EP12 - Towards a Legible Asset Class: The Evolution of UVC

University venture capital, or UVC, is entering a new phase of visibility.
Across Europe and globally, more universities are exploring venture funds as a mechanism to translate research into market outcomes. Capital is becoming available.
Institutional interest is increasing. The number of initiatives is growing.

Yet despite this momentum, the segment remains difficult to evaluate.
The challenge is not activity, but coherence.

UVC is visible, but not yet fully legible as an asset class - the underlying activity is clear, but it remains difficult for LPs to aggregate data, benchmark performance, and underwrite the segment coherently.

The Performance Gap Is Structural

Across institutions, performance varies significantly.
Some universities consistently generate spinouts that attract venture capital. Others, despite strong research output, struggle to convert innovation into investable companies.

The difference is rarely explained by scientific quality.
It is primarily structural.

Three elements tend to determine whether a spinout becomes fundable:
the structure of IP ownership, the alignment of equity expectations, and the visibility of the opportunity to external capital.

These factors sit at the intersection of academic systems and market dynamics. When they are misaligned, capital does not engage. When they are structured correctly, access to venture funding increases materially.

This is not a marginal improvement. It is multiplicative.

Compounding Effects in UVC

UVC operates within a feedback loop.

Universities that consistently produce investable opportunities attract more capital.
Capital attracts talent. Talent improves execution. The system compounds.

At the same time, institutions that do not reach this threshold face increasing difficulty catching up. The gap is not static. It expands over time.

This dynamic is well understood in venture capital.
What makes UVC more complex is the institutional environment in which it operates.

Universities must align multiple stakeholders, longer decision cycles, and non-financial objectives with the expectations of venture capital markets.

Small structural differences at the outset lead to significant divergence in outcomes.

The Data Challenge Is Not Absence, but Fragmentation

It would be incorrect to describe UVC as a data-poor environment.

There are strong universities and experienced fund managers. There are also high-quality reports and research initiatives.

The issue is not absence. It is fragmentation.

Different reports use different methodologies.
Data is collected in isolated formats.
Insights remain local rather than cumulative.

From an LP perspective, this creates a structural limitation.

At the level of individual funds, evaluation is often possible.
At the level of the asset class, comparability remains limited.

Benchmarks are not yet consistently defined.
Data is not always easily usable for allocation decisions.

As a result, capital allocation into the segment tends to be selective, even where the underlying opportunity is compelling.

From Fragmented Insights to Accumulated Knowledge

The next phase of UVC development moves beyond increasing activity.
The focus shifts toward integration.

What’s needed is a layer that connects existing knowledge and makes it usable in practice.

This means clearer metrics.
Better comparability across institutions and funds.
Aggregating existing data into formats that support real decision-making.
And improving visibility into patterns and best practices.

Nothing here needs to be replaced.
What exists needs to be connected and made to work as a coherent system.

What is taking shape is not a single solution, but an infrastructure layer —
one that connects universities, investors, and data into a more structured ecosystem.

A quiet evolution.
Less disruption, more maturation of the segment.

The Talent Dimension

Beyond structure and data, there is a talent constraint.

Commercializing research requires a specific type of operator — individuals who understand both academic systems and venture dynamics.

This capability is rare.

Universities often struggle to attract experienced entrepreneurs or venture builders who can translate research into market-oriented ventures.

Where this talent is present, outcomes improve significantly.
Where it is absent, even well-structured systems underperform.

This reinforces the broader point.

UVC is not only a capital problem. It is a system design problem.

Conclusion

University venture capital is not an emerging idea. It is an emerging investment category.

The building blocks are already in place.
Capital is increasingly available.
Interest continues to grow.

What we are seeing now is a system that is active, but not yet fully coordinated.

From an institutional perspective, UVC remains complex to interpret at scale.
Structures differ. Data is fragmented. Comparability is still developing.

For this category to mature as an asset class, it needs alignment.
It needs shared reference points.
And a data layer that connects what already exists.

Because in venture capital, performance compounds.
And the systems that learn faster, allocate better.

Timecode:

00:00 Why Universities Underperform

01:16 Fixing Spinout Funding Gaps

02:16 Value of University VC Funds

02:32 Why Launching Is Complex

04:00 Learning From a Community

05:23 Deep Tech Investing Talent

06:45 Missing Entrepreneur Operators

07:38 Venture Builders for Spinouts

Links:

Karoly Szanto LinkedIn: https://www.linkedin.com/in/karolyszanto1/

Karoly Szanto Personal Website: https://www.karolyszanto.com/

UniPrisma: https://uniprisma.com/

Guests:

Thijmen Meijer: https://www.thijmenmeijer.com/

Transcript:

[00:00:05] Károly Szántó: Based on, on the conversations I had with university stakeholders like Rectors Chance Lawyers, innovation leaders, what I heard from them saying that such an infrastructure that what what we are about to build would deliver value for them because they are not. Informed well enough to make the best possible decisions.

And why that matters for them is because they want their university to perform. And one way to measure the performance is the amount of spinouts from the university. And second, how much of those can attract venture capital investments? If, if we only look at these two and we can also add the number of patents, um, 'cause that that's already measured, we can multiply these numbers, not just increase it like 10%, but we can actually multiply these numbers because currently only 22% of these spinoffs ever get venture capital funding.

And the number one problem is neither the IP policy, the equity stake, and the visibility are in line with the market expectations. It's not very difficult to fix those once you know how to do that, and we are not here to educate them how to do that. We just want to connect the best ones with the ones who still need to learn.

And I think as a, as a university. Uh, leader, uh, you have an easy fix for this inefficiency and the gap is actually, is not a static thing between the best ones and the underperforming ones. The gap is, is growing. So whoever performs well, they, they will perform even better next year because they can attract more, uh, funds and better talent as well.

[00:02:14] Thijmen Meijer: Indeed. So how, what would you say to, uh, current universities that don't have a VC at this moment? What would you, uh, what would you say, how would you, um, what is the value for, uh, for them? Hmm. So when, when we launched the OUEC actually, and, and then when we launched, uh, uni Prisma, um. I received, uh, quite many inbound interest from universities actually from all across the globe.

[00:02:48] Károly Szántó: Um, that wanting to just pick my brain on how to launch a university venture capital fund, and it's not, it's a very complex. Um, different stakeholders. Yeah. Different, different approaches. Yeah. It's, it's super complex. It's more complex than to launch, uh, any VC fund on the market, which is already, which is already super complex and risky.

So, because now as a university, now you have to align with the university's, uh, strategy. Yeah. That is your context and finances. And decision making in universities, uh, it's quite well known that they're not the fastest. Uh, so it's, it, it can go slow. It's very, it can be very bureaucratic and administrative.

Uh, plus then you need to also convince probably some market player, a fund of funds and an outside investor to co-invest into the fund. Right? And lp, so. It's, it's, it's very complex, but I think the value that we can deliver for universities who are playing with the thought of, launching their own fund is to actually learn almost for free.

Like, you need to invest your time, of course, but, uh, but you can learn from others, uh, very easily and apply, uh, those models. But of course, uh, let's not be naive just because you have a playbook. This is how, like how to launch a, a university venture capital fund. Maybe we can write a book and publish it.

[00:04:41] Thijmen Meijer: Yep. Um, I think it would help, but, uh, it doesn't make things happen. So you need people, you need people who actually been there, done that, and to ac this is a very unique. Uh, knowhow. There's not like thousands of people are running around the street with this knowledge. It's very, very niche, very high value, and very niche.

[00:05:06] Károly Szántó: So if we have, um, the community, then this talent, this intelligence would be a lot more available and visible for those who, who require this assistance. Is there any gap in the university VC ecosystem from a talent point of view? Is there any kind of talent that is usually missing, uh, from this environment?

[00:05:38] Thijmen Meijer: Uh, well, the, you have market VCs, uh, that are investing in, in AI or investing in, in B2B software. Uh, but you also have market VCs that are investing in deep tech. Mm-hmm. Which is. Uh, similar, uh, like university VCs, it's, um, research based innovation that, uh, they try to commercialize with the spinoff. It's a different animal, it's a different kind of, uh, thinking.

It's a different kind of, uh, investing. It's more long term, uh, it's more impactful in the end, but it's much, much longer, uh, the ramp up basically than the usual B two P software. The other thing is that if a person actually understands this, but also the, the struggles with the, the academic struggles that they're having, um, meaning, uh, the IP and the patents and all these elements, uh, if they connect that basically to the long term strategy of the company and have the right talents inside the spinoff.

Then this is gold. Hmm, perfect. What I have seen, uh, launching a university venture capital fund during that time when during the launch is the lack of entrepreneurs, like already either ex exited funders or, or successful veteran funders helping the acade, like the researcher team. To, to develop, um, a a little bit of a commercial mindset, uh, a market focused mindset, um, that kind of talent.

[00:07:19] Károly Szántó: I think a lot of universities are struggling to attract that kind of talent. Why? Because the academic environment is not very attractive for entrepreneurs. Usually. There are, of course, uh, exceptions. Yeah. No, absolutely. I agree with you. Um, and I think there's a lot of entrepreneurs that would be willing to do this and are very eager to do this, but indeed, in a certain way, it's not as sexy enough basically than a B2B software apparently.

[00:07:52] Thijmen Meijer: Um. But indeed we see a lot of these, uh, gaps missing I think a lot of, spinoffs could use one of those venture builders, to These entrepreneurs, residents, um, they could use these venture builders actually commercialize the business even, uh, better and faster than that. A, a researcher, a found founder or co-founder can do mm-hmm.

[00:08:16] Károly Szántó: Absolutely.