Track, troubleshoot and optimize your fleet

Predict arrival times. Avoid costly delays. From logistics to surge pricing, stream processing is transforming urban mobility. Learn what real-time automation can do for you.

Multiple scooters parked outside.

What can you build with Quix?

Asset tracking

Some of the most valuable assets in your business are deployed far beyond warehouse walls. Monitor your fleet to produce real-time visualizations for operational teams. Event-based notifications alert you to traffic, weather and delays. Automate responses for fulfillment timelines and trigger messages to downstream customers.

Route optimization

The data you need to plan and adapt your mobility solution is out there — it’s just stuck in silos. Quix unifies data in streams that are relevant to a delivery or asset. Use ML to calculate the most efficient journey, accounting for traffic and demand. Make smarter loading decisions, weigh speed against cost factors, and even calculate CO2 emissions.

Arrival prediction

Customers hate waiting. But there’s a proven technique to reduce frustration: status updates. Stream processing helps you share credible, precise arrival times with your customers. This reduces delivery wait time to improve driver productivity. Use ML to compare predicted progress against actual progress to identify wasted minutes.

Operational efficiency

Your customer service hub is only as good as their information. When data is locked into historical reports, operators can merely react to problems. Quix gives service leaders up-to-the-millisecond data to make better decisions. Layer in ML and automation for decision support and troubleshooting.

Surge pricing

The busiest times don’t have to be painful — they can be more profitable with surge pricing, while also dialing back some peak demand. Uber uses stream processing to implement surge pricing and entice more drivers to work during peak periods. Quix makes it easy for companies to predict and respond to peaks and dynamically change pricing or incentives.

Multiple scooters parked outside.

Changing the mobility industry

Quix was founded by Formula 1 engineers who live and breathe speed and efficiency. They engineered a platform to harness the power of live data — and the mobility industry is at the forefront of the streaming data revolution.

By understanding your assets, changing conditions, and demand peaks, you’re ready to outperform the competition. Quix makes it possible for mobility companies of any size to better operate their fleets.

Ready to learn more? Read our case study that empowers a single data scientist to accurately predict fleet availability, taking into account weather and demand fluctuations.

Graphic showing Quix Streams windowing code

Introducing Streaming DataFrames

Learn how Streaming DataFrames can simplify real-time data processing in Python with a familiar DataFrame approach.
Graphic showing Quix Streams windowing code
Words by
Tomáš Neubauer
Featured image for the "Navigating stateful stream processing" post published on the Quix blog
Industry insights

Navigating stateful stream processing

Discover what sets stateful stream processing apart from stateless processing and read about its related concepts, challenges and use cases.
Featured image for the "Navigating stateful stream processing" post published on the Quix blog
Words by
Tim Sawicki
windowing in stream processing
Industry insights

A guide to windowing in stream processing

Explore streaming windows (including tumbling, sliding and hopping windows) and learn about windowing benefits, use cases and technologies.
windowing in stream processing
Words by
Daniil Gusev

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.