Partner at Big Pi Ventures
Check size: Firm-wide: Big Pi publishes equity tickets of €0.5M–€30M across its early-stage and growth funds. The current site does not publish Alex's personal range or the early-stage fund's narrower ticket policy, so the full platform range should not be read as his standard check.
Alex backs research- and engineering-led companies that start with a real problem, create defensible technical capability or intellectual property, and translate inventions into globally useful products. His GenAI analysis distinguishes durable innovation from undifferentiated model wrappers: proprietary data, deep domain knowledge, workflow integration, and a credible technical moat matter more than access to the same foundation models as everyone else.
Begin with the real customer or scientific problem and why current approaches fail. Explain the core invention, evidence it works, proprietary data or IP, comparison with alternatives, route from prototype to a reliable product, and how the technical lead compounds. Pair the technical founder with a credible commercialization plan, global market, customer validation, and a clear reason Greece or Southeast Europe strengthens talent or execution.
Scientists and engineers who can turn an invention or prototype into a useful marketable product, founders solving a real problem rather than starting from technology, well-rounded teams spanning product innovation and business development, and globally ambitious companies that can use Greece as a technical operating base.
His public framework implies caution toward technology in search of a problem, thin GenAI wrappers built on commodity models, businesses with no proprietary data or domain edge, local-only ambition, and research teams unable to articulate product transition, customer need, market scale, or defensibility.
Start with an important real-world problem, demonstrate a differentiated technical solution, protect or compound the edge through IP and data, then map the engineering milestones required to turn a prototype into a globally marketable product.
Separate commodity model capability from company-specific advantage by testing proprietary data, domain expertise, workflow ownership, product integration, evaluation evidence, distribution, and whether the moat strengthens as base models improve.
“You need to set off with the logical part first, to offer a technology that will be the solution to a real problem.”
— https://www.astralon.gr/alex-eleftheriadis-partner-at-big-pi-ventures-in-an-exclusive-interview/
Foundation models commoditize some capabilities, so durable GenAI startups need proprietary data, domain depth, workflow integration, or technical differentiation that survives model improvement.
A patent or advanced technology should begin with logic and a real problem, while globally oriented companies can use a meaningful technical presence in Greece as an execution advantage.
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