The event-driven engineering startup Quix Analytics Ltd. today announced that it raised $12.9 million in new funding to provide real-time data streaming for applications.
The Series A funding round was led by MMC Ventures with participation from existing investors Project A Ventures and Passion Capital.
Using Quix’s platform, application developers can get access to data in real time with a high-performance engine that delivers actionable insights to processed data immediately by providing modular, scalable infrastructure. It does so by providing a toolkit that developers would have to build in-house instead.
“Many companies are struggling to combine raw technologies like Kafka into real-time data capabilities,” said Mike Rosam, co-founder of Quix. “Whilst this is possible for the world’s leading tech companies, most struggle to find the talent and time to deliver real-time applications.”
Applications for real-time data ingestion include finance, e-commerce, telecommunications, data engineering, development and operations for mobile apps and gaming and more. Examples include improving user experience with stream processing for gaming apps by detecting poor performance quicker or catching cheaters and booting them, the same technology can be used by telecommunications operators to detect degraded data routes and fix them.
The founders of Quix worked as Formula 1 engineers who themselves used the power of data stream processing to make real-time decisions where split-second timing was critically important. With this experience at British luxury automotive manufacturer McLaren Technology, Rosam and Quix’s other founders created the platform to solve the same challenges they saw cropping up in the industry today.
The platform itself is modular in design and cloud agnostic, as a result, Quix customers can connect it with whatever technology or infrastructure they already build on and do not need to worry about lock-in. It also uses Python as its core programming language, which has a broad library of code for analytics, machine learning and automation use cases.
Rosam said that this new funding would go towards growing the company’s team in order to expand the product, partnerships, developer community and open-source initiatives.
“This new capital will fuel our mission to simplify event-driven data engineering so that more companies can build modern data-intensive apps,” Rosam said.