? Lucas: It backfires. I've seen examples where the AI hallucinated a detail — said a partner had invested in a company they never touched, or referenced a talk that didn't happen. That destroys trust instantly. And there's a risk that VCs start filtering out any email that looks ai generated. Some are already using tools to detect gpt written text. Luna: So it's an arms race. Founders build better AI, VCs build better detection. Lucas: It is. But I think the winning approach is to use AI not as a crutch but as a force multiplier. The founders who succeed will be the ones who combine AI efficiency with genuine human insight. They'll use the tools to handle volume, but they'll still spend time on the personal touches that matter. Luna: What about the ethics? Is it deceptive to not disclose that an email was written by AI? Lucas: That's a open question. Some VCs I've spoken to say they don't mind as long as the content is relevant. Others feel it's a breach of trust. I think the safe approach is to be transparent — say 'I used AI to help draft this, but I reviewed it personally.' That's probably where the norm is heading. Luna: Interesting. So the future of fundraising might be less about cold calls and more about smart, scalable personalization. Lucas: Exactly. And the startups that figure out that balance — leveraging AI without losing the human touch — will be the ones that raise efficiently and build lasting relationships.