Presenting COREangels Big Data & AI Europe at ETH Zürich: Investing in the Future of Intelligence
Quick Answer
COREangels Big Data & AI Europe presented at ETH Zürich Student Project House, showcasing AI and data startups driving innovation across Switzerland and Europe.
ETH Zürich holds a rare distinction in global education: ranked #7 worldwide in the QS World University Rankings 2026. That standing reflects decades of scientific leadership and a culture that turns research into real-world impact. It is precisely the kind of environment where conversations about early-stage technology investment carry genuine weight.
The Scalemetrics team attended as part of a presentation of COREangels Big Data & AI Europe at the ETH Student Project House – a venue known for bridging student ambition with entrepreneurial momentum. Dr. David Griesbach and Samira Courti led the session, walking the room through the fund's thesis, its community of business angels, and the portfolio companies already putting that thesis into practice.
Investing in the Future of Big Data and AI
Data and intelligent automation are no longer peripheral to business strategy. They have become its foundation. COREangels Big Data & AI Europe was built on that conviction: that the companies shaping how organisations understand, move, and act on data will define the next generation of European enterprise.
The fund backs early-stage ventures working across four areas:
- Machine Learning & Artificial Intelligence
- Big Data Analytics
- Automation & Predictive Systems
- Enterprise SaaS powered by AI
Capital alone is rarely what determines whether a young company scales. So the network around COREangels brings together business angels, investors, and operators who sit alongside founders – contributing domain knowledge, customer introductions, and hands-on mentorship from prototype stage through to sustainable growth.
Our Portfolio: Building the Future of AI in Europe
The current portfolio reflects a deliberate range of AI and data applications. Each company is solving a real problem at meaningful scale:
- Caplena – AI-driven text analysis for better customer insights.
- NumberEight – Contextual intelligence enabling smarter mobile experiences.
- Tripartie AI – Trust and safety for digital marketplaces.
- haddock (YC W22) – AI-based financial insights for smarter businesses.
- Tilores – Scalable identity resolution and entity matching platform.
- Scandens – AI-powered predictive solutions for business optimisation.
- Horizon – Accelerating research through data-driven insights.
- Jrny – Intelligent automation improving customer experience journeys.
What connects them is not a single vertical but a shared commitment to building technology that compounds over time. Each creates defensible value through its data, its models, or the network effects it generates. That is the kind of scalable, AI-powered approach that transforms industries rather than merely automating them.
ETH Zürich: Where Innovation Meets Opportunity
The ETH Student Project House occupies a specific role in Switzerland's technology ecosystem. It functions as a launchpad for student-led ventures and a meeting point for entrepreneurial collaboration – not just within ETH, but between academia and the broader investment community.
Events held there create a bridge that is hard to replicate elsewhere. Academic research meets venture thinking. Students with technical depth meet investors who understand commercialisation. The result is a room where an early conversation can move quickly toward something concrete. Our team is grateful to Mattis Stolze and the ETH Student Project House team for making the session possible and for the quality of engagement it produced.
Looking Ahead: Innovation Needs Community
Good ideas rarely succeed alone. COREangels Big Data & AI Europe operates on that understanding: innovation needs a surrounding structure of trust, shared expertise, and sustained collaboration to reach its potential.
The goal is a network where founders and investors develop together – drawing on collective experience, real data, and strategic perspective to drive change that matters beyond a single company's metrics.
If you are an AI or data-focused SME looking for early investment, or an angel investor motivated by shaping the direction of European AI, the conversation is worth having. Together, durable innovation becomes possible.
Related Resources
Scalemetrics helps Swiss SMEs act on decisions like this before market conditions shift. Our corporate tax and VAT compliance services and outsourced CFO team give finance directors the senior expertise to move first.
Frequently Asked Questions
What should Swiss SMEs know about investing in the Future of Big Data and AI?
Data and intelligent automation are reshaping the foundation of business, research, and everyday life. COREangels Big Data & AI Europe backs early-stage companies in machine learning, big data analytics, automation, and enterprise AI – sectors where the next wave of Swiss and European growth is already forming.
What should Swiss SMEs know about our Portfolio: Building the Future of AI in Europe?
The current COREangels portfolio spans eight companies across AI text analysis, contextual mobile intelligence, digital marketplace safety, financial insights, identity resolution, predictive business optimisation, data-driven research, and customer experience automation – each built to generate compounding value at scale.
What should Swiss SMEs know about eTH Zürich: Where Innovation Meets Opportunity?
The ETH Student Project House serves as a launchpad for student-led ventures and a hub for entrepreneurial collaboration across Switzerland. It bridges academic research with venture-stage investment, giving founders and investors a shared space where early conversations can accelerate into concrete partnerships.
What should Swiss SMEs know about looking Ahead: Innovation Needs Community?
COREangels Big Data & AI Europe holds that innovation does not thrive in isolation – it requires communities built on trust, expertise, and sustained collaboration. The fund connects founders and investors who grow together, using shared experience and strategic insight to drive meaningful, lasting change.
What financial services does Scalemetrics provide for Swiss SMEs?
The Scalemetrics team provides Swiss SME owners and CFOs with practical financial expertise: from accounting and tax compliance to financial planning, KPI monitoring, and on-demand CFO services – giving growing businesses access to senior financial leadership without a full-time hire.
What financial infrastructure do Swiss SMEs need to operate compliantly?
Swiss SMEs need OR-compliant accrual-basis bookkeeping, quarterly MWST filings with the ESTV, monthly AHV/IV/EO payroll contributions to the cantonal SVA, BVG occupational pension administration, UVG accident insurance, annual corporate tax returns, and management reporting. A fractional CFO covers this entire compliance stack.
How much does outsourced CFO services cost in Switzerland?
Outsourced CFO services in Switzerland cost CHF 3,000-12,000 per month depending on scope and company complexity. This covers the full finance function: bookkeeping, payroll, MWST, budgeting, financial modelling, and reporting. Compared to a full-time CFO at CHF 216,000-350,000 annually including social costs, the outsourced model saves CHF 100,000-200,000+ per year.
Sources & References
COREangels Big Data and AI Europe: What Swiss SMEs Can Learn from Deep-Tech Investing
The presentation of COREangels Big Data and AI Europe at ETH Zürich signals something important about the direction of Swiss investment thinking: the intersection of artificial intelligence, big data infrastructure, and commercial application is attracting institutional-quality angel investment at the earliest stages of company formation. For Swiss SMEs operating in or adjacent to these technology domains, understanding what this investor network is looking for — and what financial signals it uses to evaluate opportunities — provides a direct window into how to position for growth capital in one of Switzerland's most active investment sectors.
ETH Zürich's role as a venue for this kind of investor presentation is not accidental. Switzerland's technical universities — ETH Zürich and EPFL Lausanne — are producing a steady stream of deep-tech companies with genuine technological differentiation, and the ETH ecosystem has developed a mature commercialisation infrastructure that includes investor networks, technology transfer offices, and accelerator programmes specifically designed to bridge the gap between research and revenue. Swiss SMEs emerging from this ecosystem carry a credibility advantage with institutional investors that is worth protecting through excellent financial management — an investor who has evaluated the technical credibility of an ETH spin-off and found it compelling will be more, not less, rigorous about the financial credibility.
The financial profile that AI and big data companies present to investors like COREangels has specific characteristics. Development-phase investment is high relative to early revenue: the cost of building proprietary AI infrastructure, training data acquisition, and model development precedes commercial deployment by months or years. This means the financial model must be especially clear about the path from current burn to commercial break-even, the specific milestones that will demonstrate progress to the investment committee, and the conditions under which additional capital would be required before profitability is achieved. Swiss social charge obligations — AHV, BVG, UVG — on the highly paid technical talent that AI companies require make the fully-loaded cost of a Swiss AI team materially higher than in comparable EU markets, and this must be accurately reflected in the financial model.
Investing in the Future: Financial Lessons for Swiss AI and Data SMEs
Swiss SMEs building AI and big data products face a specific financial challenge: the product development cycle is long, the technical team is expensive, and the path from prototype to revenue-generating product involves a sequence of milestones that each require sustained investment. Managing this financial reality requires three specific disciplines that go beyond standard SME financial management.
First, R&D cost tracking that meets Swiss OR standards: Swiss accounting for research and development costs has specific rules about capitalisation versus expensing, and getting this wrong creates both compliance risk and investor credibility risk. An AI company that has capitalised development costs that should have been expensed presents a balance sheet that overstates assets and a P&L that understates current-period losses — a combination that sophisticated investors will identify and flag immediately. Second, milestone-based cash flow modelling: the cash deployment in an AI development company is not linear. Large investments cluster around specific technical milestones — model training runs, infrastructure build-outs, pilot deployment costs — and the cash flow model must reflect this non-linearity. Third, technical team total cost modelling: the fully-loaded cost of a senior Swiss AI engineer — salary of CHF 120,000–180,000 plus AHV (5.3%), BVG (age-dependent, typically 10–14% for this salary level), and other social charges — is CHF 140,000–215,000 per year. A five-person technical team is therefore a CHF 700,000–1,000,000 annual commitment, not the CHF 600,000–900,000 that gross salary suggests.
Swiss Deep-Tech Investment Readiness: Financial Checklist
| Readiness Factor | Not Ready | Investment-Ready |
|---|---|---|
| R&D Cost Accounting | Capitalisation policy unclear | OR-compliant, documented policy |
| Technical Team Cost | Gross salary only in model | Total employer cost including all Swiss charges |
| Milestone Cash Model | Linear monthly burn | Milestone-linked non-linear deployment |
| Path to Break-Even | Narrative only | Modelled, with conditions and timeline |
| IP / Asset Documentation | Informal | Registered, valued, documented in data room |
Swiss deep-tech and AI companies have a genuine opportunity to attract institutional investment — but only if the financial preparation meets the standard that investors like COREangels require. Our investor readiness service builds the financial infrastructure that converts technical credibility into investment credibility for Swiss technology companies.
Pascal Stämpfli leverages over a decade of expertise in corporate finance and venture capital to scale and optimize businesses. A CFA charterholder with a Master's in Economics from the University of St. Gallen, Pascal specializes in market & company assessments, strategy, and business value creation. Having assessed more than 1,000 companies for financial and strategic investors provides him with a sophisticated understanding of investor rationale and capital allocation. As the Managing Director of Scalemetrics and Managing Partner at COREangels Big Data & AI Europe, Pascal operates at the intersection of financial discipline and technological innovation.