E96 [AI-Translated] SEF Growth | Crowdfunding | Mega-Seeds | Follow-on | Legal AI | Mosaic | Moonlight AI | NIRLAB

00:00:00: The original podcast was recorded

00:00:02: in German.

00:00:03: This podcast

00:00:12: Hello, welcome to Burn Rate the Venture Insider podcast.

00:00:15: I'm speaking here with Guy Gjufredi about The Startup Scene With a focus on venture capital.

00:00:20: We have arrived at episode ninety six and are approaching the hundredth episode.

00:00:24: we Are recording on May twentieth At nine o'clock in the evening.

00:00:28: this podcast is sponsored by our partners omniumandupscale.ch.

00:00:34: So guy what are today's topics?

00:00:36: Today in the news we have the sef growth high potential award or rather who won it?

00:00:43: then the positive developments and the swiss crowdfunding market.

00:00:46: And mega early stage rounds meaning financing rounds larger than one billion which we are seeing more and more worldwide, the main topic revolves around rapidly successive financing rounds at different meeting higher valuations.

00:01:00: on the listener question goes into direction of Do legal AI companies still have a reason to exist when open AI, Anthropic and so on keep getting better?

00:01:10: And at the end as always we come to the transaction of The Week.

00:01:15: Well Guy tomorrow are Swiss start-up days.

00:01:17: will you be there?

00:01:18: Absolutely!

00:01:20: Every year Burn is what could call home game for me... ...and this year again We've got a panel together with Burner Cantonal Bank & AR Reventures where we'll discuss When Angels Are Good whether they are even needed at all and how to best get access to angels.

00:01:37: Very good, very exciting!

00:01:39: All right let's move to the news.

00:01:40: in The First News Story we look at five Swiss scale-ups that were awarded the SEF Growth High Potential label by the Swiss Economic Forum.

00:01:48: .The label goes to companies with strong growth strategies and high market potential.

00:01:53: it is intended to strengthen their visibility and credibility toward various stakeholders such as customers suppliers or financing partners.

00:02:02: The companies awarded were, I'll quickly read them out.

00:02:06: Tiny Fish, Grape Insurance Green Tech Wally and BC Platforms.

00:02:11: Five companies from very different sectors ranging from fast casual sushi to employee insurance and body temperature sensors all the way to payment infrastructure and real-world health data.

00:02:22: Guy, what does this selection say about the Swiss scale up market for you?

00:02:26: I would say it mainly shows how broadly positioned the Swiss Scale Up ecosystem has become by now.

00:02:33: we are not only talking about classic software startups here but really about very different business models.

00:02:39: tiny fish is scaling a compact take away sushi model with centralized production.

00:02:44: Grape insurance combines employee insurance with HR and payroll software.

00:02:49: GreenTech comes out of ETH, uses sensors for applications in sports heat exposure and safety critical professions.

00:02:58: Then Wally is building a unified payment platform across online and offline channels which also very exciting And BC Platforms works with Federated Infrastructure For Health Data.

00:03:10: This shows that Swiss scale-ups are not only growing in hype sectors but often through specialized technologies, clean processes and also strong B-to-B use cases.

00:03:20: Max why is such a label even relevant for scaleups?

00:03:23: In the end isn't it really just revenue in growth that count or am I seeing that wrong?

00:03:28: no i'm also an absolute KPI fetishist.

00:03:32: Revenue and growth are of course decisive That's clear.

00:03:36: But especially in the scaleup phase It's also about trust.

00:03:40: These companies need to win larger customers, build partnerships secure financing and often hopefully also expand and scale internationally.

00:03:50: And a label like the SEF growth high potential label can help with that because it acts as a kind of seal-of quality.

00:03:57: its strengthens positioning toward these stakeholder groups I mentioned and also helps for example in employer branding when searching for suitable employees.

00:04:07: In addition, the companies receive access to growth modules expert coaching a strategic assessment by professionals and of course access.

00:04:17: I myself worked there at SEF during my studies, and today i'm also active as a coach in the upscaler program.

00:04:26: And naturally see the potential that this label actually brings with it.

00:04:32: So for scale-ups It is very valuable because they no longer only have to prove their idea works.

00:04:39: They simply show how they can scale professionally and repeatedly.

00:04:45: Then let's look at the Swiss crowdfunding market.

00:04:47: after three rather weaker years, although it was also written as weak-years.

00:04:52: I wouldn't see it that way!

00:04:54: Let's say after three years with somewhat more moderate growth we are now seeing significant growth in the crowd funding market again for the first time.

00:05:02: according to The New Crowdfunding Monitor Switzerland by Lucerne University of Applied Sciences total volume rose to six hundred thirty million Swiss francs.

00:05:14: The market therefore remains below the record level of two thousand twenty one, but clearly shows signs.

00:05:23: This

00:05:39: segment grew by around thirty-eight percent to two hundred seventy five million Swiss francs.

00:05:46: One reason for this is the stricter equity requirements for banks since the beginning of twenty twenty five, and this naturally makes bank financing for real estate developers more expensive or harder to access.

00:05:58: as a result alternative financing platforms such as crowd lending are increasingly coming into play.

00:06:06: And what about crowd-supporting and crowd donating?

00:06:09: There are many different forms of crowdfunding.

00:06:13: Here, we're talking projects like donations or other support models.

00:06:18: Last year there was also a positive development here.

00:06:20: Crowd supporting & crowd donating grew again for the first time since twenty twenty Namely by around thirty percent to thirty five million Swiss francs.

00:06:28: A remarkable nine thousand two hundred eighty eight project were financed in total.

00:06:34: That's already substantial number.

00:06:36: Particularly strong was the sports and health category, which led others with a volume of thirteen million Swiss francs.

00:06:43: It is also interesting that platforms are increasingly relying on new models such as sponsorship activities in which members—meaning sponsors—can participate in deciding how funds are

00:06:53: distributed.".

00:06:54: To summarize one can say that the Swiss crowdfunding market... ...is on the rise again.

00:06:59: total volume increased significantly last year.

00:07:03: The growth mainly comes from crowd lending as we learned from you, meaning real estate financing.

00:07:09: And at the same time crowd supporting and crowd donating are also recovering now for twenty-twenty six which We Also researched.

00:07:17: experts expect further growth especially in Real Estate Crowd Lending.

00:07:22: this makes crowdfunding In Switzerland more relevant again both For companies and for private projects and alternative Financing.

00:07:31: In the third news story this week, we are talking about a trend in the venture capital market that is making headlines especially in the AI sector so-called mega seed rounds.

00:07:42: According to Pitchbook –a study published these days– some AI startups have recently raised seed financings in range of one billion dollars or more.

00:07:51: Examples include Advanced Machine Intelligence by Yan Likun Or World Labs By Feifei Li Or also Ineffable Intelligence.

00:08:00: At first glance, this sounds like a strong development but many early stage investors rather see it as a warning signal.

00:08:08: Their concern is too much capital, to early can harm startups because it can displace discipline focus and real product market fit.

00:08:16: Because start-ups then focused too strongly on the product and the tech instead of the market because they have no pressure since they have so much capital sitting in the bank account.

00:08:26: Eve why do investors now view these huge seed rounds critically?

00:08:31: as an investor yourself?

00:08:33: How do you fundamentally assess this?

00:08:34: Well,

00:08:35: I mean it is naturally critical for all smaller investors already simply because of the size.

00:08:39: Nobody can participate and It's an enormous bet.

00:08:42: but The main point is also This a large financing round Is not in itself A good strategy.

00:08:49: that has Already been mentioned.

00:08:51: i mean Discipline still Has to be there And more money does Not automatically Mean a better company.

00:08:57: A higher valuation In the seed Round Also Does not mean That the Company as a higher chance of achieving a higher exit.

00:09:05: And I think, especially in the seed phase it's about learning as quickly as possible talking to customers and finding out whether they really want the product being developed and whether it actually solves a real problem meaning whether there is willingness to pay for the products somewhere.

00:09:23: uh...and if you don't have too much money then you naturally try to use the little money efficiently and therefore you can also learn from inexpensive mistakes.

00:09:33: And if a startup receives an extreme amount of capital very early on, then this automatically reduces the pressure somewhat to speak with customers.

00:09:43: They maybe focus a bit less and perhaps also work a bit more efficiently pay less attention too salaries which are important in the early phase.

00:09:52: ultimately mistakes from what you learn build the company become extremely expensive quickly And investors in the Pitchbook article therefore also say that limited resources can even be very helpful because they force founders to set priorities, whereas too much money can lead to a team scaling quickly and getting somewhat distracted before it is even clear whether product market fit exists.

00:10:17: Max does this mean that large seed rounds are fundamentally bad or Is This Mainly A Phenomenon Specific To AI?

00:10:25: I do think there are special cases particularly In AI Foundation models, infrastructure large research teams.

00:10:32: as we have seen computing power meaning compute.

00:10:36: has incredibly extreme requirements.

00:10:38: It's simply very, very expensive and has become more expensive.

00:10:42: therefore in individual cases it can certainly be understandable to raise a lot of capital early but if you look at it a bit more granularly then these are more exceptions.

00:10:53: this is not a blueprint for all startups across the broader US market.

00:10:57: The median seed round is around three million dollars.

00:11:00: that shows how far removed these mega rounds actually are from reality or the normal market.

00:11:07: The main problem is the signal it sends to other founders.

00:11:11: if mega rounds are perceived as a model for success, then a kind of FOMO effect emerges and founders may think they need to raise as much money as possible even though they don't need it.

00:11:23: we're already seeing some of that in Switzerland right now.

00:11:25: when we look at cases but in the early stage what counts?

00:11:29: Is not the size of the round But whether startup can demonstrate real demand In other words product market fit.

00:11:36: So we can summarize it like this, mega seed rounds in the AI sector generate a lot of attention but are not automatically a sign of sustainable success as investors.

00:11:46: I would definitely also add ourselves to The Voices In The Pitch Book report.

00:11:51: We also warn that too much capital too early can distract founders from what really matters.

00:11:57: That means understanding customers sharpening.

00:12:03: For capital-intensive AI startups, a large seed round may make sense in individual cases.

00:12:09: But for most founders the key lesson remains it is not the size of the financing around that determines success but focus discipline and naturally the ability to build real traction with limited resources.

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00:13:36: Very good!

00:13:37: Let's move on todays main topic.

00:13:39: We are talking about a phenomenon that fits very well with the current AI and venture euphoria.

00:13:45: And also, with The Last News topic startups are raising increasingly larger financing rounds ever more quickly sometimes directly after the previous round.

00:13:54: in the past A rhythm of twelve to eighteen months between two rounds was normal.

00:13:59: I can still remember it.

00:14:01: It wasn't that long ago.

00:14:02: Then it became nine to twelve months, later six to nine months and today we are seeing cases in which companies want to raise new capital again after just a few weeks or even days.

00:14:12: These so-called fast follows raise an exciting question Is this a sign of strong demand?

00:14:18: And major opportunities Or rather already a warning sign of possible overheating?

00:14:23: We currently have an example Core Automation, a young AI startup that apparently wants to raise several hundred million dollars again shortly after large round at significantly higher valuation.

00:14:36: Behind this are various factors.

00:14:38: there is lot of capital in the market for these startups naturally also strong competition among investors.

00:14:45: We are seeing that very clearly again now.

00:14:47: And of course, there also strategic participating in this sector such as NVIDIA and similar companies which not only investing but can potentially become future customers or ecosystem partners therefore naturally have a certain amount power when it comes to investing.

00:15:06: But is exactly where the problem begins.

00:15:09: valuations often appear more clear cut from outside than they actually.

00:15:13: Sometimes the higher valuation of a follow-on round is communicated while large portion capital actually flowed at lower conditions.

00:15:22: That can create an illusion on demand and this illusion quickly become reality.

00:15:27: in VC world, you know saying fake it till you make it.

00:15:31: And people then communicate that they have already raised such and such an amount, although in reality Is that more of a positive signal for you in the sense, that big market is emerging right now?

00:16:02: or are rather skeptical?

00:16:04: You know me and what I'm going to answer here.

00:16:07: I am naturally sceptical at first.

00:16:09: why does someone want call for significantly higher valuation so shortly after already raising a lot capital ideally also having run way over twenty four months but not automatically negative either.

00:16:23: A quick follow-on round can make sense if something substantial has changed between the rounds in a short period of time.

00:16:34: For example, huge customer contract came over signed major technical breakthrough was achieved and strategic partner joined in.

00:16:42: who massively accelerate sales or proves that potential?

00:16:46: Or there is a market window that must be used immediately.

00:16:49: We also know cases not necessarily at a massively higher valuation, but for a quick follow-on round where investors look around too late and then still need few months for DD and it's too late to jump into the original round.

00:17:02: Then such investors are admitted as somewhat high evaluation due to de-risking of startup through additional runway.

00:17:11: But that is not because milestones were reached.

00:17:14: So, definitely also exists in the Swiss ecosystem.

00:17:16: That's then called a second closing.

00:17:19: We frequently discuss this here.

00:17:22: For me one of first questions I ask myself Is what has actually changed apart from momentum if capital being raised again so quickly and at significantly higher valuation?

00:17:36: The founders or fundraisers really need to explain very precisely why this new valuation is actually justified.

00:17:43: And naturally that then has to be verifiable in DD with corresponding contracts and breakthroughs, especially an AI.

00:17:50: it's of course clear.

00:17:51: we are talking about enormous capital requirements.

00:17:54: compute talent distribution.

00:17:56: everything in the sector costs an enormous amount money but capital requirement alone do not justify evaluation.

00:18:04: Personally, I am not a fan of founders using dilution from the financing round as justification for evaluation.

00:18:12: That is not an intrinsic value but only a strategy for next financing round.

00:18:17: and if you raise three million more or twice as much then valuation should also be significantly higher.

00:18:26: What matters to me is whether the additional capital creates a real advantage or merely serves to continue extending.

00:18:37: And then the question is if you do another round one month later, what valuation to use now?

00:18:46: Do you again used a fifteen because your ready closed.

00:18:49: The capital increase has been implemented.

00:18:51: everything was also reflected in the cap table as well as in the registers and so on in the share register and so forth are not?

00:18:57: you probably go ahead.

00:18:58: take the eighteen million post money.

00:19:00: that would probably still be more defensible although even there it's only one months later.

00:19:05: they're our question marks.

00:19:06: What fundamentally changed in that time?

00:19:08: But if you go even higher than the post-money and say, now I'll do twenty five then i agree with you.

00:19:13: That is probably rather questionable.

00:19:15: but Do You Fundamentally also see a danger for pricing discipline In The Venture Market If These Fast Follows Become The Order Of The Day.

00:19:24: Absolutely Pricing Discipline Is The Be All And End All For Success.

00:19:32: There are many investors who don't pay close attention to valuations.

00:19:36: Maybe we're a bit pickier here and look at them very carefully so that in the end, The problem is that these rounds don't act in isolation.

00:19:57: If a startup gets evaluation four times higher after a short time, then it immediately becomes a comparison point for other founders and not only in the same sector.

00:20:06: Then arguments come up like if they got that valuation why shouldn't we?

00:20:10: Our start-up is actually much better And solves the problem in a better way.

00:20:14: We know that well.

00:20:15: Every founder is very convinced of their idea and knows why it's better than the competitors.

00:20:19: And through this, new pricing anchors emerge that often have less to do with fundamentals then with scarcity attempts to generate FOMO and signaling effects.

00:20:28: If investors don't want to miss the rounds in end they play along or negotiate well with the founders.

00:20:35: The founders naturally see themselves in a strong position not sell below market.

00:20:41: suddenly entire price level shifts without any real fundamental added value behind it and that is definitely dangerous in boom phases.

00:20:49: In such times, It may appear rational because there's always someone willing to enter at an even higher price.

00:20:55: we saw very clearly.

00:20:58: But eventually, the company has to actually grow into that valuation.

00:21:02: And if that doesn't happen then down rounds arise difficult cap tables and disappointed expectations among employees who received ESOPs at high valuations as well as investors who entered late.

00:21:14: Then you get a downward spiral.

00:21:16: I hope we don't fall back in too quickly.

00:21:19: We are only just emerging from last downward spiral And for me, pricing discipline is therefore especially important in such markets.

00:21:31: Not because one shouldn't make bold bets but because you really need to understand what you are actually paying for?

00:21:36: Is it traction or merely access to a hot

00:21:39: story?".

00:21:41: Hey!

00:21:41: I'm part of it and can now show on my deck the LPs that i was able to invest an open AI at x-hundred billion.

00:21:50: Max how do you see mainly an AI-specific phenomenon?

00:21:54: because there is currently such an enormous capital requirement or because strategic interest has also entered the market.

00:22:02: Or are we seeing a pattern here that returns in every boom cycle?

00:22:05: Before I answer, maybe one more addition... It's always funny when start up comes to me and says We would be looking at evaluation of fifty million.

00:22:14: Okay And you know i come from valuation work.

00:22:17: I once had the opportunity to run a valuation firm.

00:22:20: And then my question is always, okay how exactly did you arrive at this valuation?

00:22:26: The most common answer from the startup is because someone paid that price.

00:22:30: and i say Okay but that still isn't an actual derivation of the

00:22:34: valuation.".

00:22:35: Then How did you arrive at the valuation?

00:22:44: And very often, the answer is something like we don't disclose that or comparables were used.

00:22:49: Or a DCF on steroids but actually showing how they valued it.

00:22:53: That is very rare and I really think that's a problem in the industry.

00:22:58: Sure You can argue supply-and-demand if someone pays that price then thats'the price.

00:23:03: But for us its huge because there always somebody who thinks an incredibly high price is justified.

00:23:11: It then isn't necessarily about finding the best investors, but simply those willing to pay the highest price.

00:23:18: Meaning whoever searches long enough will find someone.

00:23:22: they simply keep searching until And I don't think that is necessarily a healthy development.

00:23:30: But again, you can look at it from two sides.

00:23:32: You can also say if someone pays It then That's the market.

00:23:36: but as you also said At some point The rebound comes.

00:23:39: at Some point you have to grow into the valuation?

00:23:53: It is mainly an AI topic, it's a major accelerator at the moment.

00:24:01: There it is effectively case that exactly this happening because they simply need and insane amount of capital.

00:24:09: And what is fascinating about AI startups Is that don't really scale when are young.

00:24:15: Its actually opposite scaling.

00:24:17: They need more compute.

00:24:19: That's funny part.

00:24:20: We want to scale.

00:24:22: Yes, exactly.

00:24:23: In the first three or four years you scale negatively.

00:24:26: You need so much money and capital And then naturally after a few months they come back and say hey We've grown incredibly but now we need five times more cash For small fund.

00:24:41: that may be suboptimal.

00:24:42: If you are Andreessen Horowitz no problem.

00:24:45: Then probably already reserved thirty million for startup anyway Exactly.

00:24:49: But still it is pattern from previous boom cycles.

00:24:53: In every phase where a lot of capital meets a few supposed winners, financing rounds become faster valuations more aggressive and narratives naturally also becomes very important.

00:25:05: how do you sell the whole thing that is?

00:25:09: and later one often realizes that part of it was also a bit of self-congratulation, which is then rather suboptimal.

00:25:16: Yes!

00:25:17: If you now look at this situation from an investor perspective what would the startup specifically need to show for you?

00:25:24: To consider a quick follow on round truly justified And From What Point Onward?

00:25:29: Would It Seem More Like Financial Engineering Than Real Company Development?

00:25:34: I noted down three things here that a startup would have to show if they come with follow-on round at higher valuation.

00:25:41: First, there has been real change since the last round meaning not just more attention or new conversations but measurable progress.

00:25:49: I already mentioned it before customer revenue product maturity.

00:25:54: It can also be technical performance Or a new strategic advantage That didn't previously exist.

00:26:02: We often see that with American companies, where there are ongoing legal disputes and if they emerge successfully from one of those.

00:26:10: That can naturally also be a valuation trigger.

00:26:13: Second, there has to be a very clear use of capital.

00:26:16: If the company can say with this money we secure additional compute for eighteen months We continue building sales in three core markets or we make an acquisition that massively accelerates us then That is something entirely different from hey There's still some money lying around on the street.

00:26:31: Let's just raise it because It's currently available.

00:26:34: Third and I also noted This down as Very important Is The quality Of the demand meaning Who was investing And Under what conditions?

00:26:41: If the external communication suggests a high valuation but economic reality of around is far more complicated than i become very cautious then it quickly becomes signal management.

00:26:54: And for me, financial engineering begins where the round primarily serves to produce a higher valuation rather than solve a real operational problem.

00:27:03: A strong company can raise money very quickly but a quick round does not automatically make the companies

00:27:08: strong.".

00:27:08: That's good concluding statement.

00:27:10: I basically see it exactly same way.

00:27:13: In the end valuations have to be justified through real development, through revenue and product progress or market position.

00:27:21: And not merely threw the next or a larger round.

00:27:24: I think that is very important conclusion.

00:27:26: all right let's come too this week.

00:27:28: listener question.

00:27:29: it comes from till and he asks I'll quickly read it out.

00:27:33: If models from Anthropic, OpenAI and others become increasingly powerful... ...and can more easily be applied to specific industries do specialized legal tech companies still even have a real chance?

00:27:48: Till!

00:27:48: I assume you either work as startup in this area or are generally interested in the topic.

00:27:54: Definitely a very interesting question.

00:27:56: The legal AI scene is currently heavily debating whether classic legal AI is already over again, Legora for example one of the most hyped European Legal Tech startups no longer speaks about legal AI but about agentic law meaning not just AI that makes lawyers more efficient But systems that takeover entire legal workflows research document review DDs meaning due diligence's playbooks precedence client history all orchestrated through various agents in operation.

00:28:26: At the same time, there is a big question – The Elephant In The Room!

00:28:30: If Anthropic or OpenAI are already building best foundation models anyway why do we still need specialized legal tech providers?

00:28:39: Won't they simply get overrun by the large LLM providers?

00:28:43: Guy, let's dive right into it.

00:28:45: How do you see this?

00:28:46: is legal tech as an independent category currently at risk because the big LLMs are moving ever deeper in to these lucrative verticals?

00:28:54: Or are we underestimating how much value truly lies in specialization?

00:28:59: For example, in security accuracy workflow integration or also customer proximity.

00:29:05: There are two levels here that We need to briefly look at In my opinion.

00:29:09: on the one hand there is naturally The model layer and Here specialized providers hardly have a chance of being faster or cheaper than Anthropic open AI or Google or other large generalist Model Providers.

00:29:23: These companies have the data centers, the talent ,the data pipelines and naturally also the corresponding capital base.

00:29:31: We discussed that in depth earlier.

00:29:33: but legal tech companies may not win on the pure model layer But rather on the application layer meaning The use case.

00:29:42: law firms do not simply buy a good model.

00:29:44: they by trust liability reduction, if that is possible.

00:29:48: And they want software integrated into existing workflows.

00:29:51: They want to map rights and role concepts and auditability as also a very important topic.

00:29:56: I noted down.

00:29:57: Document management is extremely important and the firm specific playbooks every law firm has.

00:30:04: If someone additionally understands how an M&A due diligence or litigation process actually works and can map through the use of AI then naturally becomes extremely exciting.

00:30:15: For law firms, it is also important that their data is not used for general model training and therefore flows into the General Knowledge Pool because that is essentially their core IP.

00:30:26: And therefore they also require on-prem solutions or attack resistant proprietary cloud layers where they can be sure we are working with our own data.

00:30:34: this is exclusive to our IP only.

00:30:37: work on That is the difference between Claude, which can analyze a contract very well and provide good feedback.

00:30:48: And in that second case I definitely see potential for legal AI companies.

00:30:56: Max would you therefore say this as classic question of distribution and lock-in?

00:31:02: Meaning, who sits closer to the customer and becomes part of the law firm's daily workflow?

00:31:06: Is it large LLM platforms or specialized legal tech providers after

00:31:12: all?".

00:31:12: I think that decisive question is... who controls the workflow.

00:31:17: So if Anthropic only provides the model, but Legora or Harvey are other legal tech providers we also have one-or two in Switzerland provide the interface, data rooms and playbooks can control approval processes.

00:31:33: then there is still a lot of room left for specialized providers.

00:31:36: But pressure is brutal.

00:31:38: so just in quotation marks We make chat GPT for lawyers.

00:31:42: that's definitely no longer enough.

00:31:44: I think these companies have to prove that they are more than a nice interface on top of the foundation model.

00:31:49: They have to go deep into the legal organization, almost like Palantir with the forward deployed engineers.

00:31:56: so you have to understand things onsite configure adapt and thereby become difficult.

00:32:06: Interesting question.

00:32:07: In our view, legal AI is definitely not dead yet but generic legal AI rappers probably really do belong to the past and have little chance of success.

00:32:16: The next phase belongs to companies that build real legal infrastructure out-of-AI secure precise embedded and close to the customer.

00:32:26: And that is exactly where it will ultimately be decided whether Legal Tech can differentiate itself from Anthropic so to speak or Whether It Will Be eaten by them.

00:32:35: So Let's move on to the transactions of the week.

00:32:38: Several transactions were communicated again last week and we have briefly prepared the most important ones for you, let's start right away in Zurich.

00:32:47: Mosaic a deep tech startup from the ETH Zurich environment has now closed a pre-seed round off three point eight million US dollars.

00:32:56: The Round was led by Founderful with participation from Kickfund.

00:33:06: Mosaic develops perception chips that are intended to enable devices to see and understand their environment in real time, And do so with very low energy consumption.

00:33:17: The core is process visual position data directly on a specialized chip instead of using very energy-hungry processors or GPUs for it.

00:33:27: This should allow devices to create local maps of their environment, recognize objects or remember where something was last seen for example.

00:33:37: Like the question that often comes up – Where did I put my mobile phone again?

00:33:41: Exactly!

00:33:42: Mosaic's direct customers are mainly ODMs meaning original design manufacturers that develop hardware for smart devices.

00:33:49: Applications such as smart glasses, wearables and other battery-powered consumer devices are particularly exciting where form factor and energy consumption are extremely critical.

00:33:59: In its first year Mosaic has already generated relevant revenues through NRE contracts with ODMs meaning through specific engineering customer projects.

00:34:09: What I find exciting is that Mosaic not simply selling a chip but wants to build complete spatial intelligence layer for device manufacturers.

00:34:18: The chip comes with an application layer that Mosaic develops and maintains itself so that ODMs do not have to build everything from scratch.

00:34:27: That addresses a real bottleneck, many devices could benefit from spatial intelligence today but until now power size and integration effort were simply too high.

00:34:38: With the capital they want to advance chip development flowing into product maturity and into initial commercial integrations.

00:34:45: Strategically, the goal is to move from these initial NRE revenues that we mentioned to scalable product revenues through chip

00:34:52: sales.".

00:34:54: If Mosaic manages this transition then The Company could become quite an exciting enabler for next generation of smart glasses and spatial computing devices.

00:35:03: Good!

00:35:07: Health AI space.

00:35:09: Moonlight AI has closed a seed round of US USD, the Round was co-led by Lotus One Investment from Singapore, VP Venture Partners from Switzerland and Medin Fund from Tunisia with participation from NV Capital & The Existing Investor CHI Ventures.

00:35:27: In terms of content this is an early but very focused AI diagnostics case for hematology and pathology.

00:35:34: I

00:35:34: find what Moonlight is developing here very exciting.

00:35:37: They are developing image analysis software for clinical diagnostics, the platform uses computer vision to detect indications of genomic biomarkers and complex disease signatures from routine blood and cytology smears.

00:35:51: The big point is that instead always waiting for expensive slow next-gen sequencing processes laboratories should be able gain usable diagnostic insights faster than images they already use anyway.

00:36:04: Who are the target customers?

00:36:06: These are mainly clinical laboratories, hematologists and pathologists who want to make cancer diagnostics faster, and more scalable.

00:36:15: Moonlight is working with an international consortium of clinical partners to build a proprietary data library.

00:36:21: This database is intended to link whole slide imaging of cytopathology samples With high quality genomic data And thereby create the foundation for robust models in real laboratory environments.

00:36:34: They position themselves between AI diagnostics and precision oncology.

00:36:38: That's also interesting positioning.

00:36:40: Many oncology workflows today depend on expensive NGS analyses with longer turnaround times and Moonlight.

00:36:47: AI is trying to bypass this bottleneck by translating existing standard images into diagnostically usable signals.

00:36:55: That's attractive because the solution does not require completely new hardware, can therefore potentially be integrated faster in laboratory processes.

00:37:05: How will they use money?

00:37:07: mainly for expanding data library?

00:37:10: Then team growth is a topic and also the further development of diagnostic solutions.

00:37:15: In addition, the financing is intended to accelerate the path toward commercialization and regulatory

00:37:21: approval.".

00:37:22: Let's go to Lausanne for the next transaction... And this one has an exit near lab.

00:37:27: A spin-off from The University Of Lausann founded in twenty twenty one Has now been acquired by US company nine oh eight devices.

00:37:36: For once purchase price was communicated and it is USUSD USD.

00:37:40: USUSUSD AUD USD, USUSSUSD UPDATED AUD, USUUSUSUSS UPDATE AUD AUDE, USSUSUSSD AUD UD, UDUSUSSSUSSD UPDATTATED UPDATABLE AUD.

00:37:49: Whether that's a lot or little we cannot yet say.

00:37:53: We may have to go in medias risk.

00:37:56: It does not look like very much money right now But maybe they raised almost no money.

00:38:02: Then again would be success.

00:38:05: What does NIRLAB do?

00:38:07: They develop handheld near-infrared spectroscopy devices for chemical analyses in the field.

00:38:13: Through a mobile app, The device can apparently identify substances within seconds including more than drugs such as cocaine even through thin plastic bags or even through glass I was told In addition to platform and also determine the purity of complex mixtures Such is with THC are also analyze CBD proportions.

00:38:35: The

00:38:35: most important customers are law enforcement organizations, as one can imagine.

00:38:40: So the police customs and other authorities that have to and want to identify substances directly in the field quickly and safely.

00:38:46: according to the company uh...the technology has already been used in more than one million field analysis.

00:38:53: whether that is a lot or little you can ask yourself when you look at how many people pass through an airport.

00:38:59: But in any case, it shows that NeerLab is not simply a laboratory innovation but has already achieved practical use in day-to-day operations.

00:39:08: And the strategic fit with nine oh eight devices is obvious.

00:39:12: The US company specializes in handheld chemical analysis and brings a global commercial infrastructure as well as complementary product portfolio.

00:39:21: for the American Company near lab expands the offering in the area of rapid onsite screenings.

00:39:27: In turn, the deal means access to a larger sales channel and an established platform in the law enforcement market.

00:39:51: For the Swiss ecosystem, this is another deep tech exit.

00:39:55: Unfortunately not a unicorn outcome but at least a clear industrial M&A deal with an international

00:40:02: buyer."

00:40:03: Good!

00:40:04: As of last transaction we are also including the exit of Curly in the program.

00:40:10: Curly is known for high-quality dog harnesses and dog accessories.

00:40:14: The company was founded sixteen years ago by Mark Zimmerman, Roland Primus in Haerleberg near Zürich & has now been acquired by the Swedish outdoor group Thule.

00:40:25: The purchase price is initially ten point one million Swiss francs.

00:40:29: In addition up to six point eight million swiss franc can be added as an earn out depending on future financial figures.

00:40:37: Curly develops and sells particularly lightweight, comfortable and easy to use dog harnesses.

00:40:43: So that means harness systems that are strapped around the dogs chest and back instead of simply using a collar.

00:40:48: The founders originally come from mountaineering and transferred their experience with harnesses to dog products.

00:40:54: Curly is particularly strong in the premium segment for vest style harnesses especially small dogs.

00:41:00: Curly sells through retailers in about sixty countries so six zero.

00:41:06: That is quite a lot with the focus on Europe and North America.

00:41:09: Last year, it generated revenue of a good six million Swiss francs with a strong EBIT margin of twenty percent.

00:41:18: that shows Curly as no longer a classic startup but a profitable niche company within international distribution.

00:41:25: if we take the numbers what is quite interesting It corresponds to roughly seven times EBIT from twenty-twenty five and if the maximum earn out is achieved, The multiple according to the press release based on eBit in twenty-Twenty Seven should also be at around seven.

00:41:44: X. Curly fits well into Thule's portfolio because dog transport products are one of groups fastest growing categories.

00:41:51: The founders are expected continue holding their roles within the group.

00:41:55: This case is also not a classic VC exit, but clean strategic M&A deal of profitable niche player.