Client context: Copenhagen-based early-stage technology fund investing globally, with a focus on underrepresented founders.
The situation
The fund's traditional networks and manual screening process limited its visibility across markets. It wanted to assess a broader opportunity set while understanding local business conditions and avoiding a single-market view of what a promising company should look like.
The work
Nexteam supported the fund with investment professionals combining VC experience, analytics and AI-assisted research. The work covered:
- Startup discovery and research across multiple languages and regions.
- Preliminary screening and market-specific evaluation frameworks.
- Local ecosystem mapping and cross-market research synthesis.
- Organised market intelligence for the investment team's review.
The team expanded research coverage across Asia, Africa, Latin America and Eastern Europe. Market context remained important when interpreting the research and comparing opportunities.
The results
The fund expanded global deal flow, identified opportunities outside its previous network and reduced screening time while increasing market coverage. The case also describes a better understanding of local market dynamics.
These outcomes are qualitative in the public summary. It does not provide a screening-time baseline, evidence of predictive accuracy or a comparison of investment returns.
What this case illustrates
Broader sourcing and faster preparation can improve the information available to an investment team. They do not make automated scoring a substitute for diligence or investment judgment.
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Related reading: Governing generative AI in finance.
Client identity is confidential. This is an anonymised engagement summary; results are specific to the work described.