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Quix raises $3.2M from Project A and others for its ‘Stream centric’ approach to data

Quix, a platform for Python developers working on streaming data, has secured a £2.3 Million ($3.2M)Seed funding round led by Project A Ventures in Germany, with participation from London’s Passion Capital and angel investors. The Quix Portal is also providing developers with a free subscription to a real-time data engineering platform. Quix attracted angel investors […]

Quix, a platform for Python developers working on streaming data, has secured a £2.3 Million ($3.2M)Seed funding round led by Project A Ventures in Germany, with participation from London’s Passion Capital and angel investors. The Quix Portal is also providing developers with a free subscription to a real-time data engineering platform.

Quix attracted angel investors including Frank Sagnier (CEO, Codemasters), Ian Hogarth (Co-author, State of AI Report), Chris Schagen (CMO, Contentful), and Michael Schrezenmaier (COO, Pipedrive).

Quix wants to change the way data is handled and processed from a database-centric approach to a ‘stream-centric’ approach, connecting machine learning models to real-time data streams. This is arguably the next paradigm in computing.

Use cases for Quix, it says, include developing electric vehicles, and fraud prevention in financial services. Some of its early customers are the NHS, Deloitte and McLaren.

Indeed, the founding team consists of former McLaren F1 engineers who are used to processing real-time data streams from the systems used by most Formula 1 teams.

Co-founder and CEO Michael Rosam said: “At Quix, we believe that it will soon be essential for every organization to automatically action data within milliseconds of it being created. Whether it’s personalizing digital experiences, developing electric vehicles, automating industrial machinery, deploying smart wearables in healthcare, or detecting financial fraud faster, the ability to run machine learning models on live data streams and immediately respond to rapidly changing environments is critical to delivering better experiences and outcomes to people.”

Over email he told me that Quix’s main advantage is that it allows developers to build streaming applications on Kafka without investing in cloud infrastructure first: “Uniquely, our API & SDK connects any Python code directly to the broker so that teams can run real-time machine learning models in-memory, reducing latency and cost compared to database-centric architectures.”

Quix is entering the data ecosystem alongside batch data processing platforms like Snowflake and Databricks, and event streaming platforms like Confluent, Materialize, and DBT. However, this ecosystem is very complementary with organizations usually combining multiple products into a production infrastructure based on the strengths of each proposition.

Sam Cash of Project A Ventures said: “Data streaming is the next paradigm in data architecture, given end-users accelerating demand for live, on-demand and personalized applications. The Quix team are leading the way in this market, by democratizing access to data streaming infrastructure, which until now has been the reserve of the largest companies.”

Malin Posern, Partner at Passion Capital commented: “The world today is generating unimaginable amounts of data from digital and physical activities. Businesses of all types and sizes will want to make use of their data in real-time in order to be competitive.”

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