While foundational AI companies like OpenAI or Anthropic might get most of the press these days, a vast majority of fundraising deals are happening around so-called “wrapper” startups. These are ventures that don’t build new foundational models but instead wrap around preexisting AI models for industry-specific use cases.
I’ve seen and worked on countless wrapper decks and time and time again I see some common mistakes from founders looking to fundraise. Luckily, it’s not too hard to mitigate the most glaring pitfalls and create a winning pitch.
Mistake #1: Making It All About AI Instead of Problems
Picture this: You’re pitching your new AI-powered legal research tool to a VC. Your first slide proudly proclaims “Making AI Accessible to Lawyers!” accompanied by floating AI buzzwords and a generic chat interface screenshot.
Cue VCs tuning you out and looking at their phone
VCs know that no managing partner at a law firm wakes up thinking “Gosh, I really need more AI in my life!” What a law partner might actually think is “We’re spending 40% of our associates’ time on document review, and we’re still missing critical details.”
Let’s look at two different hypothetical value propositions for the same legal tech product:
Bad pitch: “LegalAI – Democratizing artificial intelligence for law firms with an intuitive interface powered by advanced language models.”
Good pitch: “LegalAI – Cut document review time by 70% while catching 2x more precedent-relevant details. Already saving $400K annually for firms like Smith & Associates.”
See the difference? The second one leads with concrete industry pain points and quantifiable results. The AI is just the enabler, not the star. “Lack of AI” is not a user problem – grueling document review work is.
Mistake #2: Being Too Broad With Your Market
I get it – you want to show the massive TAM. But saying your AI wrapper works for “all professional services firms” or “any company doing customer service” is a red flag. It signals you don’t deeply understand any single vertical. You don’t have the luxury of a groundbreaking foundational model that can cast a massive net, you’ll need to narrow your focus to break through the noise.
Taking our legal tech example: A bad market slide might be: “Target market: All law firms ($400B market)” A better market slide might be: “Target market: Mid-size litigation firms (200-500 lawyers) specializing in commercial disputes
- 850 firms in the US match this profile
- Currently spending $2.2M/year each on document review
- Early adopters of tech (78% already use e-discovery tools)
- Proven willingness to pay ($200K+ annual software budgets)”
- Market size = 850 * LegalAI Average Annual Contract Value
The bad slide naively implies you’ll be replacing the entire legal industry with your product. The good slide shows you understand your industry and its pain points better than anyone else.
Gust’s Mission Control can guide early founders through all sorts of complex startup hurdles.
Mistake #3: Weak Competitive Moat Story
With every AI wrapper pitch there’s an elephant in the room. Investors are immediately wondering “What stops OpenAI from doing this?” or “What prevents competitors from copying you?”, they need better answers than “first-mover advantage” or “better UI.”
This concern gets more acute at different stages:
Seed stage: Focus on speed of execution in multiple areas of traction
- “First mover in litigation prep space with 5 paying customers”
- “Building proprietary dataset of 50,000 annotated legal documents”
- “Key partnerships with 3 bar associations”
Series A: Show deepening moat
- “Network effects from collaborative case law annotations”
- “40% of US litigation firms now contributing to knowledge base”
- “ML models fine-tuned on 2M legal-specific interactions”
Series B+: Demonstrate platform potential
- “70% of customers now using 3+ products in our suite”
- “Integration with 15 major legal practice management systems”
- “API platform with 40 third-party developers building on top”
Mistake #4: Neglecting the Human Element
Too many AI wrapper pitches read like technical documentation. They forget that successful B2B software isn’t just about features – it’s about change management and user adoption.
Take these two approaches:
Tech-heavy pitch: “Our system uses RAG-based retrieval with custom embeddings and implements RLHF for response optimization.”
Human-centric pitch: “We’ve designed for how lawyers actually work:
- Preserves existing workflow in Westlaw/LexisNexis
- Associates can review AI findings in familiar Word format
- Built-in explanations of AI reasoning that satisfy ethics committees
- Training program co-developed with AmLaw 100 partners”
This mistake is similar to the previously mentioned mistake of describing your problem as a lack of AI. Except in this case on your solution slide you need to again make sure you aren’t just focusing on AI bells and whistles.
The Bottom Line
The era of “AI + Industry = $$” pitches is over. It’s no more tenable than the previous wave of “Crypto + Industry = $$”. Successful AI wrapper pitches today need to:
- Solve specific, valuable problems
- Show deep vertical expertise
- Build compelling moats beyond the AI
- Demonstrate real understanding of user adoption
Remember: VCs see dozens of AI wrapper pitches every week. Your job isn’t to convince them that AI is transformative – it’s to show them why your specific application of AI will create an enduring, lucrative business in your chosen market.
Gust’s Mission Control can guide early founders through all sorts of complex startup hurdles.
This article is intended for informational purposes only, and doesn’t constitute tax, accounting, or legal advice. Everyone’s situation is different! For advice in light of your unique circumstances, consult a tax advisor, accountant, or lawyer.
