I Sold My AI Startup Before Revenue: Here's What Investors Missed - And Founders Shouldn't
The greatest long-term value in AI will come from companies solving deep technical challenges at the model and infrastructure level rather than application-layer products built on existing AI platforms, writes angel investor Alexander Kardos-Nyheim. In this guest commentary he shares processes and questions he uses to determine the investability of an AI startup. Guest Author By Alexander Kardos-Nyheim I sold my AI research company while I was qualifying as a lawyer in the U.K. I built Safe Sign Technologies with researchers from Cambridge , DeepMind , Harvard and MIT who believed in the mission enough to trust a 21-year-old law student to lead the ship.
Key Takeaways
- Roughly 20 months later , when Thomson Reuters acquired us, it was the first time in its 170-year history it bought a company pre-revenue.
- Investors always asked about the product and the traction.
U.K. investors passed, and I ended up raising most of our funding in the United States.
- However, the capital and the conviction have also pooled around a few names that were already incumbent.
OpenAI , Anthropic and xAI took roughly 97% of it, and every other foundational AI company in the world shared what was left.
- A real advance in training efficiency, model architecture and inference cost is the work that will still matter in five years, long after most of today's wrappers have been priced out or absorbed.
Asking the right questions So the questions I ask AI founders are: Is your technical team, scientist-for-scientist, equal to or better than the team at DeepMind?
- Do not build to look fundable this quarter.
Stats & Key Facts
- #Roughly 20 months later , when Thomson Reuters acquired us, it was the first time in its 170-year history it bought a company pre-revenue.
- #Backing founders in the foundational layer In the first quarter of 2026, foundational AI startups raised around $178 billion .
- #OpenAI , Anthropic and xAI took roughly 97% of it, and every other foundational AI company in the world shared what was left.
Our published papers put the model among the best in the world at legal reasoning, and we trained it for a fraction of what the large labs were spending. We had been a quieter version of "the DeepSeek story," developing very capable models using novel algorithms with huge capital efficiency. None of that counted for much in the rooms I walked into.
Investors always asked about the product and the traction. U.K. investors passed, and I ended up raising most of our funding in the United States. I back founders now, and the things I weigh have stayed consistent.
As a founder, I was told again and again that science meant little until it was bolted onto a product. That test was wrong then and I believe it is fatal now. Backing founders in the foundational layer In the first quarter of 2026, foundational AI startups raised around $178 billion .
For more details please read the original article at Crunchbase News.
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