Just one quick caveat, Nick is in Wellington at the moment that is going through a bit of a wild weather event, if he does drop out, bear with us and we'll get there. With that, Nick, I hand over to you.

Thanks.

Thank you very much, Simon. Here we go again.

Another substantial revenue jump, outstanding metrics, undeniable success in a market where others are struggling. Before we get to the crux of the quarterly numbers and the results, I wanted to take the opportunity today to take a deeper dive into explaining to you how we're getting these results from a technical perspective.

I do appreciate you bearing with me. Practically speaking, when our customers make money, we make money.

Our phenomenal performance is anchored to the fact that we provide better revenue-generating outcomes for customers that they can get by themselves or with any other available technology in the market. The key to creating these revenue-generating outcomes is what I want to talk to you about today.

It isn't just the data. That's important.

It's table stakes, but alone, I can promise you that data does not deliver consistent revenue-generating outcomes. It's not just how we build, sell, and support our products.

Of course, again, that's really important. In my opinion, the biggest differentiator is what the Pearl Engine does.

The Pearl Engine does one thing better than anyone else in the market: it closes the gap between who businesses think their customer is and who their customer actually is at that given moment in time. This gap is where most marketing and sales spend dies, and we close that.

Our AI and technology has been trained to think differently and see patterns of true buyer and seller coherence where others can't see it. It's invisible.

It's not at face value. These are connections that no human would ever be able to find on their own.

Now, in order to help me explain this very complex and complicated function that the Pearl Engine does at scale for tens of thousands of campaigns across almost every type of B2B customer you can fathom and many B2Cs every second of every day, right, we've created a greatly simplified formula about how we go around achieving this. It is just for illustrative purposes.

To be clear, this isn't the actual formula. The formula is vastly more complicated than this, and also, we are definitely not going to be publicly sharing or disclosing our competitive advantage.

To orientate you on the inputs here, R is for revenue outcomes. Note we start with outcomes of making money.

F is the function of the Pearl Engine finding real-time cohesion between buyers and sellers at a moment in time. V is the volume of data, Q is the quality of data, S is the supply-side targeting or how that is focused in on, and T is timing, although I think that can be better thought of as temporal alignment.

Critical to this formula, it's multiplicative. If any input is zero, the revenue outcome is zero.

Now, almost every business we look at or speak to, whether they are a customer or, dare I say it, a competitor, they're focused on the V, the Q, and the S, do you have enough volume of quality data so you can find your definition of your ideal customer profile based off gut feel, based off recency or confirmation bias, right? Accordingly, most people are already out of phase to where their true buyers actually are.

The problem is they're starting with the S, that they're not starting with the outcome, they're starting with their bias. What makes that difficult is that in our experience, with small-to-medium-sized businesses, unless you're uber-niche or super-sophisticated, which is perhaps a percent of the market at best, people really don't understand who their true ideal customer is at that moment in time.

Accordingly, they're already creating filters which are discounting the area where their true customer could be sitting. The next mistake they make is that most businesses are only looking at one side of the equation: their side.

What do I want to sell? Who do I want to sell to?

They rarely ask the harder question, which is what's happening from the buyer side? There are just so many factors to consider, do they even have demand?

Is that demand active, latent, undiscovered? Do they have staff to implement your good or service?

Do they have budget to commit? There's just so many things to bring into that.

Probably most critically, people never ask the question, will that customer actually benefit from what I'm selling? Coherence requires both sides to be true.

That brings me to the last factor, which complicates this formula infinitely, and that's time. Because every day, billions of small events are shifting the alignment between buyers and sellers.

A person changes roles, budgets get cut, a competitor launches, regulation changes, World War III busts out, you know what I mean. These aren't unfortunately rare disruptions.

They're constant. They're a constant.

The landscaping is moving beneath your feet. Let me explain this with actually a real-life example.

It's absolutely the favorite customer example that came across my desk last quarter. It was a Pearldiver customer, and they sold NFL apparel.

They used Pearldiver to create unique marketing audiences to give them a competitive advantage in a very competitive market. Their Pearldiver campaigns initially were focused on creating broad audiences based off buyer-side demand.

They'd got that right, they were thinking about the other side of the coin. Said differently, they were doing advertising through to anyone that had shown interest in purchasing NFL apparel.

That is a big, broad audience. The customer got a modest uplift in comparative to their standard Meta and Google campaigns, which is to be expected if you're running broad-based campaigns using high-quality data.

This is another day in the office for Pearldiver. Then things went wrong.

For those that are not keen followers of NFL, the Kansas City Chiefs have been a dominant team in recent history. Last year they were AFC champions, they were in the Super Bowl, I think they won the Super Bowl the year beforehand.

Accordingly, the supplier over-indexed in Kansas City Chiefs stock on the assumption they were going to have another awesome season. They did not.

They bombed out. They fell out pretty early.

That supplier then had excess of Kansas City Chiefs stock they had to get rid of. They used their gut instinct and recency bias to create specific audience that they thought would be the logical buyers of Kansas City apparel: men between the ages of 25 and 45 in the states of Kansas City and Missouri, which is the catchment area for the Kansas City Chiefs.

Now on face value, that makes a ton of sense. Their results were terrible.

The Pearldiver team were alerted to the fact that the revenue outcomes for that campaign were rapidly declining. They quickly uncovered that the customer had inadvertently narrowed their target audience to a cohort that were no longer in the market for Chiefs apparel.

Right, their team had lost. Why do you want to buy a loser's jersey?

It was dead to them. They figured that out.

Then the challenge was, okay, well, who will buy it, right? This is what they handed over to the Pearl Engine.

The function is to find or identify buyers that are non-obvious to our customer. The Pearl Engine starts with the R, the question is revenue outcomes, who is buying?

It looked at the total breadth and depth of data at its disposal, that's the 31 billion sales and marketing signals it ingests daily, and then it looks for buying trends from different tangents and different perspectives. This is what it's trained to do.

It's the kind of permutations impossible for a human to fathom, let alone calculate. This is what genuine AI does best.

Our team then went back to the client with the solution: "Hey, you've got to change your parameters to females between the ages of 15 and 25, parents with teen girls, focus on the state of California." What?

Crazy, it makes no sense! They made the changes to the supply-side parameters accordingly.

The results were immediate. Buyers had been found.

They were Taylor Swift fans. Crazy at first, but think it through, Taylor Swift's engaged to a star player of the Kansas City Chiefs, she wears Chiefs apparel, Swifties want to be like her.

Swifties do not care if the Chiefs are winning or losing. In fact, I'm sure many of them had never even seen a game.

That is why they're a consistent buying cohort when others fell out. The old way of using data to market and sell has been built on a fractured foundation.

This is what we uncovered and we solved. Unfortunately, the old way is based off gut feel refinement.

The data behind it becomes shallow because you're narrowing down based on what you think, not what empirical evidence proves. Thus, you're only looking at a handful of filters, often stale data, and worst of all, there is a disconnect on what is actually happening in the market right now.

This is why most campaigns don't work consistently: they're ignoring the most important variables. The Pearl Engine solves this by doing two things simultaneously: first, it massively expands the depth, the breadth, and the quality of knowledge behind every identity in real time; and secondly, it is a force multiplier on that knowledge, discovering demand businesses can't see, scoring true coherence between buyers and sellers, and expanding their ideal customer profile beyond what intuition would ever suggest.

The result is that buyers you didn't know you had and revenue you never knew you could generate. Team, this is why customers love our services.

This is why we're growing so fast. This is why we have such great results.

On that note, over to you, Karen.

Thank you, Nick. ARR closed at $26.8 million, which is up 114% year on year and 13% quarter on quarter.

Another quarter of strong organic ARR growth. What I am most pleased about is not just the ARR number, it is the improving efficiency behind it.

ARR per employee reached $346,000, up 41% year on year and 12% on the prior quarter. Our CAC payback period improved again to 3.5 months, down 33% year on year.

Those are clear signals that we are not just growing, but we are getting better at growing. On churn, Data as a Service churn remained at 0%.

This has not moved since we launched DaaS. It is embedded in customer workflows and it stays there.

SaaS churn returned to 4.9%, a meaningful improvement from the seasonally elevated 8.3% we saw in Q3, and down 0.4 percentage points year on year. This is where we expected it to land, and it is consistent with the pattern we have seen in prior years as the noise from the December quarter normalizes.

Overall, Q4 was a strong finish to FY26. Before I hand back to Nick, I want to quickly frame out how we got here and where we are going.

The second half of FY26 was about proving the model. We closed the year at $26.8—sorry, $26.8 million ARR, we validated DaaS with zero churn to date, we brought the CAC payback down to 3.5 months, and we completed the ASX listing and expanded our investor base with top-tier Australasian investors.

The venture model works. That's all done now.

The first half of FY27 is about embedding that momentum operationally. We are focusing on shortening customer ramps and tightening collection cycles, contracted ARR turns into cash faster.

We're tightening our ideal customer profiles, because better cohorts drive stronger unit economics. We're compounding operating leverage, as ARR per employee continues to scale.

With that, it's back to you, boss.

Ha, boss! Far out, promotion.

There you have it. $26.8 million annual recurring revenue and climbing fast.

That number does not happen without AI like the Pearl Engine. It doesn't happen without a team executing across all three ventures simultaneously.

It doesn't happen without the trust of the people that are listening to this call. Now, it's on to $30 million and beyond.

We spent the last year proving we can grow at scale. We've done that again and again.

We're not slowing down. We're getting smarter.

Tighter cohorts, shorter ramps, every dollar of ARR converting to cash faster. That is the discipline that builds a business worth $200 million, $300 million, and as I've said from day one, eventually $1 billion.

With that, ad astra and over to the questions.

Thanks, Nick. Just a reminder, you can submit questions through the Q&A button at the bottom of your screen.

We've got a few questions through from James Besnell at Unified Capital Partners. First question from James: "DaaS looks to be the biggest gross driver in the business at the moment.

Can you talk to the extent of integration and stickiness of that offering versus SaaS?"

I'll jump in on that. I think that as a percent, it remained almost consistent, everything sort of grew in proportion.

Really the key to the integration on that is that it's into the revenue-generating systems of the partners that use it. They're not just using our technology to get more customers for themselves, they're using it to create services or packages which then they go and sell to multiple customers, thus they're generating revenue from it.

In order for that to happen, you're having to make a whole lot of integrations, right, not just their internal systems, HubSpot and billing and all those, but actually what the customer is using to drive their marketing all the way through. It's deeply—like I love the word "inveigled", there's a slightly sinister tone to it, I don't mean it in a bad way, but it gets very tightly integrated in.

Ultimately, and this is the part that hopefully you've got across today, it's generating revenue. That's the game we're in.

Sure, it's technology of amazing AI, but we're in the revenue-generating business. Baby, that is evergreen.

That is why people stick with these products, because it brings money in. There's no greater integration you can have on Earth than make people money, I think.

Question from James: "Just remind us in terms of the average ARR contribution of a DaaS customer versus a SaaS customer, and is the gross margin percentage similar across both?"

I'll take the first half, Karen, you can jump in on the second half. When we think around a DaaS client, I typically have in my head probably around $20,000 U.S.

per month. Now, when you think about even the upper end of the SaaS spectrum, which gets up to 5 grand, you've got a 4x jump there, but typically it's nearer between sort of 1 and 3, you've got grand U.S.

per month. Big change in that, although that gap is closing down with the sophistication of the SaaS offerings that will—again, I don't like "SaaS" as a word, it's dead to me, but those software offerings to retail clients.

As far as margins concerned, Karen?

If you think about what goes into our cost of sales, you are looking at pretty stable hosting and server costs, data costs that are kind of split across all the SaaS products and the DaaS products, they have to be there. The gross margin ends up being relatively the same across all of those types.

Thanks, Karen. Just a question from Michael Ardrey at Bell Potter: "How is cash burn or cash balance tracking, and has the cash breakeven shifted since last quarter?"

I'll start with what I said to the market and let Karen sit that. I said consistent with what I've said.

I said when we get to $30 million by December the 31st ARR this year, I don't expect to be taken out and shot, but maybe a pat on the head. If I get to 35, I expect some beers and everything over that, I expect some great Christmas presents, right?

We're not coming back to the market for cash. They are the constraints that I put on us as a business, and that's the ones that we're operating within, and we have many levers to ensure that we do that.

Karen, if you want to add some more flavor to that, please? Yeah.

I think you can see in the presentation we've talked about closing the gap between that contracted ARR and cash. We are doing that through shortening customer ramp deals, tighter cash collection cycles, and we're acknowledging that as a priority for the first half of FY27.

I think the interesting thing is that me and my team have obviously prepared various growth scenarios based on our proven growth. I think if I show these to Nick, it's super hard to pull him back to go, "Hey, we need to have efficient growth, not just get as much ARR as we can," because based on our prior growth, we can get really high.

We have to turn down revenue in order to use the cash that we have on hand. Going back to the market for another raise is a decision that would require us to look at a number of factors.

Honestly, the current share price is the main factor that we would need to look at. I guess we get a lot of conflicting advice, as you will be aware if you listen to different investors, different shareholders.

Do we go and raise more in order to get that growth that we've proven we could do, or do we now look at, which is what we're kind of saying in this presentation, we know that we can grow, now let's do it efficiently and preserve the cash and work on the EBITDA. That's what we're doing at the moment.

Answered, Karen. Another question from James Besnell at Unified: "You added about $7 million ARR this half versus 3.5 last half organically, and momentum is accelerating.

Any comments on your ability to continue printing those kind of numbers in typical seasonality in the business?"

Typical seasonality is Q3 has typically been really tough quarter for us, we bucked that trend this financial year. Kind of you see that growth, it's because we moved from having essentially one superstar product, Pearldiver, we've went to a venture model, we have three products growing simultaneously.

As Karen said, it's around efficient growth moving forward, not kind of slowing down too rapidly, but closing that cash cycle down. I don't think I'd thought of our comparative growth organically being that much up.

Thanks for bringing that up. That's what we're in the business of doing.

It's why we raised the money. That's what we said we were going to do.

We're just following through on what we said we were going to do. Cool.

Last question from James: "Can you talk to any kind of pipeline and inbounds you're seeing on sales, even qualitatively? AI in particular is accelerating exponentially.

Most of us are in Australia and New Zealand, we don't see it as much. The U.S.

is at the epicenter, any context you can give or provide there from boots on the ground?"

Many ways of answering that question. I'd say that, again, we're in the business of generating revenue.

It's evergreen. I would say that through my decade or so of being heavily focused on dealing with the States, I've never seen small-to-medium-sized businesses struggle more than now.

It is very, very tough. Things that actually generate revenue get really popular.

How we go around that is with AI. I think that there is a huge amount of noise in the market with AI.

I had a conversation with our chairman, Tim Crown, last month. I said I've never seen the signal-to-noise ratio on any technology or anything be so distorted in my business career.

Everyone is so focused about technically what AI can do or what it may do, they've lost focus on how it actually tangibly benefits you from making money or saving money. That's I think one thing we've done bloody great at Blackpearl is as much as we love our technology, it's amazing, it is world-leading in many areas, we've always focused on client outcomes.

When you're focused on creating revenue, you're always going to be really popular with customers. Stunning.

Just a question in terms of customers. A shareholder says: "Fantastic result and a great example.

Thank you. You're doing an amazing job helping your customers, but how do you actually find new customers yourselves?"

The reason our CAC payback period is so spectacular is because we use our own technology probably better than anyone else. If you think of the three kind of challenges in any business is finding potential customers, reaching out to those customers, and then selling and converting to those customers.

Our advertising campaigns across all three ventures are focused on uncovering pockets of potential customers that no one else is looking at, and so the cost per conversion is a lot less. Again, that's a classic example of how Pearldiver did that for the NFL, we're doing that for our products all the time.

Not just the face value, which every other person is going after, we attack things from different things, our cost per conversion is very low. That is aided by the fact that we use agentic AI outreach through B2B Rocket, right, through email, through LinkedIn, that takes out a huge amount of costs of traditional marketing spend.

Then when we have a demo, our closing ratios are spectacular because our sales team short-cutting down research time beforehand because they're basically getting a playbook given to them from Bebop with all the objections, how that customer is going to make money from using our products so that they have amazing conversations and short-cut the sales cycle. We are the best advertisement for our own products.

That's why I like to think. The thing is about it, as great as we are, we continually keep getting better at it all the time.

It's a constant discipline we force upon ourselves, and we see the results accordingly.

Cool. Question: "Reported revenue in the first half was 5.1 with a reported exit ARR of 19.

Does the 27 million ARR exit rate equate to a similar increase in revenue, circa 7.5 for the second half? At what ARR does the company become cash-flow positive?"

That sounds like a Karen question, that one. To be fair, I think that we've got our annual results and detail coming out in a month or so, a lot more flavor there.

Without—

I think once those FY26 full-year results come out towards the end of May, that will give you a better picture of where we're at. Obviously, we don't give out our subscription revenue figures or our cash balances throughout the year.

We're really only focused on giving out the SaaS metrics. I think that's one to—

The thing I'd like to say though is you're talking about the ARR. Where is the cash positive point?

Literally is in a situation it can be today. That's actually a pretty amazing situation to be in when you're running a business, because there's a lot of ARR.

Yes, there's a lag for that cash, but it always catches up. Just depends how quick we want to keep growing.

As Karen skipped around the point before, I may say, when she was running those scenarios, there were scenarios we were comfortably blasting through 45 mil annual recurring revenue by December the 31st, which is why I'm so cocky and confident with the 30 to 35 number, right? It requires different capitalization to get there.

Again, I hate saying SaaS, but the faster the growth, the deeper you go down before you're up. We've just got to operate within our limits on that.

That's something we're very conscious of. I think we do a good job of as well balancing growing as fast as humanly possible with cash on hand.

Do you have any typical examples of clients' return on investment using the Pearl Engine, i.e., four times return on spend?

Different products, completely different examples to that. I think that last time or recently, maybe the last time we did an investor presentation, we talked about some of those Data as a Service customers.

I'm going to stuff the numbers up here, but I think one of them was paying us $20,000 a month, they were making $200,000 a month. I don't need a calculator to tell you that's a 10x return on investment, so that's a really good example of the upper end of town.

The lower end of town is the one that probably in my heart, a little bit empathize with more, maybe slightly more so. The thing is what I love about that is use the example of B2B Rocket, right?

Their job is to book you demos. Yes, their agentic AI agent go out and blah, blah, blah, blah, blah, no one cares how many emails you send or how many opens you've got, they just want demos in their calendar.

For that, the average B2B demo in the States is around a grand. That's what you pay to get a demo booked for you.

They're 5 grand a month at the upper end VIP. That sounds like a lot of money.

If we're getting you 10 or 15 demos, well, we're three-timesing what you would typically get. The kicker is those businesses don't have the outbound sales people and discipline to get any demos.

Actually it's not an apples and oranges, it's apples and apples comparison, is it? You're getting 15 demos when you would have got none.

That's difference for a business between death and prosperous. These are the case studies that I love seeing.

Every venture is measured on outcomes. Pearldiver is measured on the relative improvement for return on advertising investment comparative to your base standard of Meta and Google.

You can see with Bebop, the leads generating, converting and HubSpot or GoHighLevel or wherever the integrations are, you can see with B2B Rocket, literally demos in your calendar and then converting in your CRM. There is no argument at that point.

You're dealing with real cash. We're, again, in the revenue-generating business for our clients.

Two more questions left. What was your Rule of 40 for last financial year, and which direction are you forecasting in FY27?

That's not a metric that we use to the market. It is based on your revenue growth rate and your profit margin.

I think we've kind of talked about our gross profit margin being fairly consistent. I think it's a really hard one to do when you have three different products and they're all at different stages.

A combined one for the group is not a great thing for us. It might be slightly misleading.

Yeah.

Isn't the Rule of 40 based off valuation comparative to growth?

Your revenue growth rate to your profit margin.

Yeah. Isn't that feels like an analyst kind of question coming through?

Surely there's some people on the call that are better educated and experienced to address that than us.

I could have pointed people in the direction of the two research analyst papers that are now out.

Go and look at them.

Perfect. Last question to interrupt you two.

Just in terms of the stock price, it's obviously been caught up in a little bit of the SaaS downturn. Can you just talk to why, whether it's Blackpearl or one of its products, all of its products, will continue to have a significant advantage over, yeah, a Claude or a ChatGPT?

Big question, and I'll address it as thoroughly as I can. First and foremost, what I was trying to do at the start of this meeting is say that really, I know there's a lot of focus on our products and now there's a lot of talk in our data, but the key part is the AI in the middle that we've trained to create revenue-generating outcomes.

That's a real defensible moat for us. Genuinely defensible because it's trained off a pretty powerful data set, but it's also trained off the fact that we own our own products and we get those feedback loops to see if people are making money or not.

That is the whole kind of thing of the Pearl Engine. If you've ever seen the diagram, there's the data, the Pearl Engine, the products in a feedback cycle.

That is a hell of a competitive advantage for us. When you look at traditional SaaS products, they're not AI first, they're trying to catch up to it.

We started this. We started being in the data business knowing that's the fuel for AI over a decade ago.

We are AI first, those business are AI second. A lot of them have got per-seat pricing models, well, that's a disastrous pricing model to have.

We're consumption and outcome-based, not even on the same planet there. The last thing that I want to really talk about, I love Claude.

You have not heard a guy mention the word "Claude" more than me over the last few months, right? Here's a fun fact, something that blew my mind, that if AI innovation stopped cold today, didn't get one little bit better, it's going to take the vast majority of the market a decade to start implementing or to have implemented all the ability that it has today.

The gap between AI innovation and human adoption is widening by the millisecond. The reality of the matter is that 99% of agentic AI projects don't get past pilot.

The huge part is outcome because why? Because they're not outcome focused, they're technology focused, we're outcome focused.

They do not have a human bridge to bridge the gap between the technologies and the outcomes, and we do. These are two massive differentials.

Make no mistake, the better that Claude gets, the better that we get. The better that Grok gets, the better that we get.

Because all those foundational models are part of our technologies. I feel like we are in a magic spot.

We picked this market trend broadly over a decade ago and specifically as far as SaaS is concerned, over 2 years ago. Nothing that is happening today is remotely surprising to us.

The only thing that shocked us is that it took as long to happen as it did. Accordingly, we're strategically perfectly positioned to continue the kind of growth that we continue doing.

Beaut. That comes up to time.

Nick, your Wi-Fi is just holding on, I think, as well. We might finish up there.

Thank you all for joining. This has been recorded and is available via the same link.

Any questions, feel free to come direct to the company, and we'll go from there. Thanks so much for joining.

Thank you.