Transcript

So, yeah, so, Celerity is an organization. We've been, uh, around for coming up to 25 years, and throughout that time, we've worked extensively with, uh, public sector organizations. And I think probably from those early days an- and- and right through the backbone of our- of our organization, it's always been, protecting and- and managing your most valuable assets, which is- which is your data. Um, we've, um, we've kind of developed over those years, so having been basically a traditional VAR in the early days. We've now built that- built that traditional VAR an- and- and have built on that, and have- and have now become, um, a market lead and managed service provider as well. So we've got lots of managed service offerings, um, in the data s- data security and resilience space, in the cybersecurity space, software asset management, and, uh, compliance and asset management. Um, lots of the conversations we' have with, public sec- uh, public sector organizations, they don't really differ, actually. We work with a lot of central gov, defense, local gov, healthcare, et cetera. Everyone's on a digital transformation journey, and what we found is that that transformation is absolutely reshaping the way in which services are delivered out by organizations. now, consumed, uh, within organizations. And, um, that's, uh, that digital transformation, um, has allowed us to really get close to our- customers, and- what we've, realized is that- you absolutely have to balance that transformation with trust, with security a- and- resiliency. And- and that's why we've been helping public sector organizations such as yourselves in order to secure their AI, uh, protect, um, their most sensitive data across its life cycle. Um, and that's really important, because that, data, whilst it's always been an important feature of- of- of organizations, it's now that competitive, uh, element to most of what organizations do these days. So we understand there are unique pressures in public sector organizations, and like I said, they're- they're a familiar conversation that we have, you know, across the breadth of- of organizations we work with. But interestingly, and we've had some conversations this morning, um, the first one we come, up a lot against is- is the lack of data visibility within organizations, you know, how do you classify your data? Sensitive data is growing at an exponential rate, and so is the importance of that data within organizations. Customers struggle to really determine, um, how and where that data resides within an organization, how it moves within that organization, but actually, how it moves out of that organization as well, who has access to it, and really the risks of- of the br- the breaches and non-compliance, uh, as a result of this. So we work extensively with our client engineering team to- to come in and help you to classify that data, and really understand where that data is, what it's doing, who's got access to it. That's fundamentally the- the- the grounding for anything that an organization is looking to do, whether that be moving into AI or et cetera. Which kind of brings me on to AI adoption, which is a really interesting topic that- that- that w- that we speak to a lot of customers clearly about. Everyone's on some form of AI journey, but actually, it's interesting to note that there's not that many organizations that are that far up the maturity scale. Most are still in those early phases of adopting AI. They're trying to build out the use cases, they're trying to build out business cases, they're trying to monetize actually what- what- what AI is going to do for their organization. But what it has done is it's created this kind of loss of visibility of where data's stored, accessed, and importantly, how it's protected. This, uh, obviously impacts an organization's ability to prioritize risks, um, which fundamentally, you know, when we talk about AI, it's very exciting, but actually, when you get into the nub of it, there are so many risks associated with, you know, with AI adoption. So we talk to them about, I mean, and- and- and- and we talk to organizations such as yourselves about how we address the security gaps across the spectrum of use cases, whether it's shadow AI, shadow data, or whether it's, you know, across into your cryptographic posture, et cetera. Um, so A- AI and- and- and- and gen AI and- and- and- and- and all that's coming with it, it's a really interesting topic and something that you have to get that security and governance life cycle correct. It has to form the basis of what you're trying to do with AI. Which leads me quickly on, sorry, uh, just to, uh, just to talk about something that's close to Darren Sander's heart, which is quantum, uh, computing. Um, we s- speak to many, uh, uh, organizations. It's a real fast and- and- and approaching threat to current, you know, encryption, you know, and security standards. And- and lots of organizations kind of think it's something that's in the future and we'll get to it at some point. Organizations like IBM, um, they're making huge advancements in quantum computing, and- and what we're starting to find is, you know, the queue date is, you know, people are talking about this queue date moving from 2035 to 2029. You know, a- a- a massive, massive leap forward, you know, and a shortening of those timescales. You know, conversely then, NCSC are having to, um, look at their roadmap, which, you know, organizations had until 2028 to- to come up with some form of a re- remediation plan around, you know, the cryptographic, um, services that- that- that they're building out. So it's a really interesting topic. Darren's here today. Please come and talk to us about it.