Cargofy Raises €9.5M to Deploy AI Digital Workers

Cargofy Lands €9.5 Million Series A to Put AI Digital Workers at the Heart of Global Freight

There is a quiet but accelerating revolution happening inside freight operations across Europe and North America, and it does not look like what most people imagine when they hear the word "automation." It does not involve robots on warehouse floors or self-driving trucks on motorways. Instead, it is happening in inboxes, dispatch systems, compliance queues, and back-office workflows — and an AI-native logistics company called Cargofy is at the centre of it. The company has just closed a Series A funding round worth €9.5 million, a milestone that marks not just a financial vote of confidence but a broader signal that the freight industry is genuinely ready to embrace AI-powered digital labour at scale.

The round, which totals €9.6 million (approximately $11 million), is structured as a combination of €5.2 million in primary capital and €4.3 million in secondary transactions. It was led by u.ventures, Toloka, and Movens Capital, with notable angel participation from Des Traynor, the co-founder of customer messaging platform Intercom. The involvement of an investor from Poland also proved to be more than financial — their local market connections helped Cargofy secure several enterprise clients in the country before the round had even formally closed. Perhaps the most telling detail, however, is what happened to one of Cargofy's earliest backers: they fully exited via the secondary market, walking away with more than fifty times their initial investment. In the current investment climate, that kind of early-backer return is not something you see often, and it says a great deal about how much conviction has built around this company since its earliest days.

At The AI World, we have been closely following how artificial intelligence is reshaping industries that have traditionally been slow to modernise. Logistics and freight, for all their complexity and global scale, have been surprisingly underserved by genuinely transformative AI solutions. Cargofy is one of the companies trying to change that — not by bolting AI onto existing tools, but by building what it calls AI infrastructure that companies can use to hire digital employees.

Redefining What It Means to Automate Freight Operations

Founded by Stakh Vozniak, Alex Kovalchuk, and Dimitri Alexiou, Cargofy operates with a fundamentally different philosophy from most logistics technology companies. Where others have focused on building dashboards, visibility platforms, or route optimisation engines, Cargofy's core product is the digital worker — an AI agent that mirrors the actual day-to-day workflow of a human freight employee. The company's platform does not ask logistics firms to rip out their existing technology stacks and start from scratch. Instead, it integrates with over seventy tools that freight companies already rely on, including Transportation Management Systems (TMS), Enterprise Resource Planning software (ERP), load boards, carrier compliance platforms, and the full range of communication channels that operations teams use every day.

What this means in practice is that a Cargofy digital worker can do much of what a dispatcher, coordinator, or back-office administrator does — handling carrier communications over email, chasing documents, sending follow-up messages, managing dispatch flows, and doing all of this around the clock, in multiple languages, across different markets. The system does not require the company to retrain its staff or overhaul its processes. It simply adds an AI layer that absorbs the high-volume, time-sensitive, repetitive work that typically eats up a logistics team's day. Stakh Vozniak, the company's CEO and founder, has been refreshingly direct about what Cargofy is actually building: "We're not building logistics software — we're building AI infrastructure where companies can hire digital employees for their operations. One person can now do the work of ten, and revenue per employee grows. That's how we see the future of this industry."

That framing matters, because it positions Cargofy not as a software vendor but as a workforce infrastructure provider — a subtle but important distinction that changes how logistics firms think about procurement, integration, and long-term dependency. When you buy software, you are buying a tool. When you hire a digital employee, you are adding capacity. Cargofy is betting that the latter framing will resonate far more deeply with freight operators who are perpetually under pressure to handle more volume with the same — or shrinking — headcount.

The Investment Case: Deep Domain Data and a Proven Edge

One of the most important things that sets Cargofy apart from the wave of AI startups that have targeted the logistics sector in the past two or three years is timing and data. The company started earlier than most of its competitors, and it did not begin life as a technology company attempting to understand freight from the outside. Instead, the founding team spent years embedded inside freight operations, learning the nuances of how shippers, carriers, and third-party logistics providers actually work — the informal processes, the edge cases, the industry-specific language, the compliance quirks that vary by region. The result of that period of immersion is a proprietary dataset measured in terabytes, accumulated over years of real operational work. When Cargofy pivoted in 2023 to building AI agents trained specifically on that data, it was not starting from zero. It was applying machine learning to a corpus of domain knowledge that most competitors simply do not have access to.

This is exactly the point that Bogdan Svyrydov, Principal at Horizon Capital and Venture Director at u.ventures, highlighted when explaining the investment rationale: "Their key advantage is the combination of strong AI expertise with a deep understanding of the needs and processes of shippers, carriers, and 3PL providers. This is what enables them to offer the most effective AI products in this market, while most other AI startups build universal solutions without accounting for the important nuances of the logistics industry." The phrase "universal solutions without accounting for nuances" is a pointed one, and it accurately describes a common failure mode in enterprise AI adoption. Generic AI tools applied to specialised industries often produce generic results. Cargofy's thesis is that freight-specific AI, trained on freight-specific data, by people who have worked inside freight operations, will consistently outperform anything built to a broader specification.

The company currently serves clients including SuuS, Nova Group, Zammler, Metinvest, and Vista, spanning shippers, carriers, and third-party logistics providers across the full freight chain. Its operations cover Europe, the United States, and the Caspian region — a geographic footprint that reflects both the ambition of the founding team and the genuinely global nature of freight itself.

Numbers That Make the Business Case Impossible to Ignore

Technology companies in the AI space often struggle to demonstrate concrete, verifiable return on investment for their enterprise customers. The numbers can be impressive in demos and pilot programmes, but they tend to get blurry by the time they reach the boardroom. Cargofy has been unusually transparent about the outcomes its clients are seeing, and the figures it has shared are striking enough to deserve careful attention.

Under the Cargofy platform, one dispatcher has been able to manage a fleet that is ten times larger than what a single dispatcher could typically handle. Think about what that means operationally: a logistics company could theoretically serve a dramatically larger client base without proportionally scaling its headcount, fundamentally altering its cost structure and margin profile. A fleet of 315 trucks using Cargofy's digital workers is saving approximately €72,400 — around $83,000 — every month. On an annualised basis, that is nearly €870,000 in operational savings from a single deployment. One of the company's US-based clients has gone further still, cutting annual logistics costs by more than €4.3 million, which is roughly $5 million. These are not incremental efficiency improvements. These are the kinds of cost reductions that change how a company thinks about its competitive position in the market.

The early backer exit story reinforces this picture from a different angle. Achieving over fifty times return on an early-stage investment is extremely rare, even in the venture capital world. It only happens when a company has demonstrated something genuinely valuable — not just a clever product, but a product that is solving a real and urgent problem at a scale that justifies significant market valuation. The fact that the secondary transaction happened in the context of a Series A, rather than a later-stage liquidity event, suggests that confidence in Cargofy's trajectory is high and that demand from new investors was strong enough to accommodate a full exit for the original backer.

Global Expansion and the Road Ahead for AI-Driven Logistics

The €9.5 million raised in this Series A is earmarked across three areas, each of which reflects a different dimension of Cargofy's growth strategy, and together they paint a picture of a company that has thought carefully about how to scale without losing the operational depth that has been its competitive advantage so far.

The first priority is expanding what the company calls local pods — dedicated regional teams that combine market knowledge with product expertise. New pods are planned for Germany, the Netherlands, France, and Spain within Europe, and in the United States the company intends to push into the Midwest, East Coast, and West Coast regions. This geographic expansion is not just about sales coverage. It reflects the understanding that freight operations are deeply local, shaped by regional regulation, carrier networks, language, and commercial practice. A German logistics company has different operational realities than a US-based third-party provider, and Cargofy's local pod model is designed to ensure that its AI agents are calibrated for those differences.

The second major investment area is team expansion, with a particular focus on diversifying the company's workforce. Currently, around ten percent of Cargofy's employees are from outside Ukraine. The company has set a target of reaching forty percent international composition, which will be important both for the cultural alignment needed to serve clients in multiple markets and for the language and regulatory expertise that underpins the multilingual, multi-market capability of the AI platform itself.

The third area is arguably the most consequential for the long-term product roadmap: deepening AI agent capabilities. Right now, Cargofy's agents primarily handle front-office tasks — client communication, order intake, carrier messaging, and document management. The R&D investment from this round will be directed at expanding those capabilities into comprehensive back-office workflows, including billing, compliance management, and end-to-end carrier coordination. This is where the real complexity in freight operations lives, and cracking it would significantly extend Cargofy's value proposition well beyond what most competitors have managed to automate.

What is particularly interesting is the organic international demand the company is already seeing. Despite having done no formal marketing in Latin America or the Middle East, Cargofy reports inbound interest from Brazil, Mexico, and the Gulf region. That kind of pull — where customers are reaching out before a company has even launched locally — is a strong signal that the problem Cargofy is solving is genuinely global, not just a European or North American phenomenon. The company plans to enter those markets as part of its next phase of expansion, which suggests the Series A may not be the last fundraising headline we see from this team.

What Cargofy's Rise Tells Us About AI's Expanding Role in Global Supply Chains

Zooming out from Cargofy's specific story, this funding round is part of a broader pattern that The AI World has been tracking closely: the emergence of vertical AI companies that are winning not because they have the most powerful foundation models, but because they have the deepest domain expertise and the most relevant training data. The freight and logistics industry is massive — global freight is a multi-trillion dollar sector — and yet it remains one of the least digitised parts of the global economy. Most freight companies still rely heavily on phone calls, emails, and spreadsheets to run operations that move goods worth enormous sums across complex international supply chains. The inefficiency is staggering, and the opportunity for AI to add real value is correspondingly large.

What makes the Cargofy model particularly compelling from a structural standpoint is that it does not require its customers to undergo a painful or disruptive digital transformation before they can start using the product. The AI agents slot into existing workflows and existing toolsets. The humans on the team continue to work the way they always have, except that they now have AI colleagues handling the most repetitive and time-intensive parts of the job. This is a very different value proposition from enterprise software that requires months of implementation, staff retraining, and process redesign before delivering any benefit. Cargofy's approach is more like hiring a highly capable new team member who shows up on day one already knowing how everything works.

For the broader AI industry, this kind of domain-specific, workflow-native agent deployment represents one of the most promising near-term paths to meaningful AI adoption in traditional industries. The technology is not replacing human judgment in complex situations — it is absorbing the high-volume, low-judgment work that consumes most of the working day, freeing up human operators to focus on relationships, exceptions, and decisions that genuinely require experience and nuance. That balance — AI handling volume, humans handling complexity — is increasingly looking like the model that actually works in practice, as opposed to the fully autonomous AI visions that have captured imagination but not yet delivered consistent real-world results.

Cargofy's Series A is a meaningful moment not just for the company itself, but for anyone watching the intersection of artificial intelligence and global commerce. With strong backing, proven results, a differentiated data advantage, and a global expansion plan that is both ambitious and thoughtfully structured, Cargofy looks well-positioned to become one of the defining AI companies in logistics over the next few years. The digital worker era in freight has arrived, and this funding round is one of the clearest signs yet that the industry is ready to embrace it.