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Essential data, straight to the business frontline

Can Osiris use A.I. to cut the data analysts out of data analysis?

Hello there,

There’s something notable about the co-founders of today’s startup in these challenging times: they’re a Russian-Ukrainian team.

They’ve developed a fresh take on data analysis that is already serving customers, eight months after the startup was incorporated. Scroll down to read all about Osiris.

But first:

  • New UK government definitions of what makes a high net worth individual are a real worry for the angel investing community and startups alike. If you haven’t read and signed the Startup Coalition’s open letter to the Chancellor, do so.

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Osiris wants to give businesses instantly useful data analysis… without data analysts

Are businesses making enough of the data they have? A whole industry has been built around ‘big data’ in recent years but there is still plenty of work to be done to bring the value of data analysis to more businesses, in easier to use ways.

Hoping to bring something new to this particular table is Osiris. To pitch it how their website does, it’s “an A.I.-powered Artificial Worker platform that automates data analytics tasks and functions, creating tailored dashboards and reports and delivering immediate interpretation and insights.”

Okay, ‘A.I.-powered Artificial Worker’ sounds a lot like 2024-vintage startup hype, so what’s really on offer here?

Co-founder and CEO Mikhail Vasenin describes it as “a toolbox for making sense out of your data. You have raw data which is used as an input, and based on this information Osiris starts to build recommendations, tasks, interpretations, and even answer your questions.”

Rather than being built for data analysts, Osiris is aimed at end-user ‘action takers’, the people who make decisions and need to do things based on data. 

Vasenin pulls an example from supermarket retail, which is one industry Osiris already works with.

“Supermarket managers struggle to benefit from the opportunities that can appear from data analysis, mostly because it's time consuming, they don't have access to data, and they usually don't have relevant skills.”

This, Vasenin argues, adds to the problem of shrinkage, which in turn leads to increased prices for consumers.

He says Osiris was last year field-tested across 16,000 supermarkets to monitor supply efficiency and fraud.

“Before Osiris, there were 150 people involved in this task. And on a daily basis, they spent approximately four hours to solve these two problems. But they only achieved 20% coverage on the information flow, just because they couldn't process all products in all these supermarkets. 

“After we applied Osiris, all stakeholders started to receive immediate individual analysis reporting and insights in each individual supermarket, and we achieved 100% coverage of the information flow. Supermarket managers had access to the analysis of not only prioritised products with a higher margin, but to all the products available in their supermarket.”

You can see a demo of how Osiris works across food retail, wellbeing, automatic reporting, and cryptocurrency analysis use cases on the startup’s website.

In its present form, the software is designed to be installed on-premises, where it can access company data more securely, without having to move it to the cloud. While it works with popular tools like Power BI or Excel, it can also pull data from legacy systems that can be difficult for data analysts to work with.

“The key thing is that Osiris’ architecture is built in such a way that its analytical core will continue to be developed. As soon as we have something new or we’ve created a new methodology, we’ll teach Osiris and it will be possible to apply it immediately to our clients,” says Vasenin.

The story so far

Vasenin is based in Newcastle, where he co-founded Osiris with Savva Shanaev and Andrii Yakovyna

Vasenin says he discovered his passion for data analysis as a teenager, when he was doing work calculating prices for a farm in Kazakhstan using Microsoft Excel. To pay his way through his first degree in Russia, he says he took advantage of an interest in automation.

“I was always automating my own tasks. So I ended up having several full-time jobs simultaneously, just because I could find a way to optimise my work through automation.”

This experience led to him developing trading algorithms with Python and machine learning. After an MBA in Russia, he moved to Newcastle in 2019 to work on a PhD at Northumbria University, investigating the relationship between companies’ financial performance and their environmental impact. 

And so Osiris is the culmination of everything Vasenin did previously. 

“After completing my PhD, I had a period of time when I finally had an opportunity to fulfil my dream of automating data analysts, automating everything I was doing before.”

The co-founding team is something that wouldn’t have been particularly notable until a couple of years ago: a collaboration between two Russians and a Ukrainian. 

Shanaev is an old university friend of Vasenin’s from his first degree in Russia, who also ended up doing a PhD at Northumbria University. Meanwhile, in a very 2020s fashion, Yakovyna has never met the other two in person but has collaborated with them online on a number of projects over the past five years.

After the trio developed the first version tech, they field-tested it with food retailers and with charities. They’ve also taken part in the Conception X programme, which helps turn PhD research into startups.

Osiris is already generating revenue. It was incorporated in May 2023, and Vasenin says its first customers were signed up in July. 

While Vasenin says the underlying Osiris tech is flexible for a number of use cases, the startup is targeting data analysis first, identifying a way for companies to plug a shortage of analysts in the job market.

“First we're concentrating on such sectors as financial services, food, retail, and banking; mostly because these industries have a lot of data and they're also interested in being cost efficient… 

“And of course, most of their decisions should be based on the data. However, this is usually not the case. This is where we can contribute most.”

Go deeper on Osiris

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