The iGaming industry talks a lot about technology being flexible, modular and scalable. But the real test comes after the first integration is complete: how quickly can you launch the next brand? 

Through the partnership between Betable and Delasport, eight brands are already live in the UK. And once the core integration was established, an additional brand was brought to market in less than one month. 

Eight brands are already live through the Betable-Delasport integration. What does that tell you? 

Reece: The real proof of scalability comes after the first launch. 

Connecting two platforms once is important, but the bigger question is whether that same foundation can support the next brand without starting again from scratch. 

That is what we have achieved with Betable. The core integration between its wider platform and Delasport’s sportsbook is already in place and proven. When a new brand is ready to launch, we can focus on what makes that proposition unique rather than rebuilding the technology underneath it. 

Eight live brands show that this is no longer just an integration. It is a repeatable launch model. 

One additional brand in the UK went live in less than two weeks. What made that possible? 

Reece: We were not starting from a blank page. 

The core connections between Betable’s platform and our sportsbook had already been built, tested and proven in a live environment. That includes critical areas such as the account, wallet and wider player journey. 

So instead of spending time rebuilding those foundations, the teams could focus on the new brand itself - its configuration, content, branding, testing and operational readiness. 

That is where the speed came from. 

We removed duplicated technical work and concentrated on what actually needed to change. As a result, the brand moved from launch preparation to go-live in less than one month. 

Does moving faster mean every brand ends up with the same sportsbook? 

Reece: Not at all. 

A reusable foundation should make launches more efficient, not make brands look or feel the same. 

The underlying technology can remain consistent while the player-facing experience is tailored around the operator. Each brand can decide how its sportsbook looks, which content is prioritised and how the overall proposition reflects its audience and commercial strategy. 

The foundation stays proven and stable. The experience remains individual. 

Which parts of the model can be reused? 

Reece: The core integration between Delasport’s sportsbook and Betable’s wider platform. 

Betable provides the broader ecosystem across areas such as player account management, casino, CRM, payments, compliance and operations. Delasport provides the sportsbook layer, including sports coverage, native horse racing, in-play betting, personalisation, engagement tools and risk management. 

Once those systems are successfully connected, there is no reason to treat every additional brand as a completely new integration project. 

The framework already exists. From there, the focus moves to configuration, testing, and the requirements of the individual brand. 

How do you maintain quality when the launch window is so short? 

Reece: Speed should come from removing repetition, not removing controls. 

The core integration has already been tested through previous launches and live operation, which removes a significant amount of technical uncertainty. 

But every new brand still goes through the right configuration, validation, testing, and readiness processes. 

The quick launches happened because the model was proven, and the teams knew how to execute it efficiently - not because steps were skipped. 

How important was the collaboration between Betable and Delasport? 

Reece: It was critical. 

A repeatable technical model only works if the operating model is just as strong. 

Both teams need clear ownership, fast communication, and a shared understanding of how a brand moves from configuration through testing and into launch. 

When everyone understands their responsibilities and decisions can be made quickly, the entire process becomes much more efficient. 

The technology created the foundation. The way the two teams worked together allowed us to make full use of it. 

Why does this matter commercially for operators? 

Reece: Because market opportunities do not wait for long integration projects. 

Operators may want to launch another brand, enter a new market, or respond quickly to a commercial opportunity. If every move requires another major technical programme, technology becomes a barrier to growth. 

A reusable model changes that. 

It gives operators a faster and more predictable route to market because they are building on a foundation that is already live and proven across multiple brands. 

That is ultimately what scalable technology should do: make growth easier, not more complicated. 

What does this prove beyond speed to market? 

Reece: It proves that scale does not have to mean more complexity. 

Without a common foundation, eight brands could mean eight separate implementations, more technical dependencies, and more maintenance. 

With a reusable model, the portfolio can grow while much of the underlying technology remains consistent. 

That helps with launch speed, but it also makes ongoing support, product development and the rollout of future capabilities more efficient. 

How would you summarise what the Betable integration has achieved? 

Reece: The partnership has moved well beyond its original integration phase. 

We now have a proven route for launching sportsbook brands on top of an established technical foundation. 

Eight live brands demonstrate that the model scales. Bringing another brand to the market quickly demonstrates how quickly it can scale. 

That is the real achievement: not simply connecting two technologies but creating a launch model that gives operators a faster, simpler and more predictable path to growth. 

From integration to launch infrastructure 

The first launch proved the integration worked. The launches that followed proved it could scale. 

And the latest launch proved something even more important: once the right foundation is in place, growth does not have to start from scratch. 

The post The Real Test of Scalability: Launching the Next Brand in Under a Month  first appeared on Delasport.

If you’ve worked with Kafka long enough, you’ve probably seen a broker fail with an OutOfMemoryError. 

The natural assumption is that the broker has exhausted its available memory. The investigation usually starts with familiar questions: 

• Is the JVM heap too small? 

• Is there a memory leak? 

• Has the container reached its memory limit? 

• Is the node under memory pressure? 

Sometimes, however, every one of those questions leads to a dead end. 

This article explores one such scenario—a failure that initially looked like a classic memory issue, but ultimately had nothing to do with available RAM. Instead, the root cause was hidden in the interaction between Kafka’s storage engine and the operating system’s virtual memory management. 

Understanding why requires looking beyond the JVM. 

The Puzzle 

Imagine a Kafka broker that suddenly refuses to start. 

The exception is familiar: 

java.lang.OutOfMemoryError 

The response is equally familiar. 

Check the heap. 

Healthy. 

Check container memory. 

Healthy. 

Check node memory. 

Healthy. 

Increase JVM heap. 

No change. 

Increase Kubernetes memory limits. 

Still no change. 

At this point, the obvious explanations have been exhausted. Yet the broker still reports an OutOfMemoryError. 

So what resource has actually been exhausted? 

Looking Beyond the Heap 

One of Kafka’s greatest strengths is its storage architecture. 

Instead of constantly reading data through traditional I/O operations, Kafka relies heavily on memory-mapped files (mmap). This allows the operating system to efficiently cache and access log data while reducing unnecessary memory copies between user space and kernel space. 

Every Kafka log segment is backed by several files: 

000000000000.log 
000000000000.index 
000000000000.timeindex 

These files are memory mapped by the broker, allowing Kafka to access them efficiently while letting the operating system handle page caching. 

This design is one of the reasons Kafka achieves such high throughput. 

But it also introduces an important dependency that is often overlooked. 

Every memory-mapped file consumes a virtual memory mapping managed by the operating system. 

Unlike JVM heap, these mappings are not limited by Java’s heap size. 

They’re an operating system resource. 

When a Small Configuration Creates a Large Problem 

Now consider the following configuration: 

segment.ms = 10000 

At first glance, nothing appears unusual. 

Kafka simply rotates log segments every ten seconds. 

But let’s follow the consequences. 

A single partition now creates: 

• 6 segments every minute 

• 360 segments every hour 

• 8,640 segments every day 

Every segment generates multiple files. 

Every file may be memory mapped. 

Multiply that across dozens or hundreds of partitions and a typical retention period, and what initially looked like a harmless configuration becomes millions of files that Kafka must manage. 

The JVM still has plenty of heap. 

The container still has available memory. 

The operating system, however, has a rapidly growing number of memory mappings to maintain. 

Eventually, that limit is reached. 

Why More Memory Doesn’t Help 

This is where the error message becomes misleading. 

The exception suggests a memory shortage. 

Naturally, engineers respond by increasing available memory. 

Unfortunately, memory was never the limiting factor. 

The limiting resource was the number of virtual memory mappings available to the Kafka process. 

Once that limit was reached, additional mmap() operations failed. 

From the JVM’s perspective, the failure surfaced as an OutOfMemoryError, even though physical memory remained available. 

The lesson is subtle but important: 

Not every OutOfMemoryError indicates that your application has exhausted RAM. 

Sometimes it indicates that the operating system can no longer provide another resource required to allocate memory. 

Understanding that distinction changes the entire direction of the investigation. 

Understanding the Chain of Events 

The interesting part wasn’t the configuration itself. 

It was understanding how a single Kafka setting propagated all the way down to the operating system. 

The chain looked like this: 

Aggressive segment rotation 
        ↓ 
More log segments 
        ↓ 
More .log and index files 
        ↓ 
More memory-mapped files 
        ↓ 
More virtual memory mappings 
        ↓ 
Operating system limit reached 
        ↓ 
mmap() fails 
        ↓ 
JVM reports OutOfMemoryError 
        ↓ 
Kafka broker cannot start 

Once the entire chain became clear, the solution became surprisingly straightforward. 

Correcting the segment rotation policy dramatically reduced the number of log segments. 

No JVM tuning was required. 

No larger Kubernetes nodes. 

No additional broker memory. 

Simply understanding which resource had actually been exhausted. 

Engineering Doesn’t Stop at the Fix 

Fixing the configuration resolved the immediate problem. 

But solving an incident once isn’t enough. 

The more important question became: 

How do we ensure we detect this long before a broker reaches that state again? 

Traditional Kafka dashboards typically focus on metrics such as: 

• JVM memory 

• CPU usage 

• Consumer lag 

• Disk utilization 

• Network throughput 

Those metrics remained perfectly healthy throughout this scenario. 

The underlying resource was invisible. 

To close that observability gap, we introduced additional monitoring focused on the resources that actually mattered. 

Among the metrics we now track are: 

• Log segment count per topic, allowing us to identify abnormal segment growth before it becomes operationally significant. 

• Open file count per Kafka broker container, providing early visibility into resource consumption that isn’t reflected in traditional JVM metrics. 

These metrics complement—not replace—the standard Kafka dashboards. Together they provide a more complete picture of broker health and make this entire class of problems visible long before they affect availability. 

Looking Beyond Kafka 

Although this example involves Kafka, the lesson extends far beyond a single technology. 

Modern distributed systems depend on many operating system resources that rarely appear in standard dashboards. 

Heap memory is only one of them. 

Others include: 

• File descriptors 

• Virtual memory mappings 

• Threads 

• Ephemeral ports 

• Inodes 

• Network connection tracking 

These resources are usually invisible—until they’re exhausted. 

Building reliable platforms means understanding not only how applications behave, but also how they interact with the operating system underneath them. 

Sometimes the most valuable debugging tool isn’t adding more resources. 

It’s identifying which resource is actually running out. 

Final Thoughts 

The most interesting production problems are rarely solved by increasing limits or allocating larger machines. 

They’re solved by understanding how systems work beneath the abstraction layers we interact with every day. 

Kafka’s use of memory-mapped files is an elegant optimization that enables exceptional performance. But like every optimization, it introduces operational characteristics that engineers should understand when running Kafka in production. 

For us, this challenge reinforced a simple principle: 

The best long-term fixes don’t just solve today’s problem—they improve tomorrow’s observability. 

The post When Kafka Runs Out of Memory Without Running Out of Memory  first appeared on Delasport.

For Delasport, this shift is already part of how the company builds sportsbook technology. Its focus is on automation, real-time intelligence, operator control, and player-first experiences. As major betting events such as the 2026 FIFA World Cup approach, operators need infrastructure that can handle scale while helping them act faster and deliver more relevant betting journeys.

The next competitive battleground will not be volume alone. It will be speed, intelligence, personalization, operational efficiency, and the ability to turn every betting moment into a meaningful experience. This is where Delasport’s approach stands out: building sportsbook infrastructure that helps operators scale, stay in control, and engage players more effectively.

Trading: Human Expertise, Enhanced by AI

AI will not replace sportsbook traders. The future belongs to traders empowered by AI.

Trading has relied on algorithms for years, but newer AI models can process large volumes of historical and real-time data, detect pricing errors, monitor market movement, identify anomalies, and support faster decisions.

This allows trading teams to spend less time on repetitive manual work and more time on strategy, liability control, market positioning, and complex risk decisions.

AI can help operators identify odds movements in real time, detect exposure risks earlier, separate recreational volume from sharper activity, and prioritize situations that need immediate attention.

This is where platform depth matters. Delasport already provides operators with tools such as Bet Monitor, Risk Monitor, Price Monitor, Risk and Limits Controller, Event Management, Performance Reports, odds consistency checks, odds alerts, and real-time reporting. These tools are exactly the type of infrastructure AI can enhance further, helping traders act faster and with greater confidence.

Personalization Is Becoming Essential

For years, sportsbooks have treated very different players in almost the same way. A high value in-play tennis bettor, a casual World Cup fan, and a weekend football accumulator player often land on the same homepage and see the same betting journey.

That model is changing.

Delasport’s My Sportsbook Personalization gives players more control by allowing them to define their preferred sports, leagues, teams, and interests. Instead of searching through irrelevant content, players can return to a sportsbook lobby built around what they actually care about.

This approach also extends across features such as My Combo, My Sports Suggestions, My Enhanced Odds, and My Personal Trader. The goal is clear: make the sportsbook feel more relevant, intuitive, and personal.

AI pushes this further by helping operators analyze behavioral patterns, preferred sports, bet types, stake sizes, bonus sensitivity, live betting behavior, and churn signals. The winning sportsbook will not be the one that shows the most markets. It will be the one that shows the right markets, to the right player, at the right moment.

Live Betting Needs Real-Time Intelligence

In-play betting is built on speed. Momentum, risk, pricing, and player intent can change in seconds, which means static sportsbook environments are no longer enough.

AI can help live betting become more dynamic by processing live event data, market
movement, expected goals, and player behavior at the same time. This can support faster momentum detection, more responsive pricing, shorter suspension times, and more contextual bet suggestions.

Delasport is already building in this direction. Betiator, the world’s first crash game for
sports, brings crash-game mechanics into live sports betting. Players follow real in-play
action, choose when to enter, and cash out before the moment hits. It creates a faster,
more visual, and more entertainment-led way to engage with live sports.

Other Delasport features, including Live Center, Live Score Animations, Quick Cash-Out, and the standalone My Bets page, also support this real-time experience. Together, they reflect the industry’s shift from static odds pages to live, visual, interactive betting entertainment.

Risk, Fraud, and Responsible Gaming

Modern sportsbook risk management goes far beyond liability monitoring. Operators must also manage bonus abuse, multi-accounting, arbitrage, payment fraud, account takeovers, suspicious betting patterns, and coordinated syndicate activity.

AI can strengthen this by connecting signals across identity, payments, wagering behavior, device data, player activity, and market exposure. Instead of reviewing disconnected alerts, teams can work from a more unified risk view.

Delasport’s sportsbook already includes tools such as Risk Alerts, Sports Integrity
Management, Risk and Limits Controller, Bet Monitor, Risk Monitor, Price Monitor, and
configurable Max Odds. AI can enhance these capabilities by helping operators detect
patterns faster, prioritize urgent risks, and reduce noise from fragmented monitoring
systems.

AI also has an important role in responsible gaming. Operators need to identify early signs of potential player harm before they escalate, such as sudden stake increases, chasing losses, very long sessions, abnormal late-night behavior, repeated failed deposits, or major changes in bet frequency.

By detecting these changes earlier, AI can support more proportionate interventions, from safer messaging and limit reminders to cooling-off options or temporary restrictions where needed. This creates a safer environment for players while helping operators build long term trust and compliance strength.

Smarter CRM, Not Louder Campaigns

Traditional sportsbook CRM often relies on broad campaigns: generic offers, standard
reload bonuses, or mass price boosts. AI allows operators to move from campaign-led
communication to contextual engagement.

Instead of asking what promotion should be sent to the full database, operators can ask: what is the right message for this player, at this moment, around this event?

Delasport’s engagement toolkit already supports this direction through features such as
Combo Booster, Combo Insurance, Combo of the Day, Odds Boost, Suggested Fixture
Cards, Risk-Free Bets, Free Bets, Missions, Tournaments, and Spin the Wheel.

A football accumulator player may respond best to My Combo or Combo Insurance. A live bettor may be more interested in Betiator, Quick Cash-Out, or in-play suggestions. A casual player may engage more with Missions, Tournaments, or gamified campaigns.

The future of CRM is not more noise. It is more relevance.

Delasport’s Vision: An Intelligent Sportsbook Ecosystem

The true AI transformation in sports betting will not come from adding a chatbot to an old platform. It will come from building sportsbook operations around intelligence,
automation, real-time data, personalization, and connected risk control.

This is the direction Delasport is already taking. Its sportsbook is designed as a connected ecosystem where trading tools, personalization features, live betting products, engagement mechanics, CRM capabilities, risk controls, and responsible gaming support work together rather than in isolation.

AI is only as powerful as the infrastructure it is built into. Long-term competitive advantage depends on a platform that can connect data, automate decisions, surface insights, and adapt to the player and the moment.

In a market where every player, every second, and every betting moment matters,
Delasport is building the sportsbook infrastructure for what comes next.

Published on: Gaming Intelligence

The post AI Is Moving the Sportsbook Forward - And Delasport Is On Track With it first appeared on Delasport.

There are few moments in sport that concentrate attention like the FIFA World Cup. For sports operators, it is not just another busy period in the calendar.

It is the moment when regular bettors, casual national fans, casino players, national team supporters and once-in-a-tournament users all arrive at the same place, looking for a way to be part of the action.

That creates an enormous opportunity, but not every operator is ready to grasp it.

A major tournament puts every part of the sportsbook experience to the test. Many casual players arrive ready to bet, but if the sportsbook does not deliver the right sports betting experience, they will not stick around.

When the schedule is intense and attention is fragmented, the difference between a sportsbook that simply functions and a sportsbook that is built to retain bettors becomes impossible to ignore. At Delasport, we see the upcoming World Cup as much more than a traffic spike. It is a defining product moment for operators. The winning operators are those whose sportsbooks have what it takes to make a strong first impression and, more importantly, retain players during and after the tournament.

The real advantage will belong to operators who deliver a sportsbook experience that feels ready for the scale of the event – fast, focused, differentiated and genuinely exciting.

That is the thinking behind Delasport’s sportsbook proposition: a sportsbook built to take the sports betting experience to new heights.

The problem with ‘more’

The instinct before a major football tournament is often to add more. More markets. More offers. More widgets. More landing pages. More promotions fighting for the same space.

The intention is understandable. During a World Cup, there is more to bet on and more attention to capture. But from the player’s perspective, ‘more’ can quickly become noise.

A casual fan does not want to search through endless menus to find tonight’s match. A live bettor does not want to lose momentum during a dangerous attack because the path to the market is too long. A casino player crossing into sports for the tournament does not necessarily understand complex bet types or sportsbook layouts. Even experienced players value speed when fixtures are coming thick and fast.

This is where Delasport’s approach starts: remove the friction before adding the excitement.

“In the group phase, the challenge is volume. With multiple teams, fixtures and storylines developing in parallel, users need clarity.”

The sportsbook should make the tournament feel easy to enter, but hard to leave. Once the user is there, it should create clear routes into the action, whether that action is a traditional pre-match bet, a live market, a boosted opportunity, a gamified micro-betting moment or a jackpot-style mechanic.

The World Cup is too valuable to be treated as just another event category. It needs its own environment, its own rhythm and its own engagement strategy.

Tournament Hub: all the matches, one place, no distractions

Delasport’s Tournament Hub was built around a very simple idea: all the matches, one place, no distractions.

During a major tournament, that simplicity becomes a powerful advantage. Players need to understand what is live, what is next and where the most relevant betting opportunities sit. Operators need a focused framework that captures attention without overwhelming the user.

Tournament Hub gives the event a dedicated space inside the sportsbook. Instead of pushing players through general navigation, it brings the competition together in a clean, event-first experience. Live fixtures are prioritised. Upcoming matches are easy to find. Key markets are closer to the surface. The route from match to bet is shorter.

For a World Cup, this matters across every stage of the tournament.

In the group phase, the challenge is volume. With multiple teams, fixtures and storylines developing in parallel, users need clarity. Tournament Hub helps organise that complexity and keeps the experience focused on the next betting opportunity.

In the knockout phase, the challenge shifts to intensity. Every match carries more weight. Every decision feels bigger. Tournament Hub supports that drama with knockout-stage visibility, matchups, outcomes and live odds in one place.

Around the matches, the hub creates room for what players actually care about during a major event: hot trends, odds boosts, boosted bet builders, boosted combos, live standings and big calls. These elements should not feel buried or disconnected. They should sit naturally within the tournament journey.

For operators, the benefits are immediate. Faster access to odds and quick-bet flows can increase betting activity. A focused event experience keeps users engaged for longer. Streamlined navigation shortens the path from discovery to bet. And because the framework is scalable, the same approach can support other high-traffic tournaments long after the World Cup ends.

The goal is not only to cater to players in the best possible way during the World Cup tournament, but also to offer them perks in the weeks after it ends.  

BETIATOR: live sport with crash-game tension

If Tournament Hub solves the navigation challenge, BETIATOR answers a more ambitious question: how can live sports betting become more active, more visual and more entertaining?

Traditional in-play betting is powerful, but it often follows the same pattern. A player picks a market, places a bet and waits. The match continues, but the interaction becomes passive.

BETIATOR changes that rhythm.

It is the first crash game built on live sports, creating a new category of sports entertainment through gamified micro-betting. The experience runs alongside live matches and turns real-time action into a simple, visual, second-by-second decision.

A player selects a live match, places a BETIATOR bet, watches the line rise as the multiplier grows and decides when to cash out before the crash moment arrives. Timing is the centre of the experience.

That is what makes it so compelling for a sportsbook audience. Unlike a random crash game, BETIATOR is connected to live sports. The player is not just watching a multiplier move in isolation. They are reading the match, feeling the momentum and deciding whether to hold or cash out.

For football, that is a natural fit. Attacks build. Pressure shifts. A counterattack can change the mood in seconds. BETIATOR turns those moments into active participation.

It is also deliberately simple. There are no complex markets to decode and no long list of odds to compare. The action is immediate: one bet, one line, one decision. That makes it accessible for casual users while still giving more experienced sports fans a sense of control and timing.

For operators, the commercial case is just as strong. BETIATOR creates incremental in-play revenue by capturing underused moments during the match. It does not need to replace the sportsbook journey; it intensifies it. It also gives operators a differentiated product in a market where many sportsbooks still feel too similar.

During a World Cup, that differentiation has real value. The event already brings the attention. BETIATOR gives operators a more memorable way to hold it.

SuperPot: where sports betting meets jackpot excitement

Not every World Cup player behaves like a traditional sports bettor. Some arrive from casino. Some are casual fans drawn in by the scale of the tournament. Some want a high-reward experience without navigating deeper sportsbook complexity.

SuperPot was designed for that wider audience.

“The tournament is not one big peak; it is a sequence of peaks. Opening matches, national-team fixtures, group-stage drama, knockouts, semi-finals and the final all create different waves of attention.”

It combines the excitement of jackpots with the thrill of sports betting, using unique sure-winner mechanics to create a sports jackpot product with broader appeal. In practice, it helps bridge two major verticals: sportsbook and casino.

That cross-vertical role is important. Sportsbook operators often talk about convergence, but the experience has to make sense to the player. SuperPot does that by bringing jackpot-style excitement into a sports environment. Sports fans get a fresh way to engage with the tournament. Casino players get a familiar type of thrill connected to live sporting interest.

For operators, this opens up serious promotional potential. A product that speaks to both sports and casino audiences can support stronger campaigns, broader reach and more effective cross-sell. It can also improve retention by giving players another reason to return beyond a single match or single bet.

That repeat element matters during a World Cup. The tournament is not one big peak; it is a sequence of peaks. Opening matches, national-team fixtures, group-stage drama, knockouts, semi-finals and the final all create different waves of attention. SuperPot adds another layer of continuity across that cycle.

The best engagement tools do not distract from the sportsbook. They give players more reasons to stay within it.

One connected World Cup journey

The real strength of Delasport’s sportsbook is not only in individual products, but in how those products support one another.

Tournament Hub creates the dedicated World Cup destination. BETIATOR brings gamified, live-match intensity into the experience. SuperPot adds jackpot-style excitement with cross-vertical reach.

Together, they help solve the central operator challenge: how to turn tournament attention into repeated, meaningful engagement.

A player might enter through Tournament Hub to check the day’s matches. They may find a boosted opportunity, follow live standings or move straight into a key market. During the match, BETIATOR offers a faster, more active way to participate in the live action. Across the tournament, SuperPot provides another reason to return, especially for users who enjoy the high-reward feel of jackpot mechanics.

This is the difference between a sportsbook that simply lists World Cup matches and a sportsbook that owns the tournament experience.

For the player, the journey is cleaner. For the operator, the product works harder.

Product readiness is commercial readiness

The World Cup will bring traffic. That part is almost guaranteed. The harder question is whether operators are ready to convert that traffic into long-term value.

Acquisition campaigns may bring users in, but the sportsbook experience determines what happens next. If navigation is slow, if live betting feels passive, if promotions are disconnected or if casual players feel lost, attention will disappear quickly.

A strong World Cup strategy should therefore start with product readiness.

Is there a dedicated tournament environment?
Is the route from match to bet short enough?
Are live moments being used properly?
Does the product offer something different from competing sportsbooks?
Can casino-style users find an easy point of entry into sports?
Are there reasons to return between headline fixtures?

These are the questions operators need to answer before kick-off, not halfway through the tournament.

At Delasport, our focus is on helping operators answer them with a sportsbook that is ready for high-pressure, high-opportunity events. Tournament Hub, BETIATOR and SuperPot each play a different role, but they are built around the same principle: reduce friction, increase engagement and give players a better reason to come back.

Built for the big stage

The upcoming World Cup will be one of the biggest sportsbook opportunities in years. It will reward operators with strong trading, smart campaigns and reliable technology. But the real winners will be those who understand that the player experience is now part of the competitive battleground.

Players will remember the sportsbook that made the tournament easier to follow. They will return to the product that gave them excitement beyond the standard bet slip. They will respond to experiences that feel fast, relevant and built around the event itself.

That is where Delasport’s sportsbook is positioned: not as a place where World Cup markets simply appear, but as a platform designed to help operators shape the full tournament experience.

With Tournament Hub, operators get a focused destination for the competition. With BETIATOR, they get a new live sports entertainment category built around gamified micro-betting. With SuperPot, they get a sports jackpot product that connects sportsbook and casino audiences through high-reward excitement.

The World Cup will bring the audience. Delasport helps operators turn that audience into action, energy and loyalty. For operators, winning starts before the first whistle. It starts with a sportsbook built for the big stage.

The post Built for the big stage: Delasport’s sportsbook vision for football’s biggest tournament  first appeared on Delasport.

This is usually the moment when the focus begins to shift - from simply delivering functionality to making better-informed decisions.

Drawing from more than eight years at Delasport, Alexander Minchev, Head of Frontend Development, shares how the role of Frontend has gradually evolved alongside the product itself. In his experience, this transformation is not driven by a single moment or major change, but by the accumulation of real-world challenges where seemingly logical solutions no longer deliver the best results for the product.

From Predictable Processes to Unexpected Outcomes

In the early stages, the workflow tends to be relatively straightforward and predictable. Tasks move through a familiar cycle - implementation, code review, quality validation, and integration. Everything appears structured and efficient: work progresses steadily, tickets are closed, and sprints finish successfully.

And in many ways, there are no surprises.

Over time, however, a recurring pattern begins to emerge. Well-defined tasks that seem perfectly reasonable on paper start creating unexpected issues once integrated into the product. Sometimes the root cause lies in hidden dependencies. Other times, it comes from accumulated business logic. And occasionally, the issue is simply that a technically “correct” solution is not necessarily the best solution for the product in general.

That becomes one of the first clear signals that the existing approach is no longer fully aligned with the product’s real needs.

And this is exactly where the need for a deeper transformation starts to take shape - one where the Frontend engineer contributes not only through implementation, but through informed technical judgment.

When Complexity Changes Everything

As products continue to grow, complexity naturally increases with them. Every new feature begins interacting with existing systems in ways that are not always obvious - neither during design nor throughout development.

At the same time, user expectations continue to rise. Users expect speed, predictability, and seamless experiences regardless of their device or connection quality. Meeting those expectations requires far more than simply shipping working functionality.

In this environment, a more uncomfortable - but critical - question starts to emerge:

“Is the product actually improving?”

Because there is a fundamental difference between building features and creating real value.This does not mean the previous approach was wrong. Rather, the scale and maturity of the product begin demanding a different level of thinking and decision-making.

The shift in Mindset

In such an environment, the way tasks are perceived inevitably change as well.

Tasks are no longer viewed as isolated technical activities, but as part of a broader system of decisions.

Naturally, this leads to more important questions being asked even before implementation begins:

• What problem are we actually solving?

• Is there a better approach?

• How will we validate that it works?

• How will success be measured?

These are not procedural questions. They directly influence what gets built - and whether it should be built that way at all.

This is where the role of the Frontend engineer begins to evolve into something much more strategic: an active participant in shaping the solution itself.

With that comes a deeper transformation in the development process. The discussion is no longer focused solely on how to implement a solution, but on which solution is the right one and what long-term impact it will have on the product.

That means carefully evaluating trade-offs, understanding what is gained, and recognizing what complexity is being introduced into the system.

The shift in Process

Much of this transformation started happening during team refinement and planning sessions. Initially, these meetings were mainly used to clarify requirements and align on implementation details. Over time, however, they gradually evolved into early-stage solution design discussions.

Instead of assuming that the proposed solution was already fixed, teams began treating it as something that could still be challenged and improved.

As a result, the conversations started changing:

• What are the alternatives?

• Can the solution be simplified?

• Is there a more efficient way to deliver value?

Quite often, this is the stage where it becomes clear that there is no single “correct” solution to a problem.

And this is also where the role of the Frontend engineer becomes noticeably more influential - not because of a formal process change, but because it becomes increasingly obvious that good decisions require strong technical perspective and long-term product awareness from the very beginning.

When Is Something really “Done”?

Over time, the understanding of what it means for a task to be “done” also changes.

A feature that simply works is no longer enough. For a solution to be considered truly complete, there needs to be visibility into how it behaves in real-world conditions - through logging, metrics, and user behavior analysis.

And not as an afterthought after release, but as part of the implementation process itself.

Without that visibility, teams operate largely on assumptions. Something may appear successful, but without real data, it becomes difficult to understand how it performs across different scenarios or how users interact with it.

This is where Frontend starts playing a much more active role. That may involve proposing what should be measured, identifying potential risk areas, or helping define what success actually means for a feature.

As a result, monitoring gradually becomes more than a technical practice - it becomes part of collaboratively building better solutions.

The Frontend Engineer as a Strategic Partner

All of these changes naturally lead to a transformation in the role of the Frontend engineer - from someone who implements predefined decisions to someone who actively helps shape them.

That includes:

• challenging unnecessary complexity

• proposing simpler and more sustainable solutions

• evaluating long-term impact on the system

• thinking about how success will be measured

Sometimes this leads to longer and more detailed discussions. Sometimes it means slowing decisions down.

But the goal remains the same: making better-informed choices.

This Is not a Formula - It’s Experience

This shift does not come from following a perfect process or adopting a universal methodology. It comes from accumulated experience - from real situations where solutions that initially seemed correct failed to produce the best outcome in practice.

And the process never really stops.

Every feature requires finding the right balance between business value, technical complexity, product evolution, and long-term maintenance cost.

There are no universal answers. But there are more informed ones.

Because this is where business goals meet the real user experience - and that is exactly where Frontend engineers create the greatest impact.

Not simply by executing solutions, but by actively shaping them.

And that is when the result does more than just work - it actually makes sense.

The post The Evolution of Frontend: From Execution to Strategic Contribution  first appeared on Delasport.

Toronto, Canada – May 13, 2026 - Delasport continues to strengthen its position in the Canadian regulated market, now powering three live brands in Ontario while preparing for further expansion into Alberta as the province moves toward opening its regulated online gaming market. 

Delasport’s technology is currently live in Ontario with TitanPlay.ca, Maverick Games, and Betnova.ca. The company provides a combination of full turnkey platform solutions of Casino, Sport, Player Account Management and Managed Services as well as its high-performance Sportsbook iFrame technology. This enables operators to launch quickly while delivering a premium user experience tailored to the Canadian audience. 

With Ontario continuing to establish itself as one of North America’s most competitive regulated markets, Delasport’s growing local presence reflects the company’s long-term commitment to Canada and its confidence in the market’s continued evolution. 

“Ontario is a strategically important market for us, and it has already proven to be a strong success story,” said Oren Cohen Shwartz, CEO of Delasport. “Seeing multiple brands successfully operating on our technology and services demonstrates the strength of our platform in acquiring and retaining players in Ontario. We’re excited to continue this momentum as we prepare for Alberta.” 

As part of its next phase of Canadian growth, Delasport has officially applied for Alberta’s upcoming B2B licensing framework and is already preparing to go live with a partner operator once the market opens. 

The company’s Canadian momentum is further supported by its mobile-first approach. TitanPlay’s iOS application is already available on the Apple App Store for users in Ontario, delivering a seamless casino and sportsbook experience powered by Delasport technology.  

Delasport’s platform in Canada includes a wide range of personalization and engagement tools designed to enhance user retention and entertainment value.  

The company has continued to position itself as one of the industry’s leading providers in regulated markets worldwide, with a strong focus on scalable technology, localization, compliance, and player-centric innovation. 

About Delasport 

Delasport is a leading global iGaming software supplier delivering sportsbook, casino, and player account management solutions for regulated markets worldwide. Known for its personalization technology and engagement-focused products, Delasport powers operators across Europe, North America, Latin America, and Africa with scalable solutions designed to drive retention and long-term growth. 

The post Delasport Accelerates Canadian Growth  first appeared on Delasport.

In the world of sports betting, Quality assurance plays a critical role by ensuring that betting platforms operate accurately, reliably and securely. These systems operate in real time and high volume transactions. An error can lead to regulatory issues, financial losses and loss of user trust. Product quality is often measured in seconds and split-second decisions. Behind the stability of such systems are the QA teams who help maintain stability, fairness and smooth user experience for betters. 

Working in such an environment builds skills and a mindset that extend beyond a specific role. Whether it’s managing markets or ensuring product quality, the ability to quickly assess risk, make precise decisions, and understand the consequences of every action is equally critical. This similarity in mindset is what enables a seamless transition from sports betting to Quality Assurance. 

Ivan Totev’s career is a strong example of this path - now Head of Quality Assurance in Delasport’s Technical Department, he has been with the company for nearly four years. His professional journey began in the sports department working in a dynamic environment, analyzing data and collaborating within a team. Today, he applies that experience in building strong testing processes, mentoring QA members and ensuring high standards throughout the development lifecycle. With a focus on collaboration, efficiency and continuous improvement, Ivan and his team help deliver stable, high-quality solutions while supporting the team in meeting both technical and business goals. 

You started your career as a Risk Analyst. What made you pursue a career change toward Quality Assurance? 

I started my career as a Risk Analyst, but my interest in the iGaming industry began much earlier. Prior to that, I worked at a casino, and that’s when I realized that what fascinated me the most wasn’t the betting itself, but how the system works “behind the scenes.”

I was never a typical customer. I was always curious about how the games were designed, how the odds were calculated, how the software tracked every bet, and the ways in which a single mistake can impact both the customer and the business.

As a Risk Analyst, I began to understand the product much more deeply. Over time, I realized that my true passion was not in managing risk, markets, or odds, but in preventing problems before they even reach the customer.

The Quality Assurance role gave me exactly that opportunity by developing a strong eye for detail and a deep understanding of how systems and processes can fail. In that sense, the transition to Quality Assurance felt completely natural.

It’s a bit like moving from being a player on the field to becoming the coach - because that’s where you start to see the whole picture.

How did your experience as a Risk Analyst help you understand the product, customer needs, and business logic? 

Both professions share many similarities. You need to think quickly and logically, anticipate possible scenarios, and be able to assess risks and potential consequences.

My experience as a Risk Analyst helped me understand the product at a level that colleagues from other departments often don’t reach. I understand what customers want because I always asked myself what I would miss if I were in their position. From there, the business logic began to fall into place naturally.

Which skills developed as a Risk Analyst were most beneficial when transitioning to software testing? 

My experience as an analyst provided a strong foundation for testing, particularly through skills like analytical thinking, data analysis, attention to detail, and risk assessment.

As a Risk Analyst, I worked with huge volumes of data in real time - statistics, odds, risk indicators, and much more. The environment is extremely dynamic, with constant changes in events, and my reaction often had to be immediate.

In Quality Assurance, when you test live events, you don’t have the luxury of taking your time to think things through. My analyst experience prepared me well for exactly these kinds of scenarios.

How did the transition from Junior Manual QA to a leadership position happen?  

There wasn’t a single “magic moment.” The transition didn’t happen overnight - it was the result of consistent effort, leadership and taking on responsibilities beyond my role, asking a lot of questions, and looking for solutions instead of waiting for instructions. Over time, this helped me build confidence and gain a broader understanding of both the role and the processes.

What kind of challenges did you face early in your career, and how did you overcome them?  

In the beginning, the biggest challenge was not having a clear understanding of what the Quality Assurance role looks like in a real working environment. One of the challenges I faced was adapting from a primarily analytical position to a more technical, hands on role.

I was entering a new profession and was still building an understanding of expectations, responsibilities, and my place in the decision-making process.

Over time, I also realized that the role often remains on the periphery, which can sometimes lead to certain problems being underestimated or postponed. What helped me adapt faster was my strong understanding of the product and my willingness to actively participate in processes.

What advice would you give for young professionals who want to grow in Quality Assurance? 

The most important thing is to understand the product in depth, not just from a user perspective but also how it is built and maintained. It is crucial to take time to learn the tools, frameworks and methodologies used in QA.

They should ask questions, look for the reasoning behind requirements, and not be afraid to express well-argued opinions. Quality Assurance is a role that requires problem solving, consistent attention to detail and a proactive attitude. It is for people who take responsibility and understand their impact on the final outcome.

What principles do you follow when building an effective team? 

For me, an effective team is not built around tools, but around mindset. I focus on three core principles: clarity, collaboration and continuous improvement.

At the core lies a strong understanding of the product and the business - not simply completing tasks. A QA specialist who doesn’t understand why a particular feature is important will struggle to prioritize correctly.

Another key principle is clearly defined responsibility. In our team, there is no room for “this is not my problem.” Quality is a shared responsibility. In that sense, everyone must clearly understand their role and influence.

This creates confidence and independence within the team and eliminates the need for micromanagement.

How do you handle challenges and pressure in live betting systems? 

Live betting is, by definition, a high-intensity environment because everything happens in real time.

For me, preparation, task prioritization, and quick risk assessment are fundamental. My experience as an analyst has always helped me recognize critical situations early on and avoid wasting valuable time. I focus on assessing risks methodologically, making decisions based on data rather than impulse and preparing for multiple outcomes.

From a leadership perspective, I try to prevent that pressure from spreading to the team. My role is to remove the ‘noise’, define priorities, and maintain control of the situation. This allows my team to stay focused and effective without panic.

What is the role of a Quality Assurance leader when implementing new technologies, AI, or automation? 

New technologies should not create dependency or resistance to change within the Quality Assurance department. Instead, they should shift focus toward higher-value work. 

The real question isn’t about adopting new technologies, tools, or automation- it is about solving real problems. Without alignment with the product, even AI and automation add little value. 

My responsibility is to identify where automation delivers the greatest value and to adopt AI and new technologies in ways that enhance product quality and team efficiency. My focus is on stability and early issue detection, rather than simply increasing the number of automated tests. 

How do you see the development of Quality Assurance roles in sports betting over the next five years?

In my opinion, Quality Assurance will become much more integrated with both product and business. It will become increasingly strategic and technologically advanced.

Traditionally, QA has often been seen as the final checkpoint before releasing a feature. In the future, QA specialists will be involved much earlier - even during the stage when requirements are being defined.

This will undoubtedly bring greater value to the business.

AI will certainly change the nature of our daily work by performing automate complex testing, predict system failures or errors, enable data driven decisions and support regulatory compliance. However, human judgment will remain just as important, especially in complex scenarios.

The post From Risk Analyst to Head of Quality Assurance  first appeared on Delasport.

Tihomir Kozich is one of them. 

Since joining Delasport in 2019 as a Sports Trader, Tihomir has built a career that spans both trading and product development. After more than four years in trading, he now leads several major initiatives, including the World Cup 2026 Hub - one of the company’s most strategic upcoming projects. 

In this interview, Tihomir shares how his trading background shaped his product thinking, what it takes to lead complex sportsbook initiatives, and how Delasport is preparing for one of the biggest events in global sports. 

You began your career at Delasport as a Sports Trader. How did your experience in trading shape your understanding of the sportsbook industry? 

Starting in Trading gave me a complete view of how the sportsbook ecosystem operates. As a trader, you are constantly monitoring markets, managing exposure, and reacting to real-time movements.

Over the years, I developed a deep understanding of the full sportsbook lifecycle - from event and market creation, pricing logic, and trend analysis to exposure management, settlement processes, and risk control across multiple sports. Working in such a dynamic environment required fast decision-making under pressure, strengthening both my analytical thinking and operational discipline.

Most importantly, trading teaches you how markets behave and how customers think. That knowledge becomes extremely valuable when working on product development because you understand the real dynamics behind every bet placed on the platform.

After more than four years in Trading, you moved into the Product team. What motivated that transition? 

After four and a half years in Trading, I felt it was the right time to take the next step in my professional development. 

At the same time, becoming a father of two also influenced how I think about long-term growth and responsibility. I wanted to challenge myself and broaden my perspective within the company. 

Moving into Product meant stepping outside my comfort zone. Seeing betting from a trader’s perspective is very different from building it from a product perspective. The transition came with a steep learning curve - understanding product processes, coordinating across teams, and shifting the mindset from operational execution to long-term product strategy. 

The first months were intense, but they accelerated my development significantly. My trading background also turned out to be a strong advantage because it allowed me to approach product decisions with a deep understanding of how markets function in practice. 

You’ve been involved in several major initiatives at Delasport. Which projects have been the most impactful in your journey? 

One important milestone was leading the UK integration project with Hollywoodbets. This initiative introduced me deeply to the horse racing domain, which is a unique vertical with its own operational and regulatory complexities. 

Managing the integration required close coordination across teams, technical implementation, and ensuring that the product met the specific requirements of the UK market. It was a challenging project that significantly expanded my sportsbook expertise, ultimately resulting in a smooth launch and a highly successful market entry. 

Another key initiative was the Bet Builder expansion for American sports, including American Football and Basketball. Bet Builders are one of the biggest innovations in modern sportsbook products, and contributing to their development for the US market was an important step for both the product and the company’s competitive positioning. The project was delivered with strong impact, enhancing user engagement and reinforcing Delasport’s position as a competitive and innovative provider in the US market. 

You are currently leading the World Cup 2026 Hub initiative. What makes this project so significant? 

The World Cup is the ultimate stress test for every sportsbook - technically, operationally, and commercially. 

Our goal is to build a centralized World Cup Hub that becomes the main destination for betting during the tournament. The focus is on reducing friction in the betting process, ensuring consistent odds availability during peak traffic, and introducing dynamic features such as Boosted offers and Bet Builders inside the hub. 

The ambition behind the project is significant. We are targeting a 15–20% increase in World Cup betting turnover compared to Euro 2024, with a large portion of bets expected to be placed directly through the World Cup Hub. 

This initiative combines product innovation, technical scalability, and commercial ambition, making it one of the most exciting projects currently underway at Delasport, and is set to directly enhance our operators’ success by driving higher engagement, improving retention, and unlocking new revenue opportunities. 

Your career path reflects strong internal growth within the company. What has helped you develop at Delasport? 

One of the most important factors has been the environment of trust and responsibility. 

When people are given the opportunity to take ownership and grow internally, it builds confidence and accountability over time. Being able to evolve through different roles within the company has allowed me to continuously expand my perspective and skill set. 

It also demonstrates the value of long-term development within an organization. 

What motivates you most in your work today? 

What motivates me most is the opportunity to build products that create real impact at scale. 

The sportsbook industry is extremely dynamic, and there is always room for innovation and improvement. Being part of that process and contributing to major initiatives like the World Cup Hub is incredibly rewarding. 

At the same time, being a father reminds me of the importance of long-term thinking - both personally and professionally. Growth, responsibility, and continuous development are values that guide me every day. 

The post From Trading to Product Excellence: Driving Innovation Ahead of World Cup 2026  first appeared on Delasport.

Why did you decide to move the company to a BigQuery-based data lakehouse architecture?

Yasen: We chose to move because our legacy setup had reached its limits. It required significant manual work, lacked proper governance, and made complex analytics or machine learning difficult to scale. BigQuery gives us a fully managed foundation that removes infrastructure overhead and lets us focus on building data products rather than maintaining systems.

A key driver for us was the ability to decouple storage from compute, allowing each to scale independently. That flexibility is essential as our data volumes grow, and our analytics needs become more dynamic. We can scale processing power when we need heavy computation, without over-provisioning storage, and vice versa.

This transformation also strengthens our ability to build trust in data across executive leadership. With a reliable, well-governed platform, leaders can make decisions with confidence, knowing the data is consistent, timely, and high-quality.

Ultimately, this move supports our long-term strategy around advanced analytics, AI, and automation, where systems can proactively generate insights or propose actions. We wanted a platform that is fast, reliable, easy to govern, and capable of powering everything from operational dashboards to machine learning. BigQuery delivers all of that in a single ecosystem.

For people who may not be familiar with a lakehouse architecture, how would you describe what you’re building?

Yasen: A lakehouse combines the best parts of a data lake and a data warehouse in one unified environment for raw data, processed transformations, analytics, and machine learning. Raw data lands in a central location, then moves through refined layers, creating a platform where data engineers, analysts, and AI engineers work together seamlessly within the same governance framework, with full lineage tracking and version-controlled pipelines. This setup makes data more accessible, reliable, and ready for insights across the business.

What made BigQuery the right platform for this transformation?

Yasen: BigQuery removes most operational burden that slows teams down. There are no servers to manage, no capacity planning, and no complicated scaling policies. It handles massive datasets with ease, provides fast SQL performance, and integrates natively with governance, transformations, and ML tools. This also makes it cost-efficient, since we only pay for what we use, without the overhead of managing infrastructure.

It also reduces dependency on rare expert profiles. Not every organization can easily hire senior data engineers with deep infrastructure knowledge. We wanted a platform where analysts can build dashboards and explore data without needing specialized engineers beside them. BigQuery helps us make the platform accessible, scalable, and future-proof.

Can you walk us through the core components of your architecture?

Yasen: We designed the architecture around simplicity, clarity, and ease of onboarding. Data is extracted from production systems and first lands in a centralized storage layer. From there, it moves into BigQuery as structured or semi-structured raw tables.

Transformations run entirely within BigQuery using GCP-native ELT tooling, which provides automated testing, modular development, environment separation, and clean dependency management. Versioning is maintained through a centralized system that tracks all changes and deployments.

The platform operates across distinct but connected layers: a data lake for raw and lightly processed data, a dedicated testing environment for validating new pipelines and models, a warehouse optimized for analytics and dashboards, and a feature store that supports machine learning workloads. Each layer is designed to flow naturally into the next and to support clear development and operational practices.

Pipelines follow production-grade orchestration processes aligned with our “pipelines as production software” mindset. This ensures reliability, maintainability, and strong observability. A monitoring system tracks execution and triggers alerts for any failures or anomalies, enabling timely visibility and proactive maintenance. The entire architecture follows the principles of the Google Cloud Well-Architected Framework to ensure reliability, performance, security, and operational excellence.

Security and governance are strict: everything is documented, tracked, and controlled so new team members can onboard confidently and safely. And while the current team is relatively smaller, every process and architectural choice is designed to scale efficiently as we grow.

Phase 1 of the project has been completed. What did that include?

Yasen: Phase 1 focused on moving a major part of our business-critical pipelines into the new architecture and establishing the full back-end foundation. We implemented consistent development processes, creating multiple environments with automated deployments, and embedding quality checks throughout the pipelines.

We are not just migrating. We are rebuilding and enriching data models so end-users - analysts and BI teams - can work more efficiently, with fewer joins and faster queries. This sets the stage to shift focus from maintenance to generating real business value.

Phase 1 laid the groundwork for reliable, maintainable, and scalable data operations that can support future growth and more advanced analytics initiatives.

How do you ensure governance, lineage, and data quality across the platform?

Yasen: Governance is built in from the start. We use centralized cataloging and policy enforcement tools to manage data consistently across the platform. Transformations include automated quality checks, and lineage is tracked automatically so anyone can see where a dataset comes from and how it was produced.

Access is controlled through a strict role-based permission model, and documentation is kept thorough and up to date. We also leverage AI assistants to support tasks like writing documentation and assisting with orchestration coding - always following strict security rules and never accessing sensitive data.

Quality assurance is a top priority. Mistakes early on could be very costly down the line, so we enforce strict standards to ensure the data is accurate, reliable, and trustworthy.

Cost control is always a concern in cloud analytics. How are you approaching BigQuery cost optimization?

Yasen: BigQuery can be very cost-efficient when used thoughtfully. We always tailor optimizations to the intended use of each dataset. For example, tables in the lake are designed for transformation-heavy workloads, as the ELT pipelines are the primary users. In contrast, tables in the warehouse and the feature store are optimized for analytics queries, dashboards, and machine learning models, which are the main consumers in those layers.

To achieve this, we apply a range of cost-efficient design strategies, including partitioning, clustering, incremental processing, and table denormalization. We also use slot reservations for predictable compute needs, materialized views for frequently accessed logic, and query caching to avoid unnecessary rescans.

The goal is to provide teams with a fast, responsive environment while controlling spending - so analysts and ML practitioners can explore and query data confidently without scanning unnecessary terabytes.

What challenges did you encounter during the transition?

Yasen: One of the main challenges is keeping the business running smoothly while modernizing the data platform. This means we must maintain the legacy system even as we build the new BigQuery-based architecture. To manage this, we follow a dual-track delivery model: focusing on building a robust back-end foundation, while maintaining existing developments and planning for the next phase of rebuilding data feeds, application integrations, and business dashboards.

Compliance and regulatory requirements are also critical – our solutions must meet all standards while continuing to deliver reliable service.

Manpower is another challenge. We intentionally develop everything in-house because deep business domain knowledge is essential for designing an architecture that truly fits our needs. Contractors can help, but they often lack the nuanced understanding and focus required for an optimal solution.

What role does AI play in your long-term roadmap?

Yasen: AI is central to our vision. The lakehouse provides the foundation for machine learning pipelines, from model training to deployment. Our vision is data-centric rather than model-centric: even the best algorithms won’t deliver value if the underlying data isn’t clean, structured, and ready for use.

We have several ML models planned for the near term, including personalized CRM journeys, fraud preventions, affiliate traffic optimizations, customer segmentations, churn prediction, early VIP client detection, and product recommendation engines.

Longer term, our vision is agentic BI - systems that proactively detect patterns, generate insights, propose decisions, and even automate actions across domains. Most data teams in the industry are still reactive, constantly juggling tasks and priorities with little time to step back, analyze deeply, or see the bigger picture. We want to break that cycle. Everything we are building today - from governance to architecture - is designed to move us toward a future where insights are not just delivered but anticipated.

Final question. What excites you most about this transformation?

Yasen: What excites me most is the shift from a reactive, maintenance-heavy setup to a proactive, value-driven platform. We’re building an environment that scales naturally, automates routine tasks, and enables advanced analytics and AI.

But it’s more than just modernizing infrastructure. We’re empowering analysts, reducing dependency on rare technical specialists, and creating a platform where teams can focus on insight, innovation, and impact instead of firefighting. This transformation will fundamentally change how the company works with data and unlock value for years to come.

The post Modernizing Our Data Platform: Building a BigQuery Lakehouse first appeared on Delasport.

Today, we introduce you to Tereza Terzieva, Head of Games R&D, who has been part of Delasport for nearly five years. With a strong background in software development and a career path shaped from an early age, Tereza is one of the standout leaders within the company.

In an environment where technical roles have traditionally been dominated by men, Tereza successfully leads the only team at Delasport fully dedicated to casino development. She passionately believes that true success comes from working with ownership and responsibility - treating what you build as your own and always aiming for long-term solutions.

In the following interview, Tereza shares more about her professional journey and her approach to leading technical teams.

After a long journey in software development and growth within Delasport, you are now Head of Games R&D. How does your technical background shape your leadership style?

My technical background keeps me grounded. Having a deep understanding of the technologies and components we work with helps me fully grasp the real tools the team uses and the challenges they face on a daily basis. As a result, my decisions are never abstract - they are rooted in practice and reality.

Equally important, this background has shaped the way I think. I have always been drawn to complex problems and finding solutions - not only by writing code, but also in managing people and projects. Every situation requires a different approach, balance, and long-term thinking. For me, leadership emerges precisely there - in understanding context, supporting people, and taking responsibility for the product. This mindset naturally led me from development into management and continues to define how I lead my team today.

Looking back on your first steps as a leader, what surprised you most about managing people?

For a long time, my path was purely technical rather than managerial. Logic and unsolvable problems were always my passion, and I never imagined myself stepping into a leadership role. Over time, however, I realized that this very passion helps me in management as well.

It teaches me to consider many different factors, to be patient, and to approach complex situations calmly. In the end, people management also involves “problems to solve” - the difference is that the solutions require more attention, understanding, and balance.

As a female leader in a traditionally male-dominated technical environment, have you ever felt that expectations were higher and that you had to prove yourself more?

Yes - and honestly, I liked it. Challenges motivate me. I have never seen this as an obstacle. I have been surrounded by mostly male company since childhood, which helped me become direct, confident, and calm in such environments.

I combine determination and drive with patience and empathy. This balance helps me build trust and work effectively with the people around me.

What do you believe is the key difference between a manager and a true leader in the tech industry?

For me, the difference lies in attitude and example. A good manager oversees processes and tasks. A true leader creates an environment where people want to give their best.

Leadership means walking alongside your team. When challenges arise - you face them together. When success comes - you give credit to those who achieved it. Trust is the foundation of everything, and when it exists, the team becomes resilient and united.

My greatest achievement is that my team is strong, cohesive, and stable - people enjoy coming to work and they choose to stay.

How do you make decisions when there is a conflict between the “ideal technical solution” and genuine business constraints?

In practice, compromises are often necessary for several reasons. What matters to me is that decisions are informed and well thought out. This means gathering enough information, listening to different perspectives, and evaluating the long-term impact.

I do not believe it is a weakness to consult more experienced colleagues - on the contrary, it shows maturity and responsibility. When we work as one, we can find the best possible balance between technology and business.

How do you balance working with team members who have diverse levels of experience?

Balance comes through clear role distribution and constant communication. More experienced colleagues could share knowledge and mentor others, while newer team members receive support and space to grow.

It is important that everyone has time for focused work as well as collaboration. When people complement and support one another, the team grows naturally.

Your team has exceptionally low turnover. How do you motivate people to think long-term rather than about completing individual tasks?

I believe people stay where they feel part of something meaningful. Our team is built on support, open communication, and a clear development direction. People see purpose in what they do and know they have room to grow.

That is when staying becomes a natural choice, not just a decision.

Your team is distributed across different countries. What practices do you use to maintain clear and effective communication?

I rely on consistency and transparency. We have daily meetings where we discuss tasks, challenges, and solutions. Communication happens on shared channels, so everyone has access and clarity.

We also work on common initiatives, which help us stay connected and maintain a powerful sense of being one team - even when we are not in the same location.

What advice would you give to people taking their first steps as technical leaders?

I would advise them not to rush into proving themselves as leaders. In my experience, that rarely works and can even push people away.

Leadership is built through actions, not titles - through how you communicate, make decisions, and show your team they can rely on you. It is important to stay close to the team and to the real work - to understand the challenges people face and where support is needed.

Share your knowledge instead of keeping it to yourself and lead by example. Trust is built through dedication, time, consistency, and honesty. When people feel that there is no need to impose authority, leadership happens naturally.

The post From Code to Leadership: Building Strong Tech Teams at Delasport first appeared on Delasport.