2027 trading update. From the company today, we have the Founder and CEO, Nick Lissette, the company CFO, Karen Cargill, and the company's CTO, Sam Daish. Before I hand over to Nick to go through the presentation up on your screen, I will just remind you that you can submit questions through the Q&A box down the bottom of your Zoom screen, and we will endeavor to get through those post the end of the presentation. With that, Nick, I will hand it over to you. Thanks.
Thank you very much, Simon. Thank you everyone for joining us for our FY 2027 Q2 update. Well, Q2 was a massive quarter. Black Pearl met its EBITDAF guidance. We, in fact, closed the gap to profitability by 34% in a single quarter. We established our first strategic partnership to underpin our partnership and platform growth strategy, and the Pearl Engine increased its net score outputs 7.7 x with the release of our latest model, RTSA 2. Now, two years ago, I was famously quoted saying that SaaS as we know it is dead. Of course, there will always be value in SaaS tools for a long time to come. But the technology advantage, which was historically protected by development costs, scarce engineering, and integration complexity, can and is getting eroded by AI.
That is why we believe the durable value is moving underneath the application to proprietary data, to specialized intelligence and infrastructure embedded into how other businesses generate revenue. This is why DaaS and PaaS are so important for Black Pearl's future. Accordingly, over the first half of FY 2027, the group's focus has been on revenue quality. It has been on distribution economics over direct sales and R&D in the Pearl Engine over application level. This is what we believe secures longevity of the company. Our goal moving forward is growth of data and platform revenue from a position of profitability without sacrificing our technical advantage. This is what we have delivered on in Q2. Today, we update the market with firm guidance on profitability. We met our EBITDAF guidance in Q2. In a single quarter, we closed 1/3 of the gap to profitability.
We brought our sales, our marketing, our development and customer success teams together across three ventures and pointed them directly at data and platform. This has enabled us to take around NZD 9.4 million in annualized costs out of our cost base. That is roughly 27%. Those changes landed during Q2, so Q2 only shows part of those savings, and from Q3, the lower cost base will be applied in full. We carefully picked our time to execute this. Our Q2 is the U.S. summer holidays, similar to, I guess, Christmas and New Year's in Australia and New Zealand, and that is when buying decisions slow and new customers are harder and more costly to acquire. The group opted not to spend into this and instead invested in launching its partnership and platform strategy. Accordingly, our growth has temporarily slowed because we chose to slow it.
Could we have kept growing while doing that? Yeah. You have to fund growth through equity. It is a capital-intensive game. The market for this has changed. Software again has lost something like $2 trillion in valuation since September of last year. Capital is super dilutive. Raising to buy growth is not, in the board's view, in the shareholders' interest. Our sequence is very deliberate. First, we get to EBITDAF profitability. Then we focused on ramping up growth again from a position of strength on better unit metrics. If we want to accelerate our growth beyond what self-funded profits do, then we will be doing that on our terms. Now, of course, there is another option. We could have continued growing revenue through Q2, but that would have been at the expense of research and development and furthering our technical advantage.
We believe that kind of quarterly capitalism would have been the worst kind of short-termism. We have been proved correct because it is that technical advantage that we invested in that has created our first partnership opportunity and launched our data intelligence onto our first platform with Snowflake. Now, to tell you more, I am going to hand you over to our Chief Technology Officer, Sam Daish.
Hey, everyone. It is great to be talking with you again. Black Pearl continues to be at the forefront of AI for sales and marketing. The advances in general frontier AI are making our Pearl Engine more valuable, not less. Last quarter, we launched the GTM-Bench, our open benchmark for AI systems that do real go-to-market work, and we committed to updating it every quarter. This is the first update. As Nick said, it was a heck of a quarter, and it was a heck of a quarter in AI as well. A new generation of frontier AI arrived this quarter. Anthropic's Claude Fable 5.1 and others is much stronger at reasoning and agentic work. Reasoning is thinking a problem through. Agentic work is planning and then carrying that work out across a whole number of systems.
The jump in capability, it is among the largest lift since LLMs became generally available. It is a real significant step forward. You can see this in our leaderboard. At its best, Fable 5.1 scored over 47,000. It beat our previous system, RTSA 1, our June system. When used with our data layer, it blew away the other results. The previous best frontier model scored 4,000. Fable 5.1 scored 47,000. It is incredible. As I have discussed before, our technology strategy is to build on the advancements in frontier models and apply that to our very specific market of sales and marketing. We take those general horizontal frontier models and build our vertically specific systems with them. As they get better, we get better. This is the strategy that we are executing day in, day out. It is the strategy we executed last quarter.
You can see this right here in the results. Our system went from being about 26,000 points better in June than the leading frontier to over 205,000 points with RTSA. The improvement is phenomenal. Our lead grew from 22,000 to 158,000, and that is the chart that you can see there on the left. You can see the quantum shift there. This is our vertical AI strategy. It is AI built for one domain, in our case, sales and marketing, and built to keep improving. I just want to make that point really clear. It is built to keep improving. The frontier labs are spending billions making their models better. That is going to continue. Meta and Google have started to catch up to OpenAI and Anthropic, and those billions flow through Black Pearl. That billions of investment flow through to us.
Every generation of frontier AI gives RTSA more capability to put to work in our specific market. We test these models on GTM-Bench, and we bring the best of it into RTSA. Then we share those results with you every quarter so that you can know that it is working. We are not building the best general purpose AI systems. That is not what we are about. That is not what we aim to do. We are built for sales and marketing. RTSA 2.0 is the first on the measure mark on the bench by a wide margin. Our customers experience this advantage. They grow their revenue faster with less waste. As Nick said, that is what sits behind the quality of opportunities that are now in play for us. Back to you, Nick.
Thanks, Sam. One of the reasons, in fact, the core reason we actually released benchmarking was not to appease you guys. It was actually because we wanted third-party data providers to try our models. I am pleased to say that is exactly what happened, and that is what resulted in the U.S. distribution agreement that supports our path to profitability and velocity of growth beyond that. For people in the data industry, our benchmarking highlights something of keen interest, and it was not the fact that our models outperformed foundational models by now 201x . It was the fact that when you put good quality third-party sales and marketing data into our models, we make it hundreds of percent more likely in finding a buyer for your product or service. We take third-party data, we make it way more valuable, way more likely resulting in a sale.
This solves a big problem for third-party data providers. If you ask any data provider the number one reason for churn, they are going to tell you that it is because the customers complain that they are getting poor financial outcomes or bad outcomes from bad data.
We heard this years ago as well. In fact, this is what propelled us to accelerate the growth of our models. Now with our models, we know at Black Pearl that it is not so much about bad data. It is more that the wrong data gets used in the wrong way because clients do not know how to take broadly useful data sets and make them specifically useful for them. The example I give, it is like crude oil. Crude oil is super valuable, but you do not want to put that directly into your car without refinement, and data is just like that.
In fact, if you put unrefined data into your marketing engine, you risk burning your whole marketing budget. That is an outcome worse than zero. If that happens, the provider of those data sets risk losing those customers. Again, because of our benchmarking, one of America's leading sales and marketing data providers now works with us to use our models to ensure their customers get maximum use from the data. Let me show you an actual real-life example of this. The file on the left, very hard to see, but it's an actual intent data file. It's a real genuine intent data file, right? Intent data is a data set that implies a business or an individual has interest in a particular topic.
This particular topic is people that are showing interest in the keywords coastal retreats. As you can see, and it's very common when you purchase an intent data set, it's delivered typically as a flat file, like a CSV with the sensitive information being hashed. Accordingly, at best, it's exceptionally difficult or more likely impossible for the average business to take this data set and find out what part is specifically useful for them. This is where our models shine. If we jump, and hopefully the video works, we're trying something new here today. We took this data file, and we put it into our Platform as a Service. This is actually showing you in collapsed time, because it does take a few minutes to set it up, connecting Claude via MCP, that's an API for AI, through to our RTSA 2 models.
It's showing our models on the background, taking that data file, building it up or expanding it out using our 31 billion data points, and then actually using our model analysis to find what the genuine composition of that audience is and how that relates best to the specific client. If we jump through to the next slide, this is the actual outputs, and this is why taking broad data sets and making them specifically useful is critical for success. This customer was trying to push out book now offers for high-end West Coast coastal retreats, that they had a network. It's a tough area to live in because you're competing against Air B2B. I forget the name of it. Help me out, Sam Daish, you're laughing at me. Save me.
Airbnb. Yep.
Oh, yeah, got it. Right, cool. You are competing against Airbnb, you are competing against Expedia.
That is an expensive game. That is why you are looking for a competitive advantage with intent data. When we analyzed this data, we found something amazing. Out of that list, only 34% of those people, and I think it was 270,000 individuals on that CSV, only 34% of them were actually interested in West Coast coastal retreats. You see that big red mark there, right? That is people that were interested in retreating from the coast, or in fact, the largest cohort was that. Again, this is the problem about intent generated from keywords is that technically, yes, that is coastal retreats, but it is not coastal retreats that is useful for if you are trying to book West Coast coastal retreats. That data set is actually useful if you had a removal company from the coast inland.
Secondly, our technology is able to identify what stage of the buying journey you are at. Again, a very unique output. We could see that only I think 35% of the 34% of people interested in coastal retreats were actually at buy now stage. I am going to frame this in the negative and then the positive. If you had taken that raw data set and put that into Meta or put that into Google and said, put buy now offers in front of these people because they have got intent in coastal retreats, you would have burned NZD 0.90 on the dollar. That is your marketing budget gone, and that customer gone. With our technology, you can focus your marketing budget on that elite 10% that are both interested in your specific proposition and ready to buy today.
That is the power of our data, and because of our technology, the data provider is now confident in extending their TAM, their target addressable market, downstream to small to medium-sized businesses and has partnered with us to service those clients. This is not just any old data provider. We are hoping to be able to name it soon and going through all that jumping through all the hoops there. But this is one of America's leading intent data providers, servicing Fortune 500 companies, household names that you know, down to upper ends of SMEs. That during their standard go-to-market, they regularly engage with prospective customers that fall below the minimum commercial and qualification thresholds. These people they will decline today because they feel that the clients do not have the resources or budgets to get proper utility from unprocessed data sets for exactly the reasons you have just seen.
Now, by adding our data analysis offering on the top of their existing DaaS offering, clients can now extract maximum value from those partners' data sets. The partnership deal was great because the partner can now start making money from clients they never could have before. But for Black Pearl Group, this means a whole new channel of customers with near immediate CAC payback. Contracted recurring revenue with a minimum deal sizes being around $15,000 per month, up to $40,000 per month. It is a revenue share agreement where Black Pearl gets up to 80% of the revenue. We manage the clients, we bill the clients, we have the customer relationship. They have 70 deals in backlog and forward projected velocity of between 1.5 to three new opportunities per month.
Obviously very exciting, but I point out this is the first partnership under our partnerships and platform strategy, and it's one shape of several. In this case, the data provider hands us customers that it can't serve itself. There are other examples we're actively working through, where the partner will keep the customers and embed our data intelligence inside their own product. So thousands of users are getting better outcomes, but they won't be seeing our name. Different structures, similar economics in the sense that we're not paying to acquire customers like we have been in the past, because the partner carries the distribution, and our data gets better with every customer it touches. Very exciting for us. The partnership and platform strategy has enabled us to optimize our cost base accordingly, doing this without sacrificing R&D or mid to long-term growth.
To talk to you more about that, I'm going to hand you over to Karen Cargill.
Thanks, Nick. Q2 was the quarter we changed the shape of this company's cost base. This chart is the quarterly cost base from Q4 FY 2026, which was our peak. In total, we have taken around 27% off compared to Q4 FY 2026. That's around NZD 9.4 million annualized savings. These changes landed during the quarter, so the Q2 and half year interim result only reflect part of the saving. The lower cost base applies in full from Q3. The box on the right shows where these cost savings came from. Two structural changes, and both are permanent. The larger is our go-to-market model, a lower cost route to market through partnerships and self-service. The second is acquisition integration. Duplicate roles across the three ventures were removed rather than redeployed. Importantly, we've done this without cutting our ability to grow.
We've kept the capacity to service the partnership pipeline, and none of this has come out of the Pearl Engine. We've protected R&D, and Sam's slide earlier shows the result from the GTM-Bench. What I'd underline is that none of these costs we've removed depend on revenue growth to hold. These are decisions already executed, not targets. A lower cost base combined with partner revenue that carries high margin and a low cost to serve is what puts profitability within reach. Earlier, Nick talked about how our focus of half has been on distribution economics over direct sales. This slide is what that means in numbers, because taking NZD 9.4 million of annualized costs out of the company only works if we change the way we grow. On the left is how we grew previously. Every DaaS dollar started life as a SaaS sale.
It took four months of acquisition cost to win the customer and at a 30% cost of sales margin, that's 5.7 months of revenue before we have recovered what we've spent. The revenue ramps over about 90 days and sits on 45-day payment terms. So that's another 4.5 Months before the cash is fully in. All of it funded up front by us. That is a model that consumes cash in order to grow. It is also why significant sales and marketing investment was not optional. We were buying the only go-to-market channel we had. On the right is what has changed. Partnerships bring us customers. The partner is paid through a revenue share, so there's no upfront acquisition cost and payback is immediate. Self-service lowers the acquisition costs on the SaaS we sell directly and recycles the cash faster.
Centralization reduces fixed costs out, and it shifts the investment to DaaS and PaaS, where the higher margin is. Pricing. Some customers were simply better suited to flexible plans and have been moved to variable consumption pricing. It benefits how they use the platform, and it means that revenue moves with usage. The result is a business that recycles cash faster, carries less fixed cost, and has its revenue weighted towards DaaS and PaaS. With that, I'll hand back to Nick.
Thank you, Karen. All right, let me close out on the position from which we grow from. We went into FY 2027 with a go-to-market that was still heavily weighted towards our applications, a high-cost base, and sales cycles which had increasingly long cash payback periods. We come out of the first half of FY 2027 with a substantially lower cost base, a model lead that's widened 7.7 x, and U.S. distribution partner bringing us customers we don't have to pay for to acquire. Guidance has been met, 1/3 of the gap to profitability closed, and a firm date in the calendar for profitability. We've quietened the noise that we'd created for ourselves by driving revenue from three separate applications, moving them to self-service, and unifying the group's energy and resources on where we believe the deeper defensible value lies.
Proprietary data, specialized intelligence, and infrastructure embedded into how other businesses generate revenue. Our goal is to grow that data and platform revenue from a position of strength, which we control. That is what we did in Q2. Thank you for your continued support. Ad astra, and over to you for Q&A, Simon.
Great. Thanks very much, Nick. We've had a number of questions that have come through, and we'll do our best to group them up. If we don't get to any, we'll commit to coming back on email. First question, when does management expect Black Pearl to become sustainably cash flow positive? What level of revenue is required to achieve this without additional capital?
Yeah. As we've projected out, it's Q1 FY 2028. For people not operating on the New Zealand financial year, that is between April and June, next year. Second half of that question. Yeah, that's the timeframe that we've put out for that. By the way, with us, EBITDAF is a reasonable proxy for cash as well. I think you asked about cash.
Right. Thanks for that, Nick. A few questions just on the partner program. Maybe first of all, who is the partner, and how should we think about this in terms of being a repeatable program?
Yeah. We're working very hard with that partner on a suitable disclosure. They're a substantial partner, so there are some intricacies there we're working through. But expectant on being able to disclose the name. Very repeatable. What's been super interesting for us, and talking about the fact that it's like, really what we're experiencing at the moment is technology-led distribution opportunities. There is actually several in flux at the moment, paperwork out for another one last week. So very, very repeatable. Not just at those big third-party data providers, but anyone that has multiple customers that rely on data to drive outcomes. That's a lot of businesses for sales and marketing. Everything from CRMs to outbound email agents to martech tools, all those sorts of things. They're the kind of partners that we're engaging with. So very exciting.
Great. Thanks, Nick. Just on the U.S. partnership, when do you expect, I think you mentioned about working hard on the agreement, but when do you expect it to be signed, and how many of the 70-plus referred companies are contracted and paying as of today?
None today. We're expectant of having the ultimate agreement executed this week, and then we move to immediately looking to move over as many of those existing opportunities as we can. One of the things that should be pointed out as well, is that we didn't take all the costs out last quarter that we'd initially anticipated we may. We've left additional costs then to ensure servicing of customers if we get a substantial volume out of the gate.
Great. Thanks, Nick. Maybe one for Karen. The second quarter revenue was down on the first quarter, the first quarterly decline. How much of that was churn versus the pullback in marketing spend? Should we expect revenue growth again in Q3?
That was mainly due to the pullback in the marketing spend, not the churn. In Q3, yes, hopefully, we will be getting a lot more revenue than we had done in Q2 with all these partnership deals coming through.
Perfect. Thank you. Question just in terms of, has the gap between ARR and subscription revenue narrowed?
Yes. It is narrowing, but important thing is, reason why we are moving away from annual recurring revenue as one of the numbers we talk about, you will note that we are retiring that out for a number of reasons. But Karen pointed out, we reclassified a portion of the annual recurring revenue, at least temporarily as, what is it called? Consumption-based or variable revenue. A really good example to that is with B2B Rocket. With B2B Rocket, you are selling an agentic agent whose job is to book you demos. The amount of demos we book is kind of the factor on how much value you can charge for a customer.
When we moved to their new model at the start of this year, you are trying to guess a future value for how many demos you can book for a particular client, and obviously how niche that product is and how good their value proposition is. All these factors outside of our control will dictate where the glass ceiling is. Rather than counting that as annual recurring revenue up front, we treat it as variable revenue until we see where the value kind of caps out for that client. Once that is maintained, then we move it over to annual recurring revenue. Again, that is all part of the fact that we have felt, again, it was not just us internally, but when we were doing our previous updates, there is a big gap between annual recurring revenue and actual revenue. We call it internally ARR and AFR.
You can guess what the F stands for. This is why we have gone to just reporting statutory revenue. Money is money, but yeah, we do have forward revenue that we expect flowing through from the hard work we have done in the past.
Great. Has there been any further DaaS churn?
Not that I'm aware of. Karen, do you want to weigh in on that one?
There has been no more than the one we've had.
Thank you. Maybe one for Karen. What was gross profit percentage for the first half?
Well, it's always been between 65%-67%. The final one will come out with the interim report, which will be released in four to five weeks.
Great. Thank you. To what extent does Black Pearl use its own Pearl Engine AI technology to identify potential customers, generate leads and grow its own business? Have you measured improvements in your own customer acquisition costs and sales conversion rates as a result?
Obviously, we rely on our technology heavily. The reason why we've now got calendars booked with some of the CEOs of partners that typically anyone else would salivate over is because we're using our own technology. Also, as we've moved the applications to self-service, obviously again, we are bulk identifying businesses that have intent, need budget, and ideal customer fit for each of our applications, and then using the B2B Rocket technology for mass push out on those. So absolutely using our own technology there. We've seen a huge improvement with output, and that's just not us, but actually just feedback from clients, even speaking with one last night on just how good the outputs are. So it's really interesting when you see that, Sam talking about that 7.7 x greater. He actually articulated that to me differently.
He said that essentially you're going to be getting 20 good calls before you have one bad call. Sam, did I get that right or have I done your framing—
Yeah, no.
This just is—
Yeah. You certainly did.
Yeah, because if you've ever had to pick up the phone and cold call someone, and that's how some of these prospective customers or businesses or partners are now looking at doing it's like not just used for marketing, it's used for account-based marketing, which is the glorified name for picking up the phone and doing the hard work. If you've ever done that, calling bad numbers, calling bad fits, this is what costs time and money in the sink. The fact that you now statistically get such long runs before you get a dud, you know what I mean? Again, the feedback we've got is very immediate from customers and seeing the improvement for the outputs, which is really exciting to see. We see it internally, but I care greatly about customer outcomes, and they've been phenomenal.
Thanks, Nick. Whilst noting we don't release cash figures until the half, which I think Karen mentioned is in four or five weeks under the NZX rules, maybe if you could just talk to just how sustainable the business is in terms of whether you would look to reduce cash expenditure to be sustainable and how that looks going forward.
Yeah. We always make sure we've got optionality. I hate talking about this because this is a loser mentality, but can we always cut costs today and be profitable? Of course. But are we going to be able to maintain a strong technical lead in the mid to long term? No. Are we going to be able to move back into aggressive growth phasing again? No, right? No one here invested in a corner dairy. I don't know what that is if you're from America or maybe Australia, right? Look up what a New Zealand dairy is. That's not what this is about, right? We're dealing in small to medium-sized business market in America. There's 36 million businesses. We're going upstream in that market. There's still millions of businesses.
We have huge upside opportunity and a rare moment in time where we have such a huge technical advantage over the market at a whole, that it's beholden on us to seize those opportunities. So we look for the best paths to protect shareholders, value today and value in the future. We navigate that each and every day. But the quicker that we get to profitability, the quicker we run things on our own terms. But we just don't want to be taking away forward opportunity in the path of doing that.
Right. Thanks, Nick. Probably just last question, and any others we'll come back on the email. But just in terms of management share purchases or board and executives, just given the current share price, does the board and management view the stock as undervalued? Are you considering purchasing shares on market when trading restrictions permit?
Well, I heard on the New Zealand shareholders forum that someone was expecting me to drop some F-bombs, and it feels like you're baiting me with that question around where the value of our stock is at the moment, Simon. But I'm a mature adult, and I know when to bite and when not to. I can speak about myself. I think I got another 110,000 shares a month or so ago at a higher share price than it is now. And I consider that exceptional value. I only speak for myself, and that's what I think about that.
Perfect. Nice and punchy, Nick. That concludes the webinar and the Q&A segment. As mentioned, we'll come back on the email to any unanswered. But Nick, I might just hand it back to you for quick closing remarks.
I've got to learn on this one, Simon, to have a really epic power statement, but I sort of shoot all my shots during my speech, and then I'm kind of stuck here with nothing to finish up on other than thank you for everyone for your continued support. I think we've made hard calls the last quarter. None of those decisions were easy, but I know that we can look ourselves in the mirror and know we made the right decisions. It might not feel like it today, but it is the right decisions if you want to not just survive but thrive in the fastest evolving industry in human history. This is the sort of bets that you have to make, and we're already seeing them paying off. So we made the right calls.
It was a tough quarter, but we've done the right thing and plowing ahead bloody efficiently. So thank you, everyone, for your support. Looking forward to sharing some more frequent updates on both the partnership agreements and relevant successes coming from that during this quarter.
Thanks, Nick. Thanks all for attending.