Hi Jamie, great to meet you. Can you start us off with an introduction?
I’m Jamie, I’m the CEO and Co-Founder of Flexciton.
My background is a mathematician that has spun into becoming an entrepreneur. I studied Mathematics at Oxford and after I graduated, I went on to become a software engineer where I spent several years building planning solutions in industry
Before starting Flexciton I had experience developing production planning solutions in industry and saw the opportunity to build something that would solve the planning problems in a much better way. What we’re doing in Flexciton is a new generation that planning solutions, compared with what I experienced while working as a consultant.
I founded Flexciton three years ago and that was when I made the transition from mathematician/developer to CEO where I now spend most of the time on the commercial and business side.
How did you find that transition?
It’s a really interesting one.
As an entrepreneur, I realized very quickly that you have to learn a lot of things very fast and I think being a software engineer really helped me get to where I am because I deeply understand our technology: what it does & how it works. I helped build a big part of it in the first place. It means I can make much better decisions about the company as I fully understand what we do.
Currently, I spend a lot of time working with customers helping them understand how our technology can solve their problems. Although I don’t code and build the software anymore, I’m still involved in technical work.
I think my background has really helped me become the kind of CEO I am now. Business had always been a big passion of mine before I founded the company, but so much has been new to me so I’ve had to learn a lot as I’ve grown.
You started Flexciton via the Entrepreneur First programme, how was that and how much would you recommend it to someone who wants to start up a tech company in London?
I met my Co-Founder Dennis, on the programme and at the time there were around 100 people on the cohort, and I didn’t know anybody beforehand.
I can imagine it can be daunting with so many people.
It is a bit strange! It was very diverse, and everybody is deeply technical where the idea is to found a deep tech company which is very much aligned with my background.
I was very fortunate to meet Dennis on the cohort. As I’d mentioned, I had been working on planning on last generation planning solutions while Dennis was researching the next generation of the technology.
I found a very good match, which doesn’t always happen on the programme, but that’s the risk that you take if you go on it.
This company wouldn’t exist if I didn’t go on the cohort so it’s definitely worth doing it!
I’ve heard the same from many founders that I’ve met over the years. Could you give me an overview of Flexciton’s core offering and what inspired you to set it up?
Think about a factory, somebody has to plan what happens in that factory. That means every week, someone has to decide what, when and how much of each product they are going to make.
Let me give an example of a textile factory who is one of our clients. They manufacture over 2000 products, but they can only make a 100 in a week, so which ones do they choose?
This is really complicated because the number of options is very significant, If someone wanted to plan the production for even one day in the factory, there are more option than atoms in the universe. Each option has different efficiency for the factory as well, so the task of the human planner is to find an efficient production plan. Now this problem is far too complicated for a human to do efficiently and that where we come.
We take all the data collected from manufacturer operations, take it up to cloud where our AI technology understands that factory deeply from the data and comes up with an optimized plan which significantly increases the efficiency of the factory.
How long would it normally take to create this plan?
Minutes, whereas it would take a human many hours to produce a plan, which still wouldn’t be very good compared to us creating a plan that is super optimized.
To give you an idea of the kinds of results that can bring, one of our clients’ factories we have seen £10s of millions of savings that can be brought to their bottom line.
And to answer the second part of your question about what inspired me to set it up, I had seen this problem in the industry coupled with the fact that all that our competitor software has done is automate what the human planner had set up. Humans have never been able to figure out an optimised plan because there are just too many options.
We don’t focus on automation; we focus on optimization.
My co-founder Dennis had been researching this in academia and we realized that it was a great opportunity to found the company.
We both saw the same problem from a different perspective, Dennis from academia and me from industry, and we were uncomfortable about not being able to make a real impact on the market. Dennis was limited being in academia while my impact was limited working for a company.
When we met at EF, we had the same feeling that we could make a real impact, and it’s come to reality with Flexciton.
I think there is an issue in some start-ups where they’ve got great technology or team but not necessarily a good product-market fit, whereas it sounds like you guys had that from the start. Flexciton has been around for 3 and a half years, what’s been the biggest challenge?
I think it’s been taking real deep tech to a complex environment to be a successful product. You’ll see that in a lot of deep tech companies and the gap between academia and real-world application can be quite large. For us, we’ve been fortunate to have a lot of demand in the last three years and we’ve been able to get several early adopter factories to work with us to bring it to market which was something a bit unique compared to some other start-ups in our space.
It’s been iterating a lot on the technology to make it fit and work properly in real life for a factory. That has taken time but I’m very excited to say that we’re pretty much there now and some of the results that we can see in real life and we can really prove what we were saying three years ago that we thought we could do, is now a reality.
AI is such a hot topic at the moment, but we still see there’s very little understanding of what it is and how it’ll impact their jobs. We are here to work alongside human and contribute to their jobs rather than replace them.
There’s definitely that education challenge that we have alongside promoting our product.
I can imagine that with the factory industry being centuries-old that there’s a bit of push back. Who would you normally speak to?
Normally, it would be the factory manager. They typically wouldn’t have any idea about AI but they know how hard it is for one person or even a team to do production planning and when you put the cost-savings in front of them alongside the efficiency of it, it’s quite an easy sell!
Do you work in the UK only or do you work with factories worldwide?
We’re completely UK based at the moment, but the reality is that some of our customers are multinational organisations and we’re going to be expanding, probably the US and then further afield because that the demand that we are seeing from our customer.
What does the future look like and what’s your ultimate goal for the company?
I think that in the short term, we’re still focusing a lot on getting that product right with our early adopter factories but very soon we’ll be looking to grow. That demand has always been there, and we’ve had to actually turn people away which is great for a start-up of our age, which is quite unusual.
We’re looking to productise as soon as we can and look to ship to other factories in the UK & Ireland and then in 2 – 3 years we’re expecting to expand overseas.
In 5 years, we want to be seen as the global leader for this type of software and I think it’s a very real opportunity because of the appetite that I can see already for what we do in the market.
Sounds exciting! Talk to us about culture as it’s something that always comes up. Pressure from investors, from sales, pressures from family and friends which can be passed down to the staff. What is it like to work at Flexciton at the moment?
We can narrow it down to a couple of parts. Firstly, we have investors in the company who very much believe in us, what we do, and in Dennis and I as Co-Founders to build this business in the way that we think we should build it.
The way we’ve chosen to build this is that we want to hire the smartest people and get them to work on the hardest problems and for them to do it with the freedom that they need to do that. It’s a very hard problem that we are trying to solve, and we hire the best people that we can possibly find in the world and we wanted them to grow as they need to.
I’ve only seen one start-up and I know there are bad cultures in other places, but what I can tell you is that everyone is very committed and inspired by the mission of what we’re trying to achieve here which is perhaps why our staff retention is high compared to elsewhere.
It’s a comfortable environment where we encourage people to come up with ideas and where they’re not afraid to make mistakes.
We work hard, as you need to in a start-up, but nobody complains about that and everybody wants to chip in and help because, ultimately, they’re inspired by what they’re working on.
Do you guys promote self-learning like courses and conferences?
We do have a training budget for each employee for whatever their needs are. However, there’s a huge amount of learning on the job and we have a very strong philosophy of giving people opportunities. Whereas in a lot of companies, especially in a corporate environment, it takes a lot of time to set up and get the right opportunity.
The contrast here is as soon as someone shows that potential and appetite to step up, we’ll give them that opportunity. We respect the fact that it takes time, and we understand that you may fail a few times before you get it right.
But actually, when you do that it’s remarkable how much people progress in their careers. I think about how I’ve progressed since leaving my previous role, it’s tremendous.
I try and bring what I’ve learnt and progressed over the years and offer that same path to my employees.
Often, you’ll find working in a corporate, if you want to get into a management position it would take a decade, for example, whereas in a start-up it could take two years. You guys were recently accepted into the first-ever Tech Nation Applied AI cohort. As it’s the first one, could you tell us a little bit about the cohort and how you think you’ll benefit from it?
The programme is primarily aimed at companies at our stage that have found a product-market fit and are really looking to grow and scale in the AI space.
It’s really all about trying to help and give training to founders particularly on the challenges that you’ll likely be facing in the next 2 – 3 years.
It’s really inspiring because the companies that they’ve picked are elite and I know quite a few entrepreneurs from other start-ups and having spent time with other people on the programme, they’re some of the best that I’ve met.
Applied AI organises various different events, like networking dinners or sessions with ex-entrepreneurs who tell you about their story and there’s training like sales training or how to scale your technology internally.
The people who will come and do the training or talks are people who have been through the process before and built a successful company so they can relate directly to the issues that you have and help you understand them before you just run into them during the normal course of building a start-up.
You seem to have done well in the last three and a half years. A lot of start-ups don’t even make it two years. If could offer one piece of advice to a fellow start-up founder, what would that be?
Focus on the market. I’ve seen many tech start-ups where they’ve focused too much on building a product very early on without fully understanding the market for it.
In the last three years, we’ve explored various opportunities with factories to get to where we’ve realized the key factories that can really benefit from our technology and actually what the product needs to be at the end of it.
If we hadn’t been so commercially driven, I can think of so many points in the past where we would have done something that wouldn’t have large enough to scale, for example, building something bespoke to one factory.
Constantly be focused on building something that has a commercial opportunity at the end of it.