Time is of the essence. An idiom whose adherence to is critical to ensure retention figures are met, and that dreaded churn rates are kept to a minimum. 

This formed the basis of a renewed Flows and Golden Whale alliance, with a real-time data orchestration loop designed to enable operators to have meaningful interactions with customers, and therefore drive smarter and swifter user engagement.

In conversation with SBC News, Malou Neguembor, Director of Client Success at Flows, and Thomas Kolbabek, Golden Whale CTO, unpack the critical factors of this process, and the overarching benefits to be achieved.

SBC News: Can you walk us through how the data flow between Flows and Golden Whale actually works? From orchestration to prediction to automation?
 

Malou Neguembor, Director of Client Success at Flows

Malou Neguembo: Flows can take data from any source, in any shape and structure, such as Kafka, RabbitMQ, webhooks, or APIs, and automatically understand its structure, making it immediately ready for use in our no-code Flow builder. 

This allows our clients to quickly shape and route the data wherever it’s needed, including platforms like Golden Whale. Within Flows, we also enrich the data by pulling in extra details from other third-party sources that the client uses. 

After enrichment, we orchestrate the data and deliver it directly to Golden Whale, formatted exactly how they need it for seamless predictions and automation – all done directly through our intuitive, no-code interface by anyone – no developers needed.

Thomas Kolbabek: Golden Whale’s Foundation platform features a unique no-integration approach, connecting seamlessly to systems already in place for data access – a perfect match with Flows. 

Foundation combines the continuously enriched data provided by Flows with historic data as a basis for machine learning. We cover deep understanding of gaming mechanics, operation and user behaviour and mold this into all stages of the ML life cycle, from data engineering to ML model training, validation and monitoring.  

Our holistic approach allows us to turn data points provided by Flows into personalised predictions and recommendations for each player. These are fed back to Flows as actionable signals and triggers, enabling automation and supporting decision making. 

SBCN: What’s the benefit to operators of having this two-way integration between data orchestration and predictive analytics?

Thomas Kolbabek, Golden Whale CTO

TK: As soon as the first prediction or recommendation is used in an operation the operation evolves constantly. Player experience and behaviour changes as more players can be retained and bonuses or incentives are distributed more specifically, avoiding bonus abuse. 

With a closed-loop, two-way integration, our ML models can continuously adjust and react to shifts in player behaviour and market conditions. One-off or old/stale ML models lack that distinct advantage and deteriorate over time, especially as the underlying operation is extended by adding new products or offers.  

Golden Whale has coined the term “LOOPS” from the very beginning, emphasising the importance of processing data, predictions and subsequent actions in a closed-loop system to continuously learn, adapt and optimise effectively.

MN: The two-way integration between Flows and Golden Whale allows operators to move from reactive to proactive engagement in real-time. Flows orchestrates live data streams and additional data via 3rd party APIs, and sends them to Golden Whale for analysis. 

As predictions are returned as new triggers to Flows, they can be built on for automations like tailored offers, risk alerts, anti-churn or retention actions, without manual input or extra development needed. All are already connected to both internal and external communication tools such as Slack, Teams, Telegram, CRM tools and reactivation partners such as Enteractive and Dynamic Messaging. 

This real-time loop empowers operators to anticipate player behaviour and act at the moment it matters most, driving smarter engagement, better retention, and reduced operational effort as all parts of the workflow with both internal and external communication, as well as dashboards and alerts, can be automated.

SBCN: Real-time seems to be the keyword here. How are you working together to ensure insights and actions happen without delay?

MN: Real-time is absolutely at the core of this integration. Flows is built to handle live data streams and trigger instant actions the moment conditions are met. 

As soon as player data hits Flows, it’s enriched, orchestrated, and sent to Golden Whale without delay. Their predictions are then returned as new triggers into Flows, where predefined workflows are ready to act – no lag, no manual steps. 

Special triggers are also sent to Flows if Golden Whale detects a change in a player’s predictions, such as churn risk increase.

The flexibility of Flows means that any new incoming data event or third-party integration can be quickly added to the loop, instantly expanding the dataset Golden Whale uses for predictions and continuously improving the quality and precision of insights.

TK: Real-time data processing and prediction delivery has been built into our platform Foundation from its inception, which again pairs perfectly with the live data streaming capability of Flows. 

Our ML model execution is directly linked to the data stream provided, enabling us to run real-time calculation of predictions on-stream, which are immediately provided back to Flows.  

While reacting to triggers and gaming activity is key, Foundation equally provides updated predictions based on events and activity that fail to happen as player behaviour shifts or stalls unexpectedly, and as soon as models detect a possible shift. 

Both parts contribute to providing in-time decision support for operations, enabling operators to interact with players while they are still engaged and more easily reachable.

SBCN: What makes Flows well-suited to handle multiple streams of data orchestration at once, and how does that impact performance for clients?

MN: Flows is designed from the ground up for very high-volume, real-time data orchestration. Our event-driven architecture allows us to handle multiple data streams simultaneously, whether from platforms, tools, or custom sources—without compromising speed or reliability.

For operators, this means no bottlenecks. Flows scales with their data, ensuring performance remains smooth even as complexity grows. The result is a system that adapts in real time, enabling faster decisions, richer player insights, and truly seamless automation at scale.

SBCN: What types of predictions are most powerful when they can be acted on in real time, and how does Flows help make that happen?

TK: We see the most impactful real-time use cases for predictions that deepen the engagement of the player with a platform or product. 

This includes very ‘Early Value Prediction’ to tailor the onboarding experience for new users, ‘Session Churn Risk Prediction’ while players are still in-play to facilitate real-time-retention, tailoring content dynamically as players navigate a platform by recommending games, bets and products and to trigger and adjust gamification tools, challenges and tournaments when a player is most likely to appreciate them.  

Our platform Foundation can orchestrate the different tools of engagement and dynamically calibrate its ML/AI-models to the very specific setup at operator level. 

Flows is key in this process by helping to connect the different ways of customer interaction to the central decision-making module from Golden Whale and by providing a consistent and high-quality stream of data points from anywhere in the operation in real-time and regardless of the original data source.

SBCN: How do you see the value of your predictive outputs increasing when they’re plugged straight back into an automation layer like Flows?

TK: Having predictions not only at the fingertips of an operator but additionally available in a highly flexible, yet easy to configure automation tool like Flows multiplies the effectiveness and thus value of predictions on multiple dimensions.  

Operators can connect predictions to business processes with a fraction of the lead time typically needed in more rigid environments.  

Implemented Flows automate these processes to run 24/7 in real-time as opposed to environments relying on schedules and synchronisations.

Orchestrating the delivery of predictions to all connected systems enables our customers to empower every part of their gaming platform, including CRMs, gamification tools, PAMs, CDPs and many others. 

Flows further enables us to automate communication of key events to teams and stakeholders without the need to set up reports or other more complex means of communication, making our predictions available continuously to both people and systems.

SBCN: Once data comes back from Golden Whale, what kinds of automated actions can operators set up instantly in Flows?

MN: Once Golden Whale returns predictive insights as Flow triggers, operators can build Flows to instantly automate actions based on those predictions. This could include sending personalised offers or bonuses, flagging high-risk behaviour for compliance review, triggering a retention campaign, or adjusting CRM segmentation in real-time.

Because Flows is no-code and fully customisable, operators can build logic that fits their exact strategy, whether it’s acting on churn risk, VIP potential, or anomalous behaviour—ensuring the right action happens automatically, at the right moment, without any manual input.

SBCN: How will this predictive loop change the way your clients approach player engagement or campaign setup?

MN: Instead of building static campaigns based on past behaviour segmentation, they can now create dynamic, real-time strategies that respond to what a player is likely to do next.

This means campaigns can be continuously optimised, automatically triggering the right message, bonus, or action based on predictive signals from Golden Whale. 

It shifts the focus from manual planning and guesswork to intelligent automation, where every player touchpoint is timely, relevant, and data-driven. The result is smarter engagement, stronger retention, and significantly less time spent on campaign setup and management.

SBCN: From Golden Whale’s perspective, what’s been the impact of having such fast, clean data orchestration coming in from Flows?

TK: Partnering with Flows and receiving orchestrated data we can rely on enables us at Golden Whale to focus on delivering the best possible orchestration of ML models for the operation of our customers. 

As Flows’ event-driven data points are more granular than pre-aggregated data sets, which in turn enables us to provide a wider range of predictions and recommendations. 

We have seen significantly shorter lead-times for continuous data access and prediction delivery while remaining flexible to receive data points that are unique to an operation and as such unique to the experience of players.

 

 

 

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