Pathway, the female-led deeptech startup unlocking the power of real-time data, has raised a $4.5 million pre-seed round from early-stage investors Inovo Venture Partners and Market One Capital. Strategic angel investors include Roger Crook, the former Global CEO of DHL, and Lukasz Kaiser, co-author of Tensfor Flow and co-inventor of Transformers, now at OpenAI.

Pathway, founded in 2020, has made its machine learning platform free and open to all developers worldwide. "Previously the reserve of enterprise firms, Pathway's AI-powered framework brings key competitive advantages to businesses that rely on fast-moving streams of data from multiple sources. Not only does it enable them to apply machine learning and automated reasoning to all and every stream of data it receives in real time but it automatically takes care of data updates for the developer in a streaming architecture. With Pathway, instead of waiting 12 hours for a data pipeline to refresh, businesses get up-to-date results in less than a minute," says an official release.

Pathway has allowed industry leaders like DB Schenker and La Poste to analyse their entire transport operations and reduce latency – or time wasted waiting for results – by a factor of up to 900x, the release added.

"Pathway allows developers to resolve their data interpretation problems by creating a Python-based programming framework for transforming table-like data in real time whether that's time series data, IoT messages, event streams or graph models. Once a developer has programmed an algorithm in Pathway, it can be used in an application in a scalable, and flexible way. It can also be easily integrated with SQL databases or existing streaming solutions like Kafka, and they can be used directly with a reactive user frontend via API."

Zuzanna Stamirowska, Co-Founder and CEO, Pathway says: "Interpreting events data using machine learning is a challenging task as it is without having to worry about constantly changing and updating the data streams you're dealing with.

"With Pathway, developers can design their code logic to work in batch mode but deploy it in streaming mode. This is significant for all businesses, especially those that handle fast-moving data from multiple sources. This is why we're making our framework open and free for everyone to use."

Kaiser adds: "In machine learning, the key to success of a programming framework is how to combine usability with scalability. This was the axis of competition between Google's TensorFlow and Facebook's PyTorch during the deep learning revolution. Today, Pathway has taken into account the lessons learned during this battle of giants, and embedded them in the compiler of its real-time data processing framework."

Supply chains need to react to changes quickly, and companies need to be able to use data insights to take the right action, says Crook. "This is something that disruptions following the Covid pandemic and black swan events like the Suez Canal blockage have brutally brought to light."

Jan Chorowski, CTO, Pathway and former Google Brain says: "In the industry, analytics can be done the SQL way or the Python way. The problem with SQL is that it is not powerful enough for machine learning applications. And the problem with Python is that it offers a powerful data science stack but this stack just doesn't handle real-time data updates."

Sometimes, data transformation needs to be repeated (iterated) for as long as needed, Chorowski added. "Sometimes, especially in real-world enterprise cases, there is a human user in the loop who needs to manually introduce corrections to the input data, and see results in seconds. All such scenarios are taken care of by Pathway."

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