When talking about start-ups, we automatically think of tech start-ups. Even in the least technical industries, new solutions require some sort of technological innovation to be competitive – whether it’s a simple app or a complex system composed of multiple software and hardware components.  

Today, we’re talking about deep tech start-ups. I especially want to address their technical founders. I’m also a tech guy at heart, this is what I did for the first 10 years of my career. In the past few years, though, working as a Tech Venture Partner for a VC fund (Fortech Investments) and looking at hundreds of pitch decks, I can say that I understand both sides of the table. This is why I want to share a few pitfalls that make fundraising harder, if not impossible, for deep tech start-ups, even though their product is great.  

In the business of start-ups, especially VC-backed ones, you need to understand that what appeals to your scientific and technical peers might not resonate in the same way with investors. And this disconnect can be the stumbling block between your innovative idea and a successfully funded venture.  

Decoding the tech jargon  

One of the most common deal breakers I see is in the content of the pitch deck itself. Highly technical founders, often deeply engrossed in the technical aspects of their products, often forget to translate the technical side to investors. And I don’t mean for them to explain what their product does. I want them to explain how their technical excellence translates into demonstrating market potential, scalability and how that product addresses a specific need in a way that’s both understandable and compelling.  

For example, a solution might be presented in the language of the target customers (as in a sales deck). Still, investors love to see how it is positioned relative to the target market and better understand the use cases to see how important the problem is (typically already known by customers). Even if there is somebody highly technical doing the investment analysis who gets all of it, they still must convey the message to the non-technical investment team members and some of the important aspects can get washed out.   

Hundreds of decks from a multitude of industries enter a VC’s funnel every year. The selection process in the initial phases of filtering is quick so those that require too much initial effort just to be understood, can be easily left out.  

You must control the narrative, by making your presentation clear even for people outside your industry that have never implemented a similar solution. Focus on the why and what, rather than the how.  

Bridging technology and commercial viability  

A strong technical foundation is undeniably important. But how does that translate into your business model? Without a clear connection to commercial applications, even the most robust technologies can fall short of attracting the interest of VCs. Besides looking for a huge market opportunity (USD 1B+), they need to see a clear, practical market-ready application of your technology that gets some demand. If you don’t have any customers yet, some ways to show interest is by building waiting lists, signing Letters of Intent, or doing partnerships.  

A good example of a relevant partnership for a Machine Learning startup that is just building its MVP (or waiting for its medical certification) is to try to get access to training data from potential customers. If they’re willing to do the work to provide the required data, it can show that it is important to them and that they’re in need of better solutions than the status quo.   

Avoid the “solution looking for a problem” trap  

Many deep tech startups are founded by exceptionally talented technical minds who have developed impressive solutions. However, a common pitfall is creating a solution that doesn't necessarily address a specific market need or problem.  

In these cases, founders often end up looking for problems to solve with their technical solutions, and this can be costly. For them, for their company, and for their investors. Pivots are encouraged in our world, and agility in doing so is impressive. But most times, investors can’t afford to wait until you find the perfect problem to solve with your tech. And even more often, by simply having to do that, you send out the wrong signals. It’s better to solve a small niche problem effectively (and expand from there), than to build a platform-level solution that is very generic and does just an ok job at solving random problems from customers that have use-case you’re not even aware of.  

Problem-solving is what creates value for customers that can be captured by your startup, not just having the best solution that does it all. There was a time when new blockchain platforms were appearing just to copy the success of other similar solutions. Without focusing on clear use cases and solving something that customers truly need, they ended up not being used even if they were more performant than the original tech stacks.  

Ensuring your innovation can't be easily duplicated  

In the realm of deep tech, it's not just about being first — it's about being defensible. This is where the concept of 'moats' comes in. A moat is a unique advantage that prevents others from easily replicating or surpassing your innovation. This could be a proprietary technology, a strong patent portfolio, exclusive partnerships, or a significant head start in research and development. Demonstrating a clear moat is crucial in convincing investors that your startup can sustain a competitive edge.  

We started to see a lot of AI wrapper startups – companies built on top of the new-wave LLM platforms that are mostly UI and heavily rely on companies such as OpenAI for the backend. The problem is that building such solutions has become way too easy (it no longer requires top-tier talent, nor strategic training data, and anybody can do them with just some simple prompts that are easy to guess). Even worse, existing big players from the industries can bundle your startup as a feature into their existing products which might have massive distribution channels. As investors, we’d like to see how you position your startup to win if such situations arise. Even if it’s not a data play, show what network effects can drive your growth and why they’re hard for others to replicate.  

Alex Burciu (in opening picture) is a Tech Venture Partner at Fortech Investments. He analyzes investment opportunities from founders in Energy, Healthcare, FinTech, Automotive, and Real Estate for the fund's portfolio. If you're looking for capital funding or joint venture partnerships, drop him a message on Linkedin.