AI PE startups

I am here as a post-MBA, ex-strategy — first consulting/PE DD and then corporate strategy guy in tech industry and now a 2x AI founder. My last company did bleeding-edge AI work with the European Space Agency. Unfortunately, old machine learning tech got commoditised and now I’m working on a new PE-focused startup. Building a new company from scratch is pretty interesting and varied. 80 hour weeks. 70% product, 20% marketing, 10% networking. The product is deal sourcing AI. The initial market is UK lower-mid market with a couple of strong differentiators which scale to US/Europe. There are risks —  1. AI has made product dev easier so market pace has radically picked up. 2. Likelihood of failure is high especially if one ends up building a product no-one wants.

Happy to answer questions anyone has about AI startups here or privately.

Note: I’m open to advisors on advisory board/co-founder.


 

3 Comments
 

Building an AI-focused startup in the private equity space is a bold and exciting move, especially given your background and the rapid pace of AI development. Based on the most helpful WSO content, here are some insights and considerations for your venture:

  1. Market Dynamics and Differentiation:

    • The AI space, particularly in deal sourcing, is becoming increasingly competitive as AI tools and frameworks become more accessible. To stand out, your product must offer unique value propositions that are hard to replicate. For example, leveraging proprietary datasets or developing algorithms tailored to specific PE workflows could be a game-changer.
    • As noted in WSO discussions, PE is still heavily human-centric, with qualitative judgment playing a significant role. Your AI solution should complement this by enhancing decision-making rather than attempting to replace it entirely.
  2. Risks and Challenges:

    • The risk of building a product that doesn't resonate with the market is real. Engaging potential users early in the development process to gather feedback and iterate on your product is crucial. This aligns with the proactive deal sourcing approach highlighted in WSO threads, where understanding industry dynamics and future trends is key.
    • The scalability of your product to markets beyond the UK lower-mid market will depend on its adaptability to different regulatory environments, data availability, and user needs in the US and Europe.
  3. Advisory Board and Networking:

    • Given your openness to advisors, consider reaching out to individuals with deep expertise in both AI and private equity. Their insights could help refine your product and strategy. Networking within the WSO community or similar platforms could connect you with potential advisors or co-founders who share your vision.
  4. AI in PE:

    • As discussed in WSO threads, PE firms are increasingly exploring AI for tasks like deal sourcing, due diligence, and portfolio management. However, the adoption of AI in PE is still in its early stages, presenting both opportunities and challenges for your startup.

Your 80-hour weeks and focus on product development, marketing, and networking reflect the dedication required to succeed in this space. If you have specific questions or need tailored advice, feel free to ask!

Sources: For Reál | The Daily Peel | 1/23/23, Breaking into VC from undergrad...my story, Is Private Equity a Low-IQ Approach to Finance?, Big Tech 2.0, Venture Capital Salary versus BB and Private Equity

I'm an AI bot trained on the most helpful WSO content across 17+ years.
 

In the same space (ignore title). From my experience the segment you’re targeting is usually a whole load of shitcos and wrappers.

The UK has a great technical ML base but the LMM market just doesn’t have much to show for it.

What’s your thesis/experience?

 

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