All the startups we've covered so far
Nine teams tackling everything from late-paid invoices to Covid-19
Hello there,
Every month, I’ll publish a roundup of all the startups recently featured in the newsletter. If you’ve recently subscribed, there’s plenty to catch up with.
— Martin
Untap
London-based Untap featured in the very first PreSeed Now. Their internet-connected wastewater monitoring system keeps track of Covid levels in sewage leaving a building, giving managers an understanding of how many people inside have the viruson any given day. This allows them to adjust their response on an ongoing basis..
Support for monitoring more pathogens is in development, and Untap plans to sell the tech to care homes, hospitals, offices, and factories, and hospitals on a subscription basis.
The first trial, in an office, detected Covid before it spread among the workforce, co-founder Claire Trant says.
A second trial, in a factory, backed up the findings from the first. “We were able to detect Covid. They were lateral-flow testing the whole building at exactly the same time, so we were able to correlate our data with theirs,” says Trant. “However, one time we found Covid when they didn't find Covid, and we found out that they had external visitors on site. Their auditors were there; they hadn't been lateral-flow testing them and they all had Covid. So they had to send their auditors home.
“Currently we’re in a care home and we've been able to tell them they’re Covid-free and they've taken their masks off, which is nice when you think about the sort of interactions you're having in a care home.”
In many ways, they’re a quintessential startup for this newsletter - building something unusual, solving an important problem, and still at an early stage with credible founders who know their stuff about the issue they’re tackling.
Rigpa
Rigpa introduced many PreSeed Now readers to the concept of neuromorphic computing: building chips that are based on the workings of the human brain.
The Edinburgh-based startup is developing chips for the A.I. computation market and aims to launch its first product next year. There’s competition out there, but the market is at a very early stage.
This topic interested a lot readers, and I hope to return to it in the future.
“The brain itself is so powerful but consumes very little power… 20 watts, like a lightbulb,” says Rigpa founder Mike Huang. “By mimicking the biology of the brain we believe we can create A.I. that has lower power consumption and faster inference speed.”
Rigpa’s work is based on Huang's PhD research into neuromorphic computing for radioisotope identification, and Huang believes that beyond improved efficiency, the approach could even help A.I. self-learn and generate its own innovative ideas.
NeuroVirt
Rehabilitating stroke patients with VR isn’t an idea unique to NeuroVirt, but they’re the only ones going to market with an offering that includes both hardware and software.
Tests of the offering have been positive, and London-based NeuroVirt is preparing to launch it commercially in the UK before expanding internationally and into other conditions beyond strokes.
The first three games NeuroVirt has developed task players with shooting (to develop grip strength), catching shapes as they move towards the player (to improve hand extension), and moving a ball around a tilting maze (to aid wrist motion).
Stroke patients are often not of the demographic you’d expect to throw themselves into VR gaming, but co-founder Eve Gregoriou says the immersive nature of the games makes them feel less like a video game session and more like a fun, accessible exercise.
Enzai
As legislation and regulations increasingly target tech, early-stage startups are going to have more than just finding product-market fit to worry about.
Belfast’s Enzai wants to help A.I. developers ensure their work is full documented to comply with laws and guidelines as they emerge.
Co-founder Ryan Donnelly explains that the excitement of building a cutting edge A.I. product can mean algorithms aren’t as well documented as they should be. And coming from a legal background, he knows the importance of being able to translate complex specialist knowledge into a more accessible format.
Experts who could offer valuable input into an A.I.'s development can end up excluded if they don’t come from a data science or machine learning background and thus find the algorithms and data sets impenetrable.”
Machine Eye
Chances are, industrial machines like forklifts and loading shovels will be fully automated long before the first consumer-ready self-driving cars go on sale.
Machine Eye is doing exactly what its name implies: giving industrial machines the ‘eyes’ they need via computer vision to operate without human input.
The Belfast-based startup’s tech is already being used on machines to assist human drivers.
“We're trying to give drivers that extra support ,trying to… augment their own situational awareness and their own capabilities. And to give business operators a technology that can start to support them, start to assist them in better managing and better operating the businesses” says founder Brendan Digney.
Payful
Most solutions to late-paid invoices come into play after the debt has been incurred. But Manchester-based Payful is building a community of businesses that pay each other on time, verified via connections to their accounting software.
Founder Andy Taylor has seen the problems with existing solutions first-hand when he worked at other startups tackling the issue.
Every business who signs up knows they will be scored, and will benefit from seeing all the other Payful users’ scores. And that mutual score-sharing should encourage users to pay each other promptly. It’s a little like how an Uber driver and their passenger are incentivised to be nice to each other because they know they’re going to be scoring each other at the end of the ride.
This has the potential to see Payful become something I’m surprised we’ve not seen more of over the years: an almost social network-like layer over business processes that builds trust and generates efficiency.
Coyosy
We’ve seen modular tech hit the market before, but Coyosy thinks it can learn from the mistakes of hardware startups in the past with its modular headphone and speaker system.
The Manchester-based startup thinks its time is now thanks to increased eco-awareness among consumers, the global economic downturn, and supply chain issues for traditional manufacturers.
In a world of pretty hardware sold in neat little boxes, hardware you couldn’t repair or upgrade even if you wanted to (hello, AirPods), Coyosy’s vision is unusual. But it ticks a lot of boxes around e-waste, sustainability, right-to-repair, and maximising customer value for money that seem incredibly timely in 2022.
Love Circular
Tech skills schools—both online and offline—are everywhere right now, but Manchester-based Love Circular is offering something different: a focus on supporting students in getting a job at the end of their course, and technology to support individualised learning.
The startup has already got new product designers roles at companies like Spotify and the Financial Times.
“[With our own platform] we can control the experience. As a designer, experience is everything… in terms of how we visualise the learning environment in itself,” says founder Zaire Allen.
“We’re really focused on personalised learning, and [that] will only work if we’re able to gather data via machine learning. The personalised learning model we want to implement will see our students being able to be graded dynamically, and to be given modules or assistance in areas they’re weakest at.”
👉 Read all about Love Circular
Deep Planet
Some call wine the ‘canary in the coal mine’ for climate change. Grapes are a delicate crop so the more support vineyards can get to optimise their yield as temperatures rise and weather patterns change, the better.
Oxford-born Deep Planet analyses satellite imagery and on-the-ground data to help vineyard operators make the most of their crop.
Shankar says improvements in efficiency driven by Deep Planet saved one customer $3 million across a thousand-hectare vineyard; around $50 per tonne of grapes they produce…
Taking a smarter approach to harvesting, based on more data, leads to more than just a nicer bottle of wine from better grapes. “The impact that this has had on the quality is, depending on if it's a high-volume producer or a premium producer, anywhere between 50 cents up to $20 per bottle of wine”.
Back on Tuesday
PreSeed Now is taking a break for the Jubilee long weekend. That’s mainly because there’s a chance you won’t check your inbox tomorrow, and if a carefully constructed newsletter isn’t opened, doesn’t really exist? We’ll be profiling another startup for you on Tuesday.
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