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Main article: Cambridge innovation capital

All topics: 2

Swim.ai raises $11M to bring real-time analytics to the edge

14:00 | 18 July

Once upon a time, it looked like cloud-based serviced would become the central hub for analyzing all IoT data. But it didn’t quite turn out that way because most IoT solutions simply generate too much data to do this effectively and the round-trip to the data center doesn’t work for applications that have to react in real time. Hence the advent of edge computing, which is spawing its own ecosystem of startups.

Among those is Swim.ai, which today announced that it has raised an $11 million Series B funding round let by Cambridge Innovation Capital, with participation from Silver Creek Ventures and Harris Barton Asset Management. The round also included a strategic investment from Arm, the chip design firm you may still remember as ARM (but don’t write it like that or their PR department will promptly email you). This brings the company’s total funding to about $18 million.

Swim.ai has an interesting take on edge computing. The company’s SWIM EDX product combines both local data processing and analytics with local machine learning. In a traditional approach, the edge devices collect the data, maybe perform some basic operations against the data to bring down the bandwidth cost and then ship it to the cloud where the hard work is done and where, if you are doing machine learning, the models are trained. Swim.ai argues that this doesn’t work for applications that need to respond in real time. Swim.ai, however, performs the model training on the edge device itself by pulling in data from all connected devices. It then builds a digital twin for each one of these devices and uses that to self-train its models based on this data.

“Demand for the EDX software is rapidly increasing, driven by our software’s unique ability to analyze and reduce data, share new insights instantly peer-to-peer – locally at the ‘edge’ on existing equipment. Efficiently processing edge data and enabling insights to be easily created and delivered with the lowest latency are critical needs for any organization,” said Rusty Cumpston, co-founder and CEO of Swim.ai. “We are thrilled to partner with our new and existing investors who share our vision and look forward to shaping the future of real-time analytics at the edge.”

The company doesn’t disclose any current customers, but it is focusing its efforts on manufacturers, service providers and smart city solutions.

Swim.ai plans to use its new funding to launch a new R&D center in Cambridge, UK, expand its product development team and tackle new verticals and geographies with an expanded sales and marketing team.

 


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Undo gets $14M to scale to meet the software accountability challenge

14:47 | 16 July

Undo, a long time player in the debugging tools space, offering its program execution capture and replay technology to help others diagnose software failures, has closed a $14 million Series B round led by Cambridge Innovation Capital, the Cambridge, UK-based builder of tech and healthcare companies.

The 2005 founded startup — initially bootstrapped (out of founder Greg Law’s garden shed) — has come a long way, and now has more than 30 paying customers for what it describes as its “record, rewind and replay” debugging technology, including the likes of SAP HANA, Mentor Graphics, Cadence and Micro Focus.

A quick potted history: In 2012, Law quit his job to go full time on Undo, raising a small amount of angel funding and then a $1.25M from seed investment in 2014, followed by $3.3M in a series A funding in 2016.

New investors in the Series B round include Global Brain Corporation, a Japanese venture capital fund; and UK-focused Parkwalk Advisors, while all Undo’s existing investor groups also participated —  including Rockspring; Martlet; Sir Peter Michael (founder of Quantel, Classic FM and California’s Peter Michael Winery); the Cambridge Angels group and Jaan Tallinn (co-founder of Skype and Kazaa).

The Series B will be used to expand Undo’s software development team, accelerate product development and grow its US operations. Undo says its best markets so far are electronic design automation (EDA); database manufacturers/data management; and networking.

“This funding will be used to significantly improve performance as part of Undo’s always-on recording vision, and also to accelerate our product roadmap and broaden the technology beyond compiled code so that it can be used with Java and other VM-based languages,” it tells us.

“Our main competitor is the status quo — engineering organisations that do not evolve with the times. Old-school debugging techniques (e.g. printf, logging, core dump analysis) have been around for decades. 2000 was all about static analysis. 2010 was about dynamic analysis, 2020 will be about capturing software failures ‘in the act’ through capture & replay technology.”

Undo argues that its Live Recorder technology offers “a completely new way of diagnosing software failures during development and in production” — arguing that its approach is superior to traditional debugging techniques such as printf, logging, core dump analysis which are “general purpose and provide limited information”, while it says static and dynamic analysis “are deep but can only look at specific instances of bugs” — whereas it claims its tech “can capture failure instances across the whole spectrum and therefore plugs in the gaps which no-one else has filled yet”.

The UK company also sees a growing opportunity for its approach given increasingly complex and increasingly autonomous software risks becoming unaccountable, if it’s making decisions without people knowing how and why. So the wider vision for Undo is not just getting faster at fixing bugs but addressing the growing need for software makers to be able to articulate — and account for — what their programs are doing at any given moment.

“Longer term it’s about that journey towards software accountability,” says Law. “Software accountability is quite a broad thing — it really means the ability to be able to know for sure what some software did as it ran. And today that’s all about the programmer’s understanding of what their program has done. But actually it’s far more than just programmers that need to understand software — and particularly as we move into this second chapter of the information revolution where computers are beginning to make decisions that affect our lives and our livelihoods. I mean in the case of social media and Facebook and things, Western democracy! The ability to have that accountability behind software actions is going to become a really important thing. That’s a progressive journey that we’re on.

“So the question is what did the software actually do? And as we grow, and as time goes on, we’ll answer that question in progressively bigger and bigger contexts.”

 


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