Make digital magic happen with live customer data

You already invest in a wealth of customer data, so why dump it into a data lake or CDP? Stream processing enables instant personalization, with recommendations to drive up cart values and reduce churn.

What can you build with Quix?


Use real-time data to personalize experiences. Combine live data such as browsing behavior with purchase history and preferences to deliver the right offer at the right time. Now you can use ML to recognize when behavior matches certain patterns and automate offers to influence conversion rate and ACV.


Should you recommend sale or full-price items? One-time or subscription? Seasonal merchandise or standbys? Quix helps retailers make smarter product recommendations. Spot the signals and decision points in customer behavior in real time, then automatically generate targeted recommendations to best influence customers.

Fraud prevention

Customers expect near-instant purchase approval. But this creates massive exposure to fraud. Quix helps you communicate faster with banking services and add your own fraud detection layers. It can also detect fraud associated with gift cards, coupon codes, loyalty rewards, and multiple user accounts. That’s the power of ML paired with real-time data.

Customer retention

Real-time data helps you better understand your product lifecycle, using ML to detect signals that a customer is likely to churn. Use this data to automate “surprise and delight” moments for your customers, such as sending an unexpected gift shortly before a subscription renewal. You can also support customer service by detecting problems early.

Reduce latency

The data load and query time needed for personalized experiences severely slows digital products. But customers won’t tolerate waiting for pages to load — latency is the new outage. Quix helps you build lightning-fast applications powered by real-time data, to immediately serve high-value content, wrapped in a customized experience.

Person browsing on his laptop.

Changing the ecommerce industry

Quix was founded by Formula 1 engineers to deliver the power of real-time data to all industries. Quix brings order to the chaos of customer data sprinkled across business silos for both historical and live data streams.

No matter how high the volume and velocity of customer data you collect, Quix can unify it in the context that matters most: a single customer.

As leading ecommerce brands embrace a digital-first approach, they’re rapidly embracing live data to deliver greater immediacy and personalization.

Ready to learn more? Chat with a friendly expert about what you can do with Quix.

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Apache Kafka vs. RabbitMQ: Comparing architectures, capabilities, and use cases

The main difference between them is that Kafka is an event streaming platform designed to ingest and process massive amounts of data, while RabbitMQ is a general-purpose message broker that supports flexible messaging patterns, multiple protocols, and complex routing.
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Apache Beam vs. Apache Spark: Big data processing solutions compared

The main difference between Spark and Beam is that the former enables you to both write and run data processing pipelines, while the latter allows you to write data processing pipelines, and then run them on various external execution environments (runners). But what are the other differences between Spark and Beam, and how are they similar?
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simplified diagram of a machine learning pipeline

The anatomy of a machine learning pipeline

Explore the characteristics, challenges, and benefits of machine learning pipelines, and read about the steps involved in training and deploying ML models to production.
simplified diagram of a machine learning pipeline
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Why the data pipeline is changing everything

Find out why analysts and market-watchers agree that traditional data processing must be replaced by stream processing. It’s happening now as innovators embrace new opportunities for greater personalization, automation and revenue.

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Quix Report cover.