#1
The lack of technical experts among investors to assess the relevance of the tech

By nature, deep tech companies rely on niche technical breakthroughs, sometimes even conquering uncharted scientific territories, making the core of their developments difficult to assess from the outside. This is a critical point because the success of these companies often relies on the feasibility of the product. To get VCs in a position where they can consider investing, we can rely on:

• Social proof, like a well-known and cited researcher as a CTO, hiring a significant number of PhDs, or getting respected KOLs on board;

• External due diligence;

• The thesis VCs can have on our domain: quantum computing or nuclear fusion startups benefit from the willingness VCs have to make an investment in these areas, for example.

Nevertheless, all these elements are nothing more than proxies, making fundraising more difficult than in the case of a startup having a working product after a few iterations and users to quantify the traction.

#2
Multiple fundraisings and dilutions

The typical fundraising journey of a company is the following:

• Seed brings you to a prototype you can put in the hands of your users;

• Series A brings you to market and allows you to reach product-market fit;

• Series B helps you accelerate the developments.

In the case of a deep tech company, building a prototype is not something you can do with a Seed only, or it better has to be a big one, which is not an easy thing for the reason above.

Therefore, the fundraising journey is quite different and involves many more fundraisings to finance the development of the product. Generally, they correspond to significant milestones.

Dilution is an important question in our case: on the one hand, investors should understand that our valuation has to increase even if we are still not on the market. On the other hand, founders should be ready not to keep 30% by the time they sell their first product.

#3
Longer development times

Deep tech startups often encounter a frustrating challenge: longer development cycles. This runs counter to the lean startup mentality of rapid iteration and quick delivery to customers. In deep tech, iteration cycles can span years rather than months. It’s essential to keep potential users engaged during this period by communicating progress regularly and involving them in the development process.

#4
Balancing necessary research with a shipping mindset internally

When you are doing breakthrough innovation, you are solving new problems. This requires research efforts, which are often very different from engineering tasks directed toward delivery and shipping. The typical framework of a researcher is “How could I best solve this?” Researchers start from a problem and look for the best possible solution.

On the other hand, engineers start from the constraint of a deadline to achieve a feature and look for the most optimal solution regarding cost and scalability. This is very different.

As a deep tech company, we have to somehow do both: keep the diverging thinking of research, and integrate it within the constrained environment of a start-up. This is an open problem. I haven’t found a perfect solution yet. My best clue is that it comes down to the culture of the company.

#5
Demonstrate traction without an MVP

As deep tech startups progress, securing larger funding rounds becomes imperative. However, without a working prototype to put in users’ hands, quantifying market demand can be challenging. To demonstrate traction convincingly:

• Build a substantial user database or community interested in your technology.

• Secure Letters of Intent (LOIs) from potential customers indicating their intent to adopt your solution.

• Execute paid Proof of Concept (PoC) projects to validate your technology’s feasibility in real-world applications.

These strategies help substantiate market interest, mitigate investor concerns, and provide evidence of your technology’s potential value.