Episode 6: Neil Marley, CEO of Qualyfi

[00:00:00] Hello and welcome to the Conversational AI News Podcast. And today I'm joined by Neil from Qualyfi. Neil, welcome.

[00:00:06] Thank you very much for having me. Appreciate you.

[00:00:08] It's really good to have you here, Neil. And thank you for being a sponsor at our Conversational AI Mini Summit last week.

[00:00:15] My pleasure. I was pleased to see our logo on the banner. I got a picture of that.

[00:00:18] There we go. There we go. I arranged that. I'm really pleased with my own hands.

[00:00:23] Neil, for those who didn't manage to come to the event, can you give us a background on your journey and then let's come to the company, please?

[00:00:32] Sure. So useful potted history, I guess, contextually is in my career, I've been in technology delivery for almost all of that.

[00:00:40] I had a stint at Microsoft helping launch Azure on an unsuspecting enterprise when it was very new, a public cloud service.

[00:00:46] And then I went to go and work for 10 years or so at a Microsoft consultancy helping enterprise customers land cloud data workplace solutions.

[00:00:56] And then about two years ago, I started to qualify. So that's been the journey. We'll talk about qualify in a second, what that means.

[00:01:02] By the way, launching Azure, that's very exciting. I mean, you must have had fun doing that.

[00:01:06] It was great. Yeah, yeah, yeah. It was one of my favorite. I was saying to my wife weirdly this morning about favorite parts of my career.

[00:01:12] That was one of the best ones. I'd go into a small gaming company of 20 people and I'd go into Unilever.

[00:01:17] And you'd have this week of complete contrast and you also had the ability to set contractual terms for this new service.

[00:01:25] So you were actually building stuff. It was really cool, you know?

[00:01:27] Because I remember the availability of cloud. The minute cloud arrived, I went, oh, up until then, I'd been responsible physically for hardware as well as the service.

[00:01:37] But it wasn't quite there. And I think this is very similar to AI, actually.

[00:01:40] So it's fascinating and it's impactful, but it wasn't quite ready, you know?

[00:01:45] We could talk about that a little bit, actually, because I think AI is in the same place right now.

[00:01:49] Are you seeing this kind of parallel then between how public cloud rose and where it is now, where it was versus AI?

[00:01:59] Are we in similar stages, do you think?

[00:02:01] Yeah, there's lots of ways, isn't there, of looking at maturity of these services.

[00:02:04] I look at it from a very pragmatic point of view.

[00:02:07] What can they do and how can they impact business outcomes?

[00:02:10] And I think the promise of public cloud, when I started doing that in 2008, 2009, there were a much, much smaller set of services.

[00:02:19] There were things like stateless VMs, you know, which were, they had challenges.

[00:02:24] But the promise was really amazing.

[00:02:27] The idea that you could just scale up and scale down utility compute, not have to wait for three months for a ProLiant server to turn up.

[00:02:34] You know, that was really exciting.

[00:02:37] And so you look at these early adopters, they come in.

[00:02:39] I think there's this cycle, isn't there?

[00:02:40] The first 15% of people in an audience adopt early and the rest follow.

[00:02:46] And so I think we're probably in that point where AI isn't perfect at all, but it is offering the promise of really amazing productivity gains and new business outcomes.

[00:02:58] So I think we're at that point.

[00:02:59] We're certainly some distance from maturity.

[00:03:02] There's things like looking at Klarna's announcement this last few weeks about the death of SaaS and all that whole stuff.

[00:03:08] But we're so far away from that, I suspect.

[00:03:11] You know, the idea that you can use AI to write apps and not have app builders, I think, is some distance away.

[00:03:17] But that's directionally good to think about, I think.

[00:03:20] But it's not.

[00:03:21] So we're still very early, I reckon, in this maturity curve.

[00:03:24] And there's so much potential.

[00:03:26] That's what makes it exciting, I think, being at the beginning of a wave.

[00:03:30] It's really cool.

[00:03:31] Bring us over to Qualify.

[00:03:32] What's the background on Qualify?

[00:03:33] So Qualify was founded to fix a couple of the challenges that we'd seen in my previous role.

[00:03:41] We were growing a consultancy business.

[00:03:44] We started at about eight people.

[00:03:46] We ended up at 350 in eight or nine years.

[00:03:48] And so that growth was explosive through the public cloud rise, aligned to Microsoft's growth as well.

[00:03:57] And some of the challenges in there I think people recognize as you grow, even if you have just new people joining, you know, and M&A and other things, is how do you get people on board quickly?

[00:04:07] How do you train them?

[00:04:08] How do you get them aligned, standardized?

[00:04:11] And particularly, where are the new talented people coming from?

[00:04:15] Where – how do you grow people, if you want to, you know, think about a verb, to develop them from an early career state?

[00:04:21] And we tried apprenticeships.

[00:04:22] We tried a boot camp approach.

[00:04:24] And none of them really worked because it's actually quite a significant investment of time, you know, to get enough time and energy from the right people to look at potential, spot that, and then spend time training them up.

[00:04:36] And it's a non-trivial act, you know.

[00:04:39] So that was one thing that we really wanted to fix because we think lots of companies have that challenge.

[00:04:44] And I think lots of people nod when you say these words.

[00:04:46] The other one was, could we find a new audience of a talent pool?

[00:04:52] And I think I've met lots of consultants in my previous business who knew Signature who were excellent consultants but didn't have a classic academic route, you know.

[00:05:02] So a lot of them didn't have a degree, but they are hugely passionate.

[00:05:05] And so I was completely convinced and I am convinced that there are thousands and thousands of people out there who don't have an opportunity, don't even know it exists,

[00:05:12] and they could be amazing in, let's just call it IT delivery is a very broad term.

[00:05:17] So we thought, why don't we put those two things together?

[00:05:20] And we found a qualifier on that basis.

[00:05:22] So let's open up the opportunity to anybody.

[00:05:25] Let's find them, train them, develop them really fast on what it means to be a great consultant with the raw talent, you know, humility, determination, attitude, EQ,

[00:05:34] a certain emotional maturity that's important for consultancy, ability to learn obviously and so on is really key as well.

[00:05:42] And see if we can get them busy very fast.

[00:05:45] Create a model which meant that that was on us, not on the customers.

[00:05:49] So we do the training up front, person lands with the organisation, they start getting valuable from day one.

[00:05:55] And we've hired about 20 people to prove that thesis and it's been fascinating.

[00:06:01] I've loved doing it.

[00:06:02] You know, the thrill of watching people go from A to B at speed has been fantastic.

[00:06:08] Say a little bit about that methodology then, right?

[00:06:11] Because here we are, Conversationally Eye news podcast.

[00:06:15] What was this methodology?

[00:06:17] There's a hint there, I think.

[00:06:18] Tell us about that methodology of bringing these people, helping them scale or grow.

[00:06:23] So we started off with some pretty classic approaches, you know, to identification of key traits, interview in,

[00:06:29] and then we did classroom training and all the things you would expect.

[00:06:33] But through that process, we assembled this enormous amount of IP, you know, what we're looking for, how we train,

[00:06:41] what we train, certifications, soft skills.

[00:06:44] So we assembled this Qualify IP and then we had the idea about six months ago, I think it was,

[00:06:49] to say let's put it into an LLM agent and you create a virtual mentor.

[00:06:53] And that would be something that would be really useful to do.

[00:06:57] But what it did was completely blew our minds, actually.

[00:07:00] When we saw that, it was like, oh my word, you can combine our IP and curated internet sources

[00:07:06] and you can give people a really impressive answer that's probably 95% right,

[00:07:12] which is as good as a human, I suspect in most cases anyway, that will help them.

[00:07:16] And so as they're going through their learning journey, that will be really useful.

[00:07:20] And that's where we started on this conversational AI front.

[00:07:22] And we've since expanded that to say, well, this is really interesting.

[00:07:26] If you then add, from our experience and domain knowledge about delivery,

[00:07:29] if you add in a company's specific security policies, naming conventions, and so on and so on and so on,

[00:07:35] there's a big, big list of documents that we've got taxonomy for.

[00:07:38] Then you can ingest that information.

[00:07:41] Suddenly, you've got something really interesting.

[00:07:44] How then does that, the end user, the individual, how do they experience that?

[00:07:52] How do they use that, Neil?

[00:07:53] Yeah.

[00:07:54] So it's a classic chat interface, version 2 now of our service.

[00:08:01] But it's a classic interface.

[00:08:03] Browser-based can be plugged into a widget or whatever to connect to the web services.

[00:08:07] And it's basically conversational.

[00:08:09] So you say a thing like a question.

[00:08:12] Right.

[00:08:12] What is our security policy on Project X?

[00:08:15] And that will give you a response which is relevant to that answer,

[00:08:19] pulling information from your data stores.

[00:08:21] But it can go further than that.

[00:08:23] And you can say things like, please.

[00:08:27] I always say please.

[00:08:28] I don't know why.

[00:08:28] Please provide me with a design document, a statement of work, a work breakdown structure,

[00:08:34] and an architecture diagram for an Azure landing zone in Canada

[00:08:38] with these parameterized requirements for, say, financial services and so on.

[00:08:44] And it will give you all those back.

[00:08:46] Because one of the things that Gen.I.I. is brilliant at is generating documents.

[00:08:50] And so it's a really good fit.

[00:08:52] When you look at technology and go, am I smushing this technology into fit something?

[00:08:55] You know, this one is actually preset, if you like, for that.

[00:09:00] The hard bit is, in the old process, is identifying all the information that you need.

[00:09:05] So where are all these documents?

[00:09:06] Where are all these best practices?

[00:09:07] And so that's a piece of work to do.

[00:09:10] We're well set up to help with.

[00:09:12] And so here's our pre-populated index of documents and policies and data points and so on.

[00:09:19] We'll help you compile those, ingest them into the model.

[00:09:21] And then you create your own little wonderful world of IP, which learns and grows.

[00:09:26] So it's very much that type of chat interface.

[00:09:28] I think we'll see that change over time.

[00:09:30] We'll see agents talking to agents and programmatic use of stuff.

[00:09:33] But right now, it's a classic sort of co-pilot tool.

[00:09:37] You can ask it a question.

[00:09:38] You can ask it to produce information for you and it'll give it back to you.

[00:09:41] Would you humanize this a little bit, Neil?

[00:09:43] But giving us an example of an individual or an amalgamation of an individual to show us that journey.

[00:09:49] Yeah.

[00:09:51] For me, this is all about knowledge transfer.

[00:09:53] What we're doing here is democratizing knowledge to people.

[00:09:57] A lot of the stuff we just talked about is either held in silos that can't be easily found or human brains, you know, the solution architects and senior.

[00:10:06] And they're not on purpose, just the way that life is.

[00:10:08] So what we're doing is taking that and democratizing and giving it to everybody else.

[00:10:12] And we've numerous examples of this in our program where people have joined our program.

[00:10:16] We've done our training course, you know, and our ramping.

[00:10:19] And then the idea is that they can use this tool.

[00:10:25] The people we've got have come from almost no knowledge about these environments.

[00:10:31] It's really important to say that.

[00:10:32] Some of them have come from classical degrees, like music degrees.

[00:10:36] Some of them have come from working in a supermarket.

[00:10:38] You know, they've come into our program with no IT knowledge.

[00:10:42] I can't stress that enough.

[00:10:43] Right.

[00:10:43] But with a determination and an interest.

[00:10:45] That's important.

[00:10:46] And so one of the people in our program was working in a college in the Midlands, you know, on reception.

[00:10:52] And he was helping hand out badges and do all the things you do on a reception.

[00:10:56] And he had interest in computing.

[00:10:58] School hadn't gone quite the way he wanted it to.

[00:11:01] A lot of people, they're not necessarily aligned to the classic education system.

[00:11:05] It's very much, you know, if you fit, you fit.

[00:11:08] Right.

[00:11:08] And so he applied for our program, gave some amazingly good answers in the interview and the testing.

[00:11:16] And it's really thoughtful.

[00:11:18] And he just accelerated through the two-month process at such rapid speed.

[00:11:23] When you find that alignment of the human's desire to the opportunity, you know, it just clicks and people go, this is my big opportunity.

[00:11:30] I'm going to grasp it.

[00:11:32] So we did a lot of in-person training, a lot of mentoring to help.

[00:11:36] But then the tools available to say you've got questions.

[00:11:40] And those questions aren't just technical.

[00:11:41] They're also about how do you respond in situations.

[00:11:44] So all of the stuff we've built in our training course is things like managing stress, dealing with difficult client escalation calls, dealing with emotional situations, presentation, reading the room, these sort of things.

[00:11:58] So you can ask the Ask Q service.

[00:12:01] Tyler, this guy, could say, I'm going into my first customer meeting.

[00:12:05] How do I prepare?

[00:12:05] That's a really good question to ask a mentoring-type person, you know.

[00:12:10] If they're not available, you can get a very good three- to four-point plan to how to go and do a professional job in that meeting.

[00:12:18] So there's loads of content in that area, as well as the technical stuff.

[00:12:22] So if you're going through the advanced Azure Amazon certification and he's unclear on a certain topic or a certain area, then you can use the tool to ask questions about that.

[00:12:32] And then it extends into the actual deployments of areas inside the customer.

[00:12:36] So where he's working, they'll have projects and engagements.

[00:12:39] And they will be – that's not set up for him specifically yet in that world.

[00:12:43] But as and when people take on these tools, you know, they'll be able to ask questions that are context-relevant to the projects and customers they're working in.

[00:12:51] And that is when you start to get really interesting outcomes, yeah.

[00:12:54] A lot of the individuals I'm speaking to, and me myself, trying to find individuals and get skills into your team and then make sure that everybody's working from the same common data stack and templates is really complicated, Neil.

[00:13:10] So this looks like a really – you know, I can imagine a lot of executives responding very well to you when you're presenting this as a possibility for them, for their own needs on their project and activities.

[00:13:22] Yeah.

[00:13:22] Just forget, if you like, the qualify early career thing, which is where this all came from, to help ramp fast, give standardization.

[00:13:30] Ramping fast and standardization are still massive challenges for delivery teams, mostly founded on the risk element.

[00:13:36] You know, if you're not doing things in a standardized way, you're probably not efficient.

[00:13:41] So it's a cost issue.

[00:13:42] And you're also – the biggest thing that we spent a lot of manual time on was security audit and making sure that things have been deployed in the right way.

[00:13:52] Critically important, obviously.

[00:13:54] You know, you're dealing with production-level systems, and you have to make sure that you are applying the appropriate policies and so on.

[00:14:00] And that is really hard if your team is changing materially regularly.

[00:14:06] So if you're growing or acquiring, you know, and there's churn in the world, it's really difficult to say if you're growing at 50% and you have attrition, you're actually growing at more than that because you're taking more people on.

[00:14:17] And so you've got probably a new company after a year, you know, in terms of the people who are new are bigger than the ones that were there before.

[00:14:26] So how do you get them all using the same – you have to teach them.

[00:14:30] And currently, the only real way of teaching them is through, I think, through sitting down with a senior person who knows everything.

[00:14:36] This is a really fascinating answer to that massive challenge that people have.

[00:14:41] So this is where the genesis of the idea came from, the qualified program and giving early career people a great ramp.

[00:14:48] But that challenge is exactly the same one that mid-senior people have landing into organizations doing delivery.

[00:14:54] What then is the qualified service offering today?

[00:15:00] So if you like, the classic go-to-market, if you want, the thing that we think is important is this Ask Q service, which is effectively a lot of RIP combined with LLM and RAG services that allows you to give answers to people that are highly domain relevant in the area of technical delivery.

[00:15:22] So if you've got a technology delivery function in a bank and a retailer or that's your primary business, you can give this tool quite non-invasively.

[00:15:32] You know, you can plug it into a person's workflow and they can ask you questions of our IP, your data stores and your policies.

[00:15:39] And it's a way of just surfacing and transferring knowledge that's in your business.

[00:15:44] We used to use knowledge bases and they were never kept updated and, you know, people always juggled to find them and whether it was the right thing.

[00:15:51] This is the next generation, I think, of a dynamic talkback knowledge base.

[00:15:56] That's at level one.

[00:15:57] And then level two is it can build scripts and deploy stuff for you as well, subject to a bunch of controls you need to think about.

[00:16:05] But there's that piece.

[00:16:07] I think that's the primary service.

[00:16:09] Then we offer the people who can use these services.

[00:16:15] So we train them on next generation AI, data, cybersecurity tool sets using these type of tools.

[00:16:22] And you can inject people like that into your workforce who are coming from all kinds of backgrounds.

[00:16:27] So you're bringing a bunch of diversity into your team, but they're using the latest technology.

[00:16:31] So it's a combination of those two things.

[00:16:32] You know, we start with the Ask Q thing because I think that is hugely relevant to everybody.

[00:16:36] But we're really interested in how we can enable that knowledge transfer for early career people.

[00:16:41] You might have them in your business already, you know, and that may be you may have a graduate program and that may be a real struggle for you.

[00:16:47] How do you how do you get them ramped?

[00:16:49] How do you get them knowledgeable?

[00:16:51] So we're more than happy to provide services to help with people you already have as well as supply people through our own process.

[00:16:57] I think the reason you'd use our people, if you like, is that we select them specifically on the basis of those characteristics we talked about earlier.

[00:17:05] You know, the ability to be empathetic, the ability to be determined, the ability to consume knowledge really quickly, passionate about the topic.

[00:17:15] We select those characteristics, not just I've got a 2.1 STEM degree.

[00:17:20] You know, that is that's not a good marker anymore.

[00:17:23] I don't think in terms of are they going to be a great consultant?

[00:17:26] Wait, like so three weeks ago, more or less, a whole load of graduates joined their graduate training programs.

[00:17:37] Many of them selected based on that precise criteria.

[00:17:43] Yes, exactly.

[00:17:44] It is speaking to people in in talent teams and delivery organizations who get the influx every autumn of people.

[00:17:53] It's a bit of a lottery, I think, from their perspective.

[00:17:57] They get some bright, bright humans who may have potential.

[00:18:03] But what we have tested for in our program is actually very specifically to be an IT consultant, delivery expert.

[00:18:09] Right.

[00:18:09] The half of it, at least, is how you are, you know, and your attitude to life.

[00:18:16] We've met lots of very, very bright people that we don't think would actually be very good at being a consultant because you have to want to work in a team.

[00:18:23] You have to want to understand other people, listen well, understand requirements, think about it from a business perspective, not just a technical one, you know, and deliver pragmatically as well.

[00:18:35] Not just technically beautiful answers, but the ones that work in the real world and that are also efficient and economical.

[00:18:40] So it's actually quite a broad range of characteristics in a human that you're looking for.

[00:18:46] And one of them is can they cope with intellectual rigors of a problem?

[00:18:52] That's just one of them, you know.

[00:18:53] But what you'll find is people are determined will find a way, you know, to get that.

[00:18:58] Or they'll bring other people in or there's a combination of answers.

[00:19:01] They'll get it done, exactly.

[00:19:04] So those are the things I think that really matter.

[00:19:06] And I suspect that most organizations bringing in people to their businesses won't go to that level, I think, in terms of testing, I suspect, for those types of functions.

[00:19:19] What – I wondered then, can we move toward the precipice, Neil, of the horror?

[00:19:27] What does this mean for the future of tech delivery and the tech delivery world if, you know, if you've got your ask queue?

[00:19:36] Yeah.

[00:19:37] Right?

[00:19:38] Because essentially, if you've got the right attitude or the qualifiers that you're discussing there, really, as long as you've got your ask queue, you can technically achieve anything.

[00:19:50] So what are the implications for this?

[00:19:52] Well, I think they are – they're profound, actually, first of all.

[00:19:57] And they're non-trivial.

[00:19:59] They are those things.

[00:20:01] So if you look at the production of a statement of work – in my old business, we'd give a pre-sales leader, you know, two days, two and a half days to go off and write and construct a statement of work using a template and so on.

[00:20:13] That's two minutes.

[00:20:15] That's the difference in productivity.

[00:20:16] So if you extend that out, then you start looking at, let's say, you know, a 25% reduction in steady state teams.

[00:20:27] There's an immediate consequence there, which is, I think, smaller teams using software agents – let's just use those words rather than AR – but software agents – will probably be sort of directionally where that's headed.

[00:20:41] And there's a bunch of consequences from that, you know, which – not obviously just the reduction in the workforce, but also all the surrounding functions inside a business.

[00:20:50] So, you know, what does that mean for your size of your office?

[00:20:53] If you're working in a large global SI and you have people all over the world, you know, which of those people are going to be impacted most by the agents?

[00:21:10] You know, and they're probably things like coding.

[00:21:13] You know, if you have a very clear set of requirements, you can do what I've just said for coding.

[00:21:19] So there's some functions inside these businesses, whether they're in a bank or in a consultancy firm, that are delivering outcomes.

[00:21:25] And some of them can be quite relatively packaged up.

[00:21:28] You might call it intellectual manual labor.

[00:21:30] I heard that phrase a while ago.

[00:21:32] It's, you know, it's like a – it's a way of defining –

[00:21:35] Intellectual manual labor.

[00:21:36] I love it.

[00:21:36] Right.

[00:21:36] Okay.

[00:21:37] Because it is actually process.

[00:21:38] It's not – it's a function that you perform within a very well understood set of guidelines, processes, and frameworks, you know.

[00:21:44] So – and those sort of tools – those sort of functions are very easily achieved with a thing like Ask Q.

[00:21:50] So you can say, yeah, give me a design diagram for this, for these parameters.

[00:21:54] And actually, a lot of those scripts, codes, coding outputs, and so on are particularly suited to a Gen AI outcome.

[00:22:02] So you start looking at it going, actually, what else don't I need as much?

[00:22:06] Or what do I need differently?

[00:22:07] So you look at something like talent acquisition.

[00:22:11] Classically, those functions have gone into market and with a requirement from a practice leader or a –

[00:22:18] So I would like to have a person in this location for this approximate amount of money that has five years of Python experience.

[00:22:26] Pick a technology.

[00:22:28] I don't think people will be doing that.

[00:22:30] I think it will almost be – the procurement exercise will be internal for an agent to do that.

[00:22:34] You know, it will be how do you do that with a software tool, which, again, will completely change the way in which people think about talent.

[00:22:44] Agents will be part of the talent in your business.

[00:22:48] Agents will be part of the talent in your business.

[00:23:16] So really interesting things about the business models, particularly, again, for consulting firms.

[00:23:21] They often operate on a time materials or day rate basis.

[00:23:25] What does that mean in the future?

[00:23:27] You know, where you don't have humans doing 25% of the work, how do you bill for an agent or agentic workflow?

[00:23:34] No one's thought about how that's going to play out, I don't think, yet.

[00:23:37] They may start looking more at fixed price outcomes and other things.

[00:23:41] But it will reduce the cost base, effectively, so the technology will become cheaper to operate.

[00:23:49] And there will be a big battle about who can create the most efficient agents to do all kinds of things inside outsourced projects and so on.

[00:23:57] So I think there's some really interesting ramifications for this.

[00:24:01] I think the other thing that I think is really key, if you look at all technology developments in the last X decades, they must be led by business.

[00:24:10] And they must be led by outcomes, not by the technology.

[00:24:13] So the technology is fascinating.

[00:24:16] But the thing that makes it work is the application of that technology in a business context.

[00:24:20] So I think domain-specific areas are really key.

[00:24:24] We're focusing as Qualify on technology delivery.

[00:24:27] We're not going to get into retail customer experience.

[00:24:30] That is a completely different domain.

[00:24:34] And I think focusing on people who know their onions when it comes to a certain area and can create an answer using technology to fix some of the challenges I talked about before, focusing on that.

[00:24:47] So that's the key thing.

[00:24:48] It's not, isn't this cool, we can do this.

[00:24:49] It is, this is going to revolutionize the way we deliver outcomes to our customers internally and externally.

[00:24:56] And it costs less and it's high quality and it's less risk.

[00:25:00] That's a go.

[00:25:02] We'll do that.

[00:25:03] If I play the game then, Neil, would then, if for example, I have the ASCUE agent in my service delivery team,

[00:25:14] and because I've got ASCUE and I've added my own IP and you've done more to this,

[00:25:19] and we've got the right people operating or working with it, I would then ideally be in a better place to deliver outcomes versus somebody else.

[00:25:30] And I think the important bit is actually this is a platform we're offering and you create your own differentiation with your documents, policies, IP and approach.

[00:25:39] So we're offering a framework for that.

[00:25:42] It's not like buying a SaaS tool where everyone gets the same answer.

[00:25:45] Yes.

[00:25:45] Very interesting.

[00:25:46] Or chat GPT even where everyone gets mostly, not every time because obviously it modifies, but there's no differentiation in public cloud offered AI services.

[00:25:57] You're actually feeding your IP into it when you do that.

[00:26:01] You're actually making it better.

[00:26:01] You're actually making it better for everyone else.

[00:26:03] I think the important thing about ASCUE and other domain-specific agents is that they sit inside your infrastructure with your information, your data,

[00:26:13] and are inherently secure in that way, and then you feed them with your best practices and your learning.

[00:26:19] And I think over time we'll see those develop massively into different ways.

[00:26:24] So company A's one instance of ASCUE will be quite different from company B's because it's using some of our IP,

[00:26:32] which will be the same answer, for training ramping, which probably is not going to change and it won't be differentiated in that sense.

[00:26:39] But the bit that will make the difference is how the agents respond to questions and how good they are and how well trained they are

[00:26:47] and the number of scenarios they're able to consume and interpret and offer back an answer.

[00:26:54] That will be really, that will be a differentiator.

[00:26:56] And then you'll see that the company A and company B thing, the one that's doing better, will offer a competitive advantage.

[00:27:05] People will start talking about that in their marketing literature, you know, that sort of thing.

[00:27:09] What then, Neil, what are you looking for commercially, people listening now?

[00:27:15] What would you like to happen?

[00:27:17] Well, I think if anyone has, if you think, you're listening to this and you think, yeah, I think he's got a point.

[00:27:24] I think there's going to be some change.

[00:27:27] And even if you think it's 10%, you know, or, you know, there's a lot of marketing hyperbole about AI and so on.

[00:27:33] But I think it will significantly and radically alter technology delivery.

[00:27:38] And if you think that and you agree and you're nodding, then I think have a look at what we've built.

[00:27:42] I think it's a tool set that allows you to very quickly take advantage of some of the early stage areas, you know,

[00:27:49] without breaking what you're currently doing.

[00:27:51] It's just additive.

[00:27:52] So give yourself a knowledge base.

[00:27:54] Give yourself a deployable script library.

[00:27:56] Give yourself all these features for your technology team, ability to standardize and ramp new hires, wherever they come from.

[00:28:05] They're all great things.

[00:28:06] So, and that's the first stage on this journey.

[00:28:09] You know, you can go too soon or you can go too late in some of these technical waves.

[00:28:13] And I think start with something that's very useful.

[00:28:17] Business outcome is good.

[00:28:19] And then start the journey.

[00:28:20] But do start.

[00:28:21] I think get going with it.

[00:28:23] Right.

[00:28:23] And assess it and pick a department, pick a function and off you go and learn about how it works or not for you.

[00:28:29] I think that's what I would say.

[00:28:31] We've built a very specific answer for technical delivery teams and that's our domain.

[00:28:36] So if that's interesting, we should talk and show you what we've got.

[00:28:39] Really cool.

[00:28:39] Neil, what's the right way of doing that, of talking?

[00:28:42] How do people find you and connect with you?

[00:28:44] Yeah.

[00:28:45] So I'm on LinkedIn.

[00:28:46] Neil Marley at Qualify, spelt weirdly.

[00:28:49] I'll put the details in there.

[00:28:51] Yeah.

[00:28:51] But it's always to get the domain name, you know, how these things are.

[00:28:54] I'd love to hear from people and have a conversation about what's going on in their world and whether we can help or not and what we could do.

[00:29:03] Because I'm very much of the opinion that I want to understand as well what's going on.

[00:29:08] So this may not be an answer for everybody in different states of their current maturity, but it may be brilliant for some.

[00:29:15] Then you heard it there, dear listener.

[00:29:18] Neil has called for coffee.

[00:29:21] Well, I'm putting words in your mouth there, Neil.

[00:29:22] But Neil would like to talk.

[00:29:24] Yes.

[00:29:25] I think that would be a really good – if you're semi-interested or very interested, drop a note to Neil and see what kind of conversations you can take.

[00:29:36] Neil, can I say thank you so much for taking the time?

[00:29:38] That's been really, really interesting.

[00:29:40] Neil, thanks very much.

[00:29:42] Thank you very much, Ewan.

[00:29:42] I enjoyed that.

[00:29:43] It's a great time to be part of a new wave, a new era, I think, of technology.

[00:29:49] And if we focus on what that means for businesses, we won't go far wrong, I think, in the end.

[00:29:54] I hear you.

[00:29:55] I agree.

[00:29:56] Thanks, Neil.

[00:29:57] Thank you.