You probably have not heard of Dmitry Sverdlik, founder and CEO of Xenoss. And that, in a world obsessed with the loud and the hyped, is precisely the point. Dmitry is not the guy throwing launch parties funded by venture capital funny money, nor is Xenoss a household name peddling the latest social media distraction. Instead, he is one of those quiet engineers who, years ago, peered into the messy, chaotic guts of the internet economy and saw not just a problem, but an organizing principle – a gaping inefficiency that everyone else was either too busy or too blind to fix.

His revelation? “Data had become the real product,” Dmitry says, a statement so simple it sounds almost like a platitude. Except, he realized it back when most companies still thought data was just the exhaust fumes of their actual business. This was not about hoarding user info to sell more ads in the usual way; this was about understanding that the ability to build, manage, and intelligently deploy massive, complex data systems was the new bedrock of value. For any company. In any industry.

Dmitry’s story, and that of Xenoss, his New York-based software engineering firm, is about what happens when a deeply technical mind confronts a market full of businesses flailing around with digital transformation, often choking on the very data they think will save them. It is a classic tale of seeing what others do not, and then building the specialized tools – and the team – to capitalize on that insight. And it is why, in 2025, if you are looking for entrepreneurs who are not just chasing trends but building the foundational layers of future business, Dmitry is a name you need to know.

The AdTech Crucible

Dmitry cut his teeth in the digital equivalent of a blast furnace: AdTech. “Since the early 2000s, I’ve been operating at the edge of AdTech innovation,” he recounts. Think about that for a moment. The early 2000s. Mobile phones were still relatively dumb. The internet advertising ecosystem was a primordial soup. His team was behind “the world’s first mobile DSP.” A Demand-Side Platform, for the uninitiated, is a system that lets advertisers buy ad impressions across a universe of websites and apps in real-time. Doing this on mobile, back then, was like trying to build a Formula 1 car while the road was still being paved. He even navigated an AdTech startup to a “successful exit.”

These were not just lines on a resume. This was an education. “These years gave me a deep appreciation for domain complexity,” he says. AdTech, with its billions of daily transactions, its need for microsecond responses (real-time bidding), and its demand for systems that absolutely cannot fail (high-availability systems), is a brutal testing ground for engineers. It is where you learn about “data pipelines under massive load” not as a theoretical concept, but as a series of frantic late-night calls because something, somewhere, is about to break under the deluge.

More importantly, Dmitry saw a pattern. “Great businesses struggled to scale because of technical execution gaps.” They had the ideas, the market, the ambition. What they lacked was the engineering firepower, the deep, specialized knowledge to build the digital engines they needed. “That’s what led me to start Xenoss,” he states, “a software development service company purpose-built to solve this particular kind of challenge.” He did not want to build another AdTech product. He wanted to build a company that could build any complex, data-heavy product for anyone who had hit that technical wall.

From Niche Commando Team to AI Infrastructure Gurus

When Xenoss launched in 2013, it did not try to be all things to all people. That is the fastest way to become nothing to anyone. “Xenoss started with a clear niche: building custom software for the MarTech and AdTech space,” Dmitry explains. “Off-the-shelf products didn’t satisfy their needs and business objectives.” These clients were not looking for slightly better AdTech platforms; they were looking for someone to build the intricate, bespoke machinery that standard software vendors simply did not offer.

Then came that dawning realization about data being the actual product. By 2024, it was undeniable. “That led us to reevaluate the data engineering and machine learning expertise we accumulated over the years,” Dmitry notes. The intense, specialized work they had done in the demanding AdTech and MarTech sectors had, almost by accident, forged an elite capability in handling exactly what was becoming the business world’s biggest headache – and its biggest opportunity. “We’ve decided to utilize our extensive experience to help more clients across domains with their data challenges and AI exploration.”

So, Xenoss pivoted, or rather, expanded its aperture. Today, they are the people you call when you need “tailored AI and data platforms” to solve knotty problems like hyperautomation, operational efficiency, or finding new revenue streams hidden in your data. This is not about sprinkling some AI fairy dust on an old spreadsheet. “AI doesn’t create value on its own,” Dmitry insists, with the quiet conviction of someone who has seen too many AI projects go sideways. “It needs a solid and scalable data infrastructure supporting it.”

This is the unglamorous truth of the AI revolution. Everyone wants the “intelligence,” but few want to do the hard, foundational work. “At Xenoss, we engineer the entire foundation–data collection systems, pipelines, governance, monitoring, and scalable serving layers.” Dmitry continues, “It’s the deep infrastructure work that makes AI reliable, maintainable, and factually useful.” Their edge? “We build the systems within real-world constraints: incomplete data, legacy systems, and regulatory pressure.” They get AI into production fast, where it can start delivering value, not just PowerPoints.

The Data Whisperers

Who hires these data commandos? “Our roots are in AdTech and MarTech,” Dmitry says, but now the client list stretches into “Oil and Gas to Finance and Banking.” These are not startups looking for their first app. “Most clients already have solid internal teams but run into architectural or scaling limits. They turn to us when off-the-shelf tools fall short and the stakes demand custom engineering.”

The problems are usually deeply embedded. “Fragmented data sources, brittle pipelines, models that silently degrade in production, or outdated infrastructure that can’t support AI workloads.” Xenoss comes in, not with a pre-packaged solution, but with a team ready to “rebuild the foundation, designing scalable systems, integrating AI where it actually moves the needle, and giving our clients complete control over their data lifecycle.” That last part – “complete control” – is key. It is about turning data from a source of anxiety into an asset, a weapon.

And they do it with an almost obsessive focus on integrity and security. “We design for traceability from the start,” Dmitry emphasizes, listing data lineage, audit logs, and automated validation. His security principle is refreshingly blunt: “If it’s not observable, it’s not secure.” For AI ethics, they “avoid ‘black box’ models unless there’s a business case, and even then, we make sure they’re explainable and monitored.” This is not just good practice; it is good business when you are handling the crown jewels of other companies.

Success, for Dmitry, is not just about hitting financial targets, though Xenoss did achieve a staggering 932% revenue growth over three years, landing it on the Inc. 5000 list. “If what we build runs critical business functions, scales under load, and earns trust from internal users, that’s impact,” he says. The real prize? “When a client stops seeing data as a problem and sees it as a competitive asset.”

The Dmitry System

How does he pull it off? Dmitry describes his leadership as built on “clarity, autonomy, and accountability.” He hires smart people, points them at the mountain, and gives them the gear to climb it. “At Xenoss, we operate with high autonomy and high responsibility.” Innovation is not accidental; it is “structured” via an internal hub. Operational excellence is “a system” of rigorous processes. He stays close to his engineers and clients, “because that’s where real alignment happens.”

It was not always an easy sell. “Early on, one of the biggest challenges was earning trust from large enterprises as a lean, engineering-led company,” he admits. They did not have a massive sales force. They had “strong execution.” They delivered. Reputation, it turns out, is still a powerful currency. The shift to explicitly focus on AI and data engineering in 2024 “aligned perfectly with both client demand and our core strengths.”

Looking ahead, Xenoss is “platformizing” its expertise into reusable components to speed up impact. They are digging into “agent-based systems” for decision-making and hyperautomation, and deepening partnerships with tech giants like AWS, GCP, Databricks, and Snowflake.

Away from the digital coalface, Dmitry practices a kind of strategic disconnection to maintain balance. He also mentors early-stage founders. “It’s a way to give back, but it also keeps me sharp,” he says. “Helping others navigate tough decisions forces me to think clearly and stay grounded.”

His advice to aspiring innovators is straightforward and practical, reflecting his experience through various hype cycles: “Focus on real pain points. Companies that win aren’t the ones with the best pitch decks; they’re the ones whose systems are still running, still scaling, and still delivering value one, two, three years later.”

In a world drowning in data and thirsty for solutions, Dmitry Sverdlik and Xenoss are quietly, competently, building the dams, the aqueducts, and the turbines. And that is a story worth following.

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