We spoke to Lily Hristova, Product Associate at Senseye, about machine learning, identifying problems before they happen and start up culture. Read all about it…
Hi Lily, great to talk to you. So, for the uninitiated, what exactly is it that Senseye does?
Senseye tries to predict problems before they occur. We use machine learning technology and artificial intelligence to analyse our client’s data to predict failure points with their machinery. So, for example, we might monitor a production line at a car factory. The failure of even one robot in this type of environment could cause production to stop for days – which can obviously cause huge losses for the company.
We’re also looking for patterns; things that have gone wrong in the past, trends within the data that seem to be linked to certain issues, anomalies etc. The technology we develop helps maintenance engineers spot things that are at risk of failure much earlier (potentially up to six months in advance). It’s all about performing the right maintenance at the right time rather than fixing something that’s already broken. This enables our clients to save a huge amount of time and money!
Very interesting! So what exactly is your role?
I work here as a Product Associate. Working within the Product Team, my role is all about developing various features within our releases. We work closely with the research team to understand exactly what these improvements should be. We work in cycles, using an agile approach to development, so sometimes it’s busier than others.
I see. Is this something you’ve done throughout your career?
Well, my degree is actually as a telecoms engineer – it has nothing to do with what I do now at Senseye! I started out with a graduate diploma from Southampton University, and Senseye happens to be based here too. Since graduating I’ve worked for quite a few IT start ups, initially as an Account Manager. I then found my way into product development (which I find a lot more interesting than my actual degree!). So, I have a technical background but it’s not directly linked to the main focus of Senseye!
At this point I’ve worked for the company for a year and 8 months, so I feel like I’ve been here for quite a long time now. I really love the startup culture. It gives you a lot more freedom to make decisions. In terms of its size, Senseye doesn’t feel like a startup anymore – we’ve been successful and have grown quite rapidly – but we’ve definitely held on to that culture though. Flexible working hours, remote working and so on… we’re free to explore and develop without the restrictions of a big company. It’s a really nice way to work.
Tell us, how did you come to work with McFelder?
A colleague of mine who was working as a project manager had established the relationship with McFelder – then that was eventually extended to us in the product team and translations have been my responsibility to manage since mid-2019. We’ve had a successful working relationship for quite a while now! Our team uses McFelder when we have new releases and features – teaming up with a reliable translation partner makes the workload a lot easier.
Well we’re very glad to hear it! Can you explain a bit about your software localisation needs?
We’ve developed a cloud-based application (software) that’s mainly used in English but needs to be translated into 6 other languages. Every cycle we have new releases that introduce new features, so we need translations for the messaging within them. Or it could be translation support for a completely new product.
Another service that we provide is our new Support Centre. Language is an important factor here too. It’s where our customers find user guides and other important information relating to our services. Essentially, it’s a knowledge base that explains how to change settings, how to use features, outlines new releases and major changes. We send new articles over to McFelder to make sure everyone has accurate information available to them in their chosen language. Having translations complete prior to, say, a new product launch is simply more proactive and helps us to better serve our clients.
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So it’s obviously very technical in nature…
Yes, both the content of the translation and the process of translating software is technical. It’s not as simple as just translating a document. Our engineers will generate a specific file type for the English version of a particular piece of software. They’re then sent off to our Project Manager at McFelder, and sent back to us in the appropriate format, ready to implement directly into our current build.
Of course, due to the nature of our service, the subject matter itself is very technical too. We have to be very weary of the terminology; machine monitoring, machine learning, failure modes and so on. If we say we see a certain failure mode happening in an asset and it’s not translated properly clients can lose trust in our product. Accuracy is very important!
Absolutely. Well thanks for giving us such an interesting insight into what’s obviously a cutting-edge business!
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