Principal
Big Pi VenturesCheck size: €500K-€3M initial investments for Melina's early-stage work; Big Pi's wider family-of-funds range extends to €30M.
Melina invests in early-stage AI, robotics, B2B SaaS, life sciences, and climate technology. Her engineering and deep-learning background supports technical diligence, while her strategy-and-operations experience informs evaluation of commercial paths, deal structure, and the practical support a technical founding team needs after investment.
Technically ambitious founders and natural problem-solvers who can explain how a breakthrough becomes a useful marketable product, pair product innovation with business-development capability, and pursue a sufficiently large international market.
No clear pass criteria are available yet. Treat this as unknown until Kit finds direct evidence.
Explain the core technical breakthrough in enough depth for diligence, then connect it to a specific customer problem, a large international market, and a realistic commercialization plan. Cover team composition, defensibility, technical milestones, initial go-to-market evidence, and the exact operating or strategic help needed after the round.
Evaluate the technical advance and its defensibility together with the customer problem, market size, team coverage, deal structure, and path from prototype to a scalable commercial product.
For embodied or robotic AI, prioritize direct evidence from deployed systems and the builders operating them: what works, what fails, and what technical bottleneck must be cleared next.
No writing has been linked yet. Kit can search for posts, interviews, and fund essays worth reading before outreach.
Quote coverage is incomplete. Kit can look for direct comments on markets, founders, and investment criteria.
Before joining Big Pi, Melina spent roughly two years as a management consultant at McKinsey & Company, working on strategy and operations across energy, banking, insurance, and telecommunications. She holds an integrated master's in electrical and computer engineering from the National Technical University of Athens; her thesis applied deep learning to business-process prediction.