In 2025, Greece emerged as the fastest-growing startup market in Europe — not just within its own region, but across the continent as a whole. Total investment surpassed €732 million across more than 90 startups, a 35% increase on the previous year — in a year when several major European markets were contracting or stagnating. France saw an expected 11.7% drop in VC deal value, while Germany lost momentum in the second half of the year.

That headline figure deserves some unpacking, because the composition of the investment matters as much as the total.

While early-stage rounds made up 75% of all deals, they accounted for only €117.5 million of the total invested — with the remaining €614 million flowing to Series A and later rounds. The money is increasingly following proven traction rather than early promise, a pattern consistent with the broader European shift toward scale-up investment. The sectoral distribution reflects this maturity too: the most funded categories in 2024 and 2025 were artificial intelligence, biotechnology, and health technologies — sectors where Greece has been building technical depth for longer than the recent coverage suggests.

International confidence is no longer a matter of isolated bets. In 2024 alone, 156 international investors participated in Greek funding rounds, with 36% of them based in the United States — a structural pattern of commitment, not a one-off signal. Major names including Sequoia, Andreessen Horowitz, and Alibaba have each backed Greek-founded companies, a level of tier-1 engagement that would have been exceptional five years ago.

What explains the momentum? Several factors are converging. Over the past decade, Greece has built out 19 data centres — with more under construction — and now hosts more high-capacity submarine cables than anywhere else in Southeast Europe. This is infrastructure that attracts serious operators. At the same time, HDBI now supports 30 VC funds, with 16 actively deploying capital into startups — a structural deepening that would have been unrecognisable a decade ago.

There is also a less visible dynamic at play. Greece has long maintained a meaningful asymmetry between its high-quality tech talent and its relatively low cost of labour — and global companies are increasingly taking advantage of this gap. For the most part, however, this access has been informal: Greek engineers freelancing for foreign teams, contributing to products in which they hold no equity and no strategic stake. The smarter model — bringing international companies into Greece structurally, so that local builders participate in value creation rather than simply providing billable hours — remains underdeveloped. That gap is where real opportunity lies and we at Forthtech have been utilising this opportunity ever since our fund’s launch.

None of this means the work is done. Tech remains barely 1% of Greece’s GDP, while in Western economies the figure sits closer to 10%. Greece is still classified as a “Moderate Innovator” by the European Innovation Scoreboard.

But the trajectory is unambiguous. Greece is no longer building the conditions for a startup ecosystem — it is operating one. The question has shifted from whether international capital will take Greece seriously, to how local and European players position themselves within a market that is demonstrably going strong.

We were.

When Forthtech was formed, the thesis was straightforward, even if the timing felt uncomfortable: the Fourth Industrial Revolution was not a future event. It was already underway. Deep learning was moving from research labs into real enterprise problems. Machine learning was beginning to reshape how organisations managed risk, communicated, and made decisions. The infrastructure was not yet mature. The tooling was rough. The market was full of enthusiasm and short on follow-through.

That gap — between acknowledging a transformation and actually backing it — was where we chose to operate.

Between 2010 and 2025, AI startups evolved from peripheral innovation actors into the central focus of global venture capital, with funding growth exceeding 40% compound annual growth rate over fifteen years. What that trajectory obscures is how uneven the early years were. In 2020, the capital was not yet flowing at scale into applied AI — into the companies solving real problems in risk, in communications, in decision intelligence. Most of the enthusiasm was concentrated in a handful of frontier labs and headline use cases. The applied layer, where 4IR would actually be lived by businesses, remained underfunded and underestimated.

We built our portfolio in that space. Companies developing AI and deep learning solutions not as research projects, but as products with enterprise customers, measurable outcomes, and defensible positions. We looked for founders who understood that the value of machine intelligence was not in the model — it was in what the model enabled.

This is an era-defining shift, comparable in scale to the rise of the internet or mobile, creating the potential to build large-scale global companies from anywhere in the world — and the difference now is that adoption is faster, more pervasive, and increasingly grounded in real enterprise demand rather than pure speculation. That description is accurate today. In 2020, it was a bet.

We made it. We are not claiming perfect foresight. We are saying that the signals were there for those paying attention — and that conviction, without the cover of consensus, is what early-stage investment actually requires.

The 4IR is no longer a thesis. It is the operating environment. We invested before it became obvious. That is the only time it makes sense to invest.

In 2025, early-stage rounds — pre-seed and seed — made up 75% of all funding deals in Greece, yet captured only €117.5 million of the total invested. The remaining €614 million went to Series A and later. In other words, the base of the funnel is wide and active, but only a fraction of what enters it makes it through to the next stage. That gap is not unique to Greece, but here it is particularly consequential.

The bottleneck between seed and Series A is a pan-European problem that has been tightening for several years. Across Europe, the median time from seed to Series A now stretches to approximately 25 months — and for some sectors it exceeds 30. 2050 In Q1 2025, 46% of all seed financings were bridge rounds rather than priced rounds 2050 — a sign that founders are surviving the gap rather than closing it cleanly. Bridge rounds are not inherently bad, but they are a signal: the path from early traction to institutional conviction is longer, harder, and more expensive than it was three years ago.

The bar at Series A has also moved. Investors now expect not just product-market fit, but demonstrable unit economics and scaling capacity — and round sizes have risen to match, with many founders finding themselves priced out of conversations they would have had more easily in 2021. For Greek founders specifically, the average seed round for startups operating in Greece in 2024 was $2.1 million — less than half the $5.1 million average for Greek-founded startups operating abroad, a gap that reflects both the cost structure advantage and the relative scarcity of large local tickets.

None of this is insurmountable, but it requires founders to rethink the timeline. Treating the pre-seed or seed round as a design partner programme rather than a capital event is becoming the more pragmatic posture — with longer runways, leaner teams, and capital efficiency built into the story from day one.

The infrastructure to support this is improving. HDBI, EIT Digital, and a growing network of Greek VC funds are increasingly focused on connecting early-stage founders with the mentoring, investor networks, and follow-on capital they need to navigate the funnel — not just to get in, but to get through. New vehicles like Big Pi Ventures’ €200 million growth fund, targeting tickets of €7 to €20 million, are specifically designed to address the growth-stage gap that has historically forced Greek founders to look abroad for their next round.

The honest message for founders is this: the funnel is narrow, but it is not closed. The startups that reach Series A in this environment are not necessarily the ones with the best ideas — they are the ones that managed their runway, hit the right proof points, and understood what institutional investors actually need to see before they move. That knowledge is now more available than it has ever been. The gap between early promise and scalable business is closeable. It just takes longer than the headlines suggest.

Most of what enterprises deployed between 2022 and 2024 was the former — tools that answer questions, generate content, summarise documents. Useful, but fundamentally reactive. Agentic AI is something structurally different: systems that plan, reason, and execute multi-step tasks autonomously, without continuous human instruction at each step.

That distinction matters enormously for anyone building or investing in B2B technology right now.

The adoption numbers are striking in their speed. According to Gartner, fewer than 5% of enterprise applications embedded agent capabilities in 2025. By the end of 2026, that figure is projected to reach 40% — one of the steepest adoption curves in enterprise software history. KPMG’s AI Quarterly Pulse Survey tracked agent deployment surging from 11% of organisations in Q1 2025 to 42% by Q3 — a nearly fourfold jump in under six months. These are not pilot numbers. These are production deployments.

On the investment side, the trajectory is equally clear. Agentic AI startups raised approximately $1.3 billion in 2023, $3.8 billion in 2024, and an estimated $6.5–7 billion across 2025 — roughly doubling year on year. The capital is not flowing toward LLM infrastructure. It is flowing toward companies that have built actual products on top of it — vertical solutions with real enterprise customers and measurable outcomes.

That last point is where the investment thesis gets specific. The market is not rewarding builders who can demonstrate a capable model demo. The hard part was never the model — system complexity has become the primary deployment bottleneck, with multi-agent orchestration, reliability, and traceability now surpassing all other challenges as organisations move from prototypes to production. The companies that will capture durable value are those that have solved the integration and governance layer, not just the intelligence layer.

For B2B founders, this creates a clearer brief than the generative AI wave did. The question is not “how do we add AI to our product?” It is: which workflows in our domain involve multi-step decision-making that currently requires constant human oversight — and what would it take to make those autonomous? Risk assessment, compliance monitoring, communications orchestration, customer workflow management: these are the categories where agentic architectures are already delivering returns above cost of capital, and where defensible positions can be built.

Gartner’s longer-term projection suggests agentic AI could generate close to 30% of enterprise application software revenue by 2035, surpassing $450 billion. That is a large number. More relevant for builders today is the near-term window: the companies that move from prototype to production in the next 18 months will be setting the category defaults that later entrants will have to displace.

At Forthtech, this is not an abstract observation. Our portfolio’s focus on AI and deep learning applications means we have been watching the applied layer of this space closely — and the shift from generative to agentic is the most consequential change we have seen since we began investing. The builders who understand what agentic really means, beyond the terminology, are the ones worth backing. And we are proud to say that we are working with visionary founders in that premise.

Supply chains are where the shift became impossible to ignore first. The disruptions of the early 2020s — pandemic-driven shortages, Red Sea rerouting, tariff shocks — exposed something fundamental: global supply networks had been optimised for efficiency at the expense of resilience, and the tools organisations used to manage them were almost entirely retrospective. They could tell you what had gone wrong. They could not tell you what was about to.

AI-powered control towers are now integrating procurement, manufacturing, and logistics data — using machine learning algorithms to ingest external signals including weather patterns, port congestion, and social media sentiment to predict disruptions before they materialise physically. The shift from reactive to predictive is not incremental. It represents a different category of capability entirely, and enterprises that have made the transition are operating with a structural advantage over those still running quarterly risk reviews.

Geopolitics has added urgency. Geopolitical risks are elevated as 2026 gets underway, with accelerating fragmentation and shifts in major economic relationships exposing new fractures across global business. The World Economic Forum’s Global Risks Report characterises 2025–2026 as a period of unprecedented risk interconnections, with state-based conflict, geo-economic confrontation and cyber threats ranking among the primary immediate concerns for organisations globally. For risk management technology, this is not headwind — it is the demand signal that has been building for years.

The financial dimension compounds this. European businesses in particular operate in an environment shaped by geopolitical tensions, supply chain disruptions, and financial market volatility — interconnected pressures that are compelling organisations to adopt advanced risk management solutions at an accelerating pace. The global risk management software market was valued at $12.3 billion in 2020 and is projected to reach $21.2 billion by 2026 — growth that reflects genuine enterprise need rather than speculative adoption.

The technology gap that existed five years ago — when the need was clear but the tooling was not — is closing. AI-driven scenario analysis, automated risk reporting and integration of risk signals across previously siloed systems are moving from experimentation to operational deployment. The constraint today is less about what the technology can do and more about organisational readiness: data governance, integration architecture and the willingness to treat risk management as a strategic capability rather than an administrative one.

That transition is the real investment story. The organisations that move from periodic, fragmented risk processes to continuous, connected intelligence will not only be better protected — they will make faster, more confident decisions across every function that touches risk. In an environment where volatility is structural rather than cyclical, that is a material competitive advantage.

At Forthtech, risk management technology has been a core portfolio vertical from the outset — not because the market was easy, but because the need was undeniable. The companies building in this space have found that the world has moved decisively in their direction.

As part of our investment strategy, a good number of the companies we have backed were largely built outside Greece. Many have a Greek co-founder or a founding team with roots here; some do not. What they share is a decision, supported by our investment, to open a base in Greece — as a European operating hub, as a development centre or as their primary entry point into the EU market. That model is less common than it should be. It is also, in our experience, more effective than it looks.

Greece’s case as a location for international tech companies rests on several converging advantages. Advantageous labour costs, steady employment growth, an increasingly skilled young workforce and strong availability of multilingual professionals create favourable conditions for international companies seeking efficiency, scalability and stability. Operating costs run approximately 40% lower than in traditional Western European tech hubs, which for an early-stage company translates directly into extended runway and faster iteration cycles. For a company already operating in a high-cost market establishing a Greek hub is not a compromise. It is a deliberate structural choice.

The talent pool is the less visible part of the equation. Greek engineers and product builders are technically strong, multilingual by default and accustomed to working across cultural contexts. Crucially, they are oriented outward: 81% of Greek firms engage in international trade — significantly above the EU average — a figure that reflects not only business activity, but a fundamental professional mindset. For a company building B2B products for European enterprise customers, a Greek team is already calibrated for the market it needs to serve.

What this model produces — and what we believe matters beyond the individual companies — is a form of value creation that strengthens the Greek tech ecosystem from the demand side rather than the supply side alone. When an international company opens its European hub in Athens, it is not only about creating jobs. It is bringing foreign capital and management practices into the local market, connecting Greek talent to international product development cycles and contributing to a research and development base that builds lasting technical capacity in the country. Greece now hosts 19 data centres — with more under construction — and more high-capacity submarine cables than anywhere else in Southeast Europe: infrastructure built in part because companies found reasons to be here.

The blind spots are real and worth naming. Perception lag exists: building from Athens still requires more explanation than building from Berlin or Amsterdam in some enterprise sales contexts and companies need to make deliberate choices about where to stage their customer-facing presence. The operational complexity of scaling across European markets — over 100 VAT regimes, non-harmonised product standards and fragmented compliance requirements — does not disappear simply because a company has a Greek base. These are solvable problems, but founders who underestimate them lose time they cannot recover.

The broader point, though, is this: Greece’s role in the European tech landscape is not limited to producing companies that scale outward. It is also becoming a place where companies built elsewhere choose to scale inward — establishing the European presence they need, with the talent and cost structure that makes that presence sustainable.

That is the model Forthtech has backed. And it is, we believe, a meaningful contribution to the economic fabric of a country that has earned a more prominent place in Europe’s technology story than it is usually given credit for.