Mark Eardley is the CEO of Langcliffe International, a buy-side corporate deal broking service.
Matt Lewis is the Director of Matix Ventures, an AI consultancy.
Miranda Hartley is the Content Lead at Evolution AI, an AI data extraction firm.
In this interview, we discuss Langcliffe’s new AI platform, AI-enabled growth and the delicate art of balancing people/technology relationships.
Miranda: Could you introduce Langcliffe’s implementation of AI?
Mark: As Langcliffe aims to fill the information gap in the UK M&A lower and mid-market, what was driving our business was lots of data. We had lots of data on vendor advisors, vendors and buyers. But then we realised we knew very little about data - despite being a data-driven business.
Fortuitously, roundabout the time of that realisation, a mutual friend introduced me to Matt. Initially, we've looked at AI to acquire and integrate buyers' data more effectively into our system. But now we're looking holistically at what it can do: be it the buy side, be it the processes within the business, or be it the sell side.
Matt: That's how I see it - the ultimate goal is to deploy AI throughout the entire data process in an end-to-end life cycle. We bring data in, ingest data into the platform, and clean and process it. Then, we analyse it and make actionable events based on that analysis.
That's where we wanted to be in terms of having AI applied at every step of the way. And what we've been doing so far is leveraging AI for processes like cleaning and enrichment. So, we bring data into the platform, make sure that it's high-quality data, and then enrich it with the metadata that we need to make effective recommendations to our buyer clients.
Further down the road, a prospect we find really interesting is having AI intelligently analyse that data to make highly targeted and fine-tuned recommendations for our clients.
Miranda: How have you maintained data privacy during the implementation of AI into your platform?
Mark: Many people in our space are trying to do this without people, and they have publicly open, transparent platforms.
The only people who see our platform are us, and we control the data that goes in. With the AI tool, we control where that data goes, how it goes, and if it goes, and that's really important. It's been our password since day one.
We get confidential data from vendor advisors, and we are 110% A) secure and B) confidential vis à vis that data.
Miranda: Was your team initially on board with the introduction of AI?
Matt: The reception has been overwhelmingly positive in a number of areas, like speed and efficiency. Working with data at scale can be a very manual, laborious process. It’s not just within the corporate finance industry but across the board; you've got data analysts and data entry operators who are sitting on a machine entering data.
One of the promises of AI is that a lot of laborious work can be done. Take this away, and those team members can focus on delivering higher-value services. I think that's been the basis of the positive reception we've seen so far from the team at Langcliffe: it's leveraging them to do more interesting things.
Miranda: How has AI tangibly changed your team's daily workload?
Mark: We're going on a journey with the AI tool. Matt started working with that over six months. Now, the tool is almost here. This month is the first time that we're going to use it properly.
While we're still in the early stages of this journey, I believe that utilising the tool for data cleansing and input, along with automating processes within our platform, will significantly increase efficiency and effectiveness. Perhaps come back and ask me in 12 months because I think then it will have freed up the team to spend more time speaking to clients and building relationships.
I would hope that within two years, we're twice the size, but with the AI aspects of what we're doing, we may not even need any new people.
Now, I don't know that - but I get that feeling.
Matt: While we're doing rollout literally as we speak, we've beta-tested it for several months.
We've been able to see the areas where the tool has value. And so here’s maybe a slightly simplistic example, but one that hammers home its value:
The AI agents collect their sources as they research online and enrich the data set that the team uses - we're still in a stage where we don't want to hand over complete autonomous control to the AI.
The team then has a list of all the sources they can click on instantly; they can validate that AI-generated data. That in itself is a massive time-saving opportunity in that they don't have to start at the beginning and validate the AI’s work.
That feature is saving substantial amounts of time. But then, as Mark says, as we roll out these features more deeply into the whole data workflow, we expect significant freeing up of resources.
Miranda: Time savings aside, what motivated Langcliffe to explore AI?
Mark: The motivation was growing the business more quickly. Putting quality data into our system more quickly was a motivation, but it wasn't the complete motivation.
Matt, do you agree with what I've just said?
Matt: Absolutely. And I think we can improve the quality of the overall service if we can reallocate resources to spend more time with customers and understand their needs and requirements.
It will be a virtuous circle because we will have better quality data come into the system, and we can maintain better quality relationships with our customers.
Mark: Also, if we can gradually perfect the data on buyers worldwide, we can offer vendor advisors a far better service in terms of suggesting buyers for the companies they bring to the market, i.e., their sale mandates.
So, to me, AI was about growing the business more quickly and offering a better service to buyers and vendor advisors. But one of AI’s ancillary benefits is that it will save time and costs, or at least it means we won't have to increase the cost as rapidly as we would in the absence of AI.
Miranda: Are any other departments in Langcliffe looking to implement AI?
Matt: The AI platform we're building is very much based on this agentic approach, which describes the idea of being able to deploy specific customised agents to carry out various tasks.
Even though, at the moment, the agents are all focused on generating company-based financial information for the data that we want to bring into the platform, there's no reason why, in the future, we couldn’t start deploying more marketing-focused agents, for example, and bringing that data into the platform to make use of.
Miranda: Matt, how did you choose what AI you were going to use?
Matt: It's a combination of factors. The three main ones are performance and cost, and I would categorise the third as tool use.
So, the cost is obvious: obviously, the cheaper, the better, but the cheaper models tend to be the less performant.
And because we are deploying these agents, they need access to tools, and not all models are equally good at using tools to do things like web searching, web scraping and reading a PDF document, for example. It’s really a combination of those factors that means that we tend to opt for OpenAI’s GPT models.
Miranda: Are you thinking about changing the company positioning in tandem with your implementation of AI?
Mark: At the same time as we’re massively improving our AI capabilities, we’re addressing marketing; we're addressing the structure of the business in terms of who does what.
We are professionalising our business across the board and bringing in professionals covering marketing, finance and technology. A change in the brand and website which we are considering will be a decision taken independent of AI.
Miranda: How do you think Langcliffe’s approach to AI is different from others in your field?
Mark: It's very interesting to explore whether we're a tech business that uses people or a tech-enabled people business.
The differentiator we have in the market is we're a people business; we deal with people, and we build relationships. What I want to make sure of is that we lead on tech, and nobody will get anywhere near our tech eventually.
Obviously, we’re not going to be able to compete with Goldman Sachs, but I don't want anybody to be stronger in what we do with technology, including AI. The difference is we will always be people-led, and it won't be machines building relationships. It will be people building relationships.
Our strategy is to leverage AI, not for the sake of leveraging AI, but to empower the business to add even more value to these customer relationships and be a people-first business supported by the best technology.
To find out more about Langcliffe’s work, visit their website at langcliffeinternational.com.
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