Infrastructure, Intelligence, Intention: Why Peter Lu’s Quiet AI Revolution Deserves Switzerland’s Attention

By Tallulah Patricia Bär

It was during a brief interlude at the inaugural Europe-Asia Economic Summit in Davos—a summit I’ve had the privilege of advising over the past eight months—that I found myself in conversation with Peter Lu. Not in a spotlighted keynote. Not over a planned briefing. But in that liminal space where ideas sometimes unfold more freely: the coffee break.

Europe Asia Economic Summit

The EAESummit, designed as a strategic bridge between regions, convened a focused circle of decision-makers committed to fostering durable cooperation between Europe and Asia. Among them was Peter Lu, Founder and CEO of Neurowatt—an AI foundry and software house headquartered in Singapore, with a research and development team based in Taipei.

Lu’s presence was understated, his pace calm—but his vision was anything but ordinary. What he is building spans not only traditional AI use cases, but a new category of cognitive AI-powered agents—systems designed to synthesize real-time global data, understand context, and execute action. Whether parsing 90,000 financial headlines a day or autonomously placing trades via his Finance AI engine, Lu’s architecture isn’t just reactive—it is structurally anticipatory. In parallel, his tools automate complex workflows across manufacturing, spatial design, and real estate, forming a modular stack that is already in use across Asia and now expanding to the U.S.

More About The Work

Lu leads a rapidly growing AI infrastructure company currently being incubated under NASDAQ’s global startup program—an elite cohort of twelve selected annually with an eye toward public listing. A former top trader on Binance, with an 83.5% win rate over consecutive years, Lu combines statistical precision with an engineer’s instinct for systems design.

His team is building AI agents capable of parsing over 90,000 news sources per day, restructuring content, and triggering automated trades based on real-time analysis. Beyond finance, his models underpin robotic arms for TSMC in Taiwan and automated logistics for a 24,000-location tea chain operating across China. In the real estate sector, his company has developed spatial AI tools that remove friction from transactions, replacing much of the traditional sales process with scan-based architecture and generative layout planning. These aren’t prototypes. They’re already in deployment!

Lu calls his framework a “dual engine of thought”—a technical evolution that allows AI not just to react to inputs, but to develop layered, cross-referenced understanding. He isn’t selling hype. He’s designing AI not as a product, but as infrastructure.

What It Signals

In a geopolitical moment defined by fragmented governance, regional data regimes, and shifting alliances, Lu’s model reflects a broader truth: the next phase of economic influence will be defined less by ideology, and more by infrastructure.

Who builds the systems? Who calibrates the intelligence? Who retains optionality?

Lu, who was educated in Toronto and MIT Sloan and raised in Taiwan, is positioned at precisely that edge. He’s neither constrained by a single political center nor beholden to any one investor base. In a multipolar AI economy, his neutrality may prove his greatest asset.

From a Swiss perspective, this moment is instructive.

Why Switzerland Should Pay Attention

Switzerland has long built quietly—precision instruments, financial stability, multilateral diplomacy. But in the emerging architecture of intelligence infrastructure, neutrality alone is not enough. What’s needed now is credible engagement.

And we are, by many measures, ready.

Switzerland’s latest policy developments, including its Risk-Based Approach to AI Regulation, emphasize proportionality, transparency, and innovation enablement over restriction.

Unlike the EU’s AI Act (comparison here), which skews toward bureaucratic overreach, Swiss policymakers are positioning the country as a platform—stable, principled, and agile. This is not just regulatory foresight. It’s geopolitical soft power, Swiss-style.

Institutions like the University of Zurich—with its RiskLab, AI and Finance Research Center, and growing endowment strategy—are already exploring applied partnerships. As part of my upcoming mandate in the Swiss academic philanthropy ecosystem, I see growing need and interest for AI as a strategic funding pillar: not just for scientific prestige, but for real-world transformation.

Lu’s work is not only technically relevant. It is philosophically aligned. Modular, decentralized, scalable—qualities that resonate in a country that values quality over volume, credibility over noise.

The Infrastructure Is Here

Spaces like Headquarter in Zurich—open, cross-disciplinary, and designed to host the kinds of ventures that blur the line between lab and firm—are uniquely positioned to welcome companies like Peter Lu’s. These are not coworking spaces in the traditional sense. They are civic engines for innovation and creativity: where policy meets product, where founders meet faculty, where east meets west and all in between.

Peter hasn't yet chosen a European base. But should he consider Switzerland, he will find not just regulatory clarity and technical talent—but a culture of institutional seriousness paired with international reach. From the University of Zurich to the Swiss Federal Institute of Technology (ETH), to multilateral investors between Zurich and Geneva, to fintech-forward cantons like Zug (more here), Switzerland offers a distributed but connected platform for applied AI leadership.

A Summit as Signal

That we met at EAES—a summit born from cross-continental trust—is itself significant. This gathering wasn’t a tech conference. It was a geopolitical design space. A place where infrastructure builders, capital allocators, regulators, and academics could reflect on what’s next. Not just what’s profitable.

Peter Lu wasn’t on stage that day—but his presence was already imprinted at the Summit. The day before, he had commanded the CEO Impact Circle, an intimate dialogue reserved for leaders shaping tomorrow’s economic architecture. He shared that space with Michael Lewrick, whose latest book AI and Innovation currently sits on my desk, ready to be marked up and dog-eared soon, and with Bettina Schaller, who leads one of the most ambitious and necessary mandates of our time: preparing the workforce not just for the future of Switzerland, but for the future of work itself—globally. It was a fitting trio. Infrastructure, imagination, and implementation in motion.. But his presence—and our conversation—reflected exactly what the summit was designed to create: unexpected encounters that point to long-term possibilities.

In Peter, I saw not just a founder. I saw a systems strategist. A builder of tools that may well define how we trade, plan, invest, and govern over the next decade.

We often talk about AI as a challenge to sovereignty, autonomy, or even humanity. But there is another lens: AI as infrastructure. And in Peter Lu’s case, AI as quietly precise, already functioning infrastructure—with the potential to power a new layer of intelligent systems across industries.

Switzerland has the trust, the terrain, and the talent.

And we are, in every sense of the word, ready.

Switzerland is Ready!