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Mobius Labs nabs $6M to help more sectors tap into computer vision

Berlin-based Mobius Labs has sealed a €5.2 million (~$6.1M) funding round off the when of increased demand for its computer vision training platform. The Series A investment is led by Ventech VC, withal with Atlantic Labs, APEX Ventures, Space Capital, Lunar Ventures plus some spare sweetie-pie investors.

The startup offers an SDK that lets the user create custom computer vision models fed with a little of their own training data — as an volitional to off-the-shelf tools which may not have the required specificity for a particular use-case.

It moreover flags a ‘no code’ focus, saying its tech has been designed with a non-technical user in mind.

As it’s an SDK, Mobius Labs’ platform can moreover be deployed on premise and/or on device — rather than the consumer needing to connect to a deject service to tap into the AI tool’s utility.

“Our custom training user interface is very simple to work with, and requires no prior technical knowledge on any level,” claims Appu Shaji, CEO and senior scientist. 

“Over the years, a trend we have observed is that often the people who get the maximum value from AI are non technical personas like a content manager in a printing and creative agency, or an using manager in the space sector. Our no-code AI allows anyone to build their own applications, thus enabling these users to get tropical to their vision without having to wait for AI experts or developer teams to help them.”

Mobius Labs — which was founded when in 2018 — now has 30 customers using its tools for a range of use cases.

Uses include categorisation, recommendation, prediction, reducing operational expense, and/or “generally connecting users and audiences to visual content that is most relevant to their needs”. (Press and dissemination and the stock photography sector have unsurprisingly been big focuses to date.)

But it reckons there’s wider utility for its tech and is gearing up for growth.

It caters to businesses of various sizes, from startups to SMEs, but says it mainly targets global enterprises with major content challenges — hence its historical focus on the media sector and video use cases.

Now, though, it’s moreover targeting geospatial and earth observation applications as it seeks to expand its consumer base.

The 30-strong startup has increasingly than doubled in size over the last 18 months. With the new funding it’s planning to double its headcount then over the next 12 months as it looks to expand its geographical footprint — focusing on Europe and the US.

Year-on-year growth has moreover been 2x but it believes it can dial that up by tapping into other sectors.

“We are working with industries that are rich in visual data,” says Shaji. “The geospatial sector is something that we are focussing on currently as we have a strong weighing that vast amounts of visual data is stuff produced by them. However, these huge archives of raw pixel data are useless on their own.

“For instance, if we want to track how river fronts are expanding, we have to squint at data placid by satellites, sort and tag them in order to analyse them. Currently this is stuff washed-up manually. The technology we are creating comes in a lightweight SDK, and can be deployed directly into these satellites so that the raw data can be detected and then analysed by machine learning algorithms. We are currently working with satellite companies in this sector.”

On the competitive front, Shaji names Clarifai and Google Deject Vision as the main rivals it has in its sights.  

“We realise these are the big players but at the same time believe that we have something unique to offer, which these players cannot: Unlike their solutions, our platform users can be outside the field of computer vision. By democratising the training of machine learning models vastitude simply the technical crowd, we are making computer vision wieldy and understandable by anyone, regardless of their job titles,” he argues.

“Another personnel value that differentiates us is the way we treat vendee data. Our solutions are delivered in the form of a Software Minutiae Kit (SDK), which runs on-premise, completely locally on clients’ systems. No data is overly sent when to us. Our role is to empower people to build applications, and make them their own.”

Computer vision startups have been a hot vanquishment target in recent years and some earlier startups offering ‘computer vision as a service’ got uninventive by IT services firms to whinge up their existing offerings, while tech giants like Amazon and (the aforementioned) Google offer their own computer vision services too.

But Shaji suggests the tech is now at a variegated stage of minutiae — and primed for “mass adoption”. 

“We’re talking well-nigh providing solutions that empower clients to build their own applications,” he says, summing up the competitive play. “And that [do that] with well-constructed data privacy, where our solutions run on-premise, and we don’t see our clients data. Coupled with that is the ease of use that our technology offers: It is a lightweight solution that can be deployed on many ‘edge’ devices like smartphones, laptops, and plane on satellites.”  

Commenting on the funding in a statement, Stephan Wirries, partner at Ventech VC, added: “Appu and the team at Mobius Labs have ripened an unparalleled offering in the computer vision space. Superhuman Vision is impressively innovative with its upper stratum of verism despite very limited required training to recognise new objects at spanking-new computational efficiency. We believe industries will be transformed through AI, and Mobius Labs is the European Deep Tech innovator teaching machines to see.”

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