Deep Tech Research
- First-time and unique data collection of deep tech ventures worldwide (data points: ventures, IP, founding team, financing history, partnerships)
- Scientific identification of deep tech ventures vs. “regular tech” ventures
- Patent portfolio & scientific publications of founding teams
- University and research-institute spin-outs
- Classification using scraped information on technology readiness / solution, scientific novelty, and IP intensity
- Creation of a harmonized, global dataset enabling longitudinal comparison
Our Study in a Nutschell
- Research Questions:
- Descriptive analyses of deep tech ecosystem:
- Mapping global deep-tech hotspots and their evolution over time
- Venture founding counts
- Strength of research institutions
- Density of corporate partners (by industry)
- Identification of industry and technology clusters (e.g., quantum, biotech, carbon capture…)
- Founding team characteristics
- Academic & industry backgrounds
- Multidisciplinary expertise and seniority
- Founding team size and complementarities
- Venture characteristics
- Business model archetypes
- Time to funding
- Capital intensity, regulatory exposure
- Identification of success factors:
- Patents and founding-team publication history
- Role of spin-outs from universities
- Founding-team composition (e.g., scientific/ industrial experience, disciplines, tenure)
- Corporate partnerships (e.g., development collaborations; corporate investments)
- Funding models / hybrid financing (e.g., grants, derisking in early stages, venture capital, corporate VC, infrastructure banks etc.)
- Examplary data sources leveraged:
Our partnership
The TUM-Team behind the Deep Tech Observatory
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