Thank you, Andy. Good morning, everyone.

Thanks for joining us on our Q2 2026 conference call. With me today, as usual, is Mo Ashoor, our Chief Financial Officer.

As we do each quarter, we've published a CEO letter alongside these results. It's available on our website and filed on SEDAR.

I'll be covering key themes from that letter today. Q2 was another quarter of disciplined execution during what continues to be a deliberate transition year.

Our first half was really about building more of the AI-enabled capabilities across our service catalog, put it in front of clients, prove it works in production, and the Q2 results reflect that. The underlying work of converting our catalog and our people to an AI-augmented delivery model reached a number of important milestones.

Going to talk a bit about that today. Let me start as I have been lately with a quick reminder of what Pivotree does and why the market opportunity ahead of us is significant.

We really are technology services firm that helps our clients drive towards a frictionless buying experience for their customers. We help enterprise clients get the right data in the right format into the right systems, and increasingly, that is at AI-powered speed and a fraction of the traditional cost.

That market shift we're seeing really is profound. Client conversations are moving from "should we invest in AI?"

to "how do we deploy AI against specific outcomes on top of our data?" That is exactly the conversation where our domain expertise, what we call that real intelligence, is the most relevant.

We're not applying AI as a buzzword, but as a practical accelerant. It's a tool.

It's a very powerful tool. It's on top of decades of accumulated domain knowledge in commerce platforms, data, and integration.

RI and AI is our operating philosophy for 2026. Ultimately, the benefit for our clients is we are delivering services that are better, cheaper, and faster than ever before.

We're really actively preparing our clients for that agentic future of commerce. Let me show you a little bit about what that means.

Going to give you a specific example. Again, part of the reason I'm sharing this is we get a lot of questions around "explain what you do," and I think probably the easiest way to explain it is to use a customer example.

A specialty retailer came to us running its product data across categories as different as automotive parts and food. They were doing it on a homegrown system they had outgrown.

We started by building them a proper governed product data platform and cleaning up the data underneath it. That work is still underway.

This started at the end of last year. The kind of work we've done for many years.

Now here's the really important part of the change that's going on. The same client was in the early stages of overhauling its entire technology stack, legacy systems that all needed to connect to each other, getting data to the right systems.

They initially planned to do the integration work themselves with another partner. When the real scope of that became clear, neither their team nor their partner could handle the speed they needed to get it done in and the complexity, they came to us and asked.

We didn't win that business just because we had a good relationship with them. We won it because we could show them exactly how we'd deliver: on time, with quality, at a competitive price.

Again, the kicker here was we used our AI capabilities to show them a really accelerated delivery time frame and how we would do this with AI POCs. This is the new economy.

It's a "show me, not tell me" economy. We could show them.

Now we're building and running 140 of those integrations restructured into a multiyear AI-powered service. It wasn't just build the system that would move the data, it was manage the system using the same AI scaffolding we used to build it.

This is where I want to be precise: AI was accelerating, cutting the design, the build, and the QA time by 50% to 70%. It's not a marketing number.

That's what our delivery team is actually seeing on this account. Given the really aggressive time frames that the customer needed this done by, you couldn't do this manually.

You couldn't throw enough people at it. In fact, quite often putting more people on things ends up slowing them down.

This was all about our capability accelerating our ability to get this done quickly and effectively. What started as a one-time million-dollar engagement is now over a $3 million deal.

That's really about how we land a customer with some of that capability we have and then expand it through all the capabilities we're building now with AI. This is really grounding who we are and how we deliver.

Again, real-world example, but let me talk about how that came about. We're really working our way through transforming our service catalog.

It's not a one-time initiative, it's a sequence we run continuously. Now it really started last year with enabling our workforce.

This is true for everyone in our industry. We had to take our workforce and build those extended capabilities: training, tools, process, work to discover who our force multipliers are.

Those are people. Our force multipliers are those real intelligence folks that we now enable with AI.

Then those force multipliers build new processes. They prove capabilities internally.

They document the outcomes before we ever take them to a client. From there, we demonstrate those capabilities to clients and prove the outcomes in their environment.

That's when we begin delivering with the new capability live. Again, I think what's really important about our transition, unlike some of what you hear in the world of AI where lots of failed experiments, our experiments don't fail.

These are people that are transforming existing known processes using AI to heavily automate and accelerate them. Because these folks really know their domains well, when we teach them how to use AI, they're able to leverage the tool to automate their process.

They're not really inventing anything new, they're just doing something they already know much better, much faster, and ultimately, for our customer, cheaper. Once we have that capability, we prove it works both to ourselves and to our clients, we really now have to establish an effective go-to-market new capability.

This is all going on at the same time our customers themselves are going through an AI adoption journey. This is happening across the industry.

Everybody is exploring and trying to understand how to effectively apply AI. We're doing it in our catalog.

Our customers are starting to expect from all their service providers they want things better, cheaper, faster. They still aren't all aware how to leverage AI effectively, and there's an important relationship that has to happen.

In developing those capabilities, customers have to have their own capabilities in this front. If they're not able to handle the speed of AI, the whole process breaks down.

This is again a journey that's evolving where both client and service provider have to be working at the same pace. Really now the key is all this has to show up in our pipeline.

As we go through this go-to-market motion as customers begin to understand what to ask for, how to ask for it, how to accept and work with it, this starts turning into added pipeline. When that new capability starts pulling qualified opportunities in pipe, that's our earliest signal that the go-to-market motion is working, well ahead of it converting into bookings and revenue.

That's what we're seeing right now. We called it out in the letter.

We called it out in the PR. It's also why we think our pipeline is probably the strongest it's been.

We had one of our biggest pipeline add quarters in almost two years. We're seeing the early signals.

Now, again, pipeline is an early indicator of bookings. Bookings is an early indicator of revenue.

All these things have to convert in order to get to revenue growth. This is, again, what we're seeing.

We're starting to see that pipeline build. Against that backdrop, if you just put it into numbers, here's what it's telling us about the state of the transition.

In order to get to these capabilities, we had to transform our workforce. So 100% of our workforce is now AI-enabled.

They've completed basic training, 63% of them are using it daily in their roles, ahead of our Q2 internal milestones, and we have quite a few that have moved into advanced use capabilities. These are our force multipliers.

Our Q3 focus shifts to building the next tier of advanced practitioners. We want everyone in Pivotree to become a force multiplier.

That enablement has turned into 22% of our revenue this quarter had a AI enabling it, 33% of PS revenue was AI-enabled in the quarter. Just to show you how fast things are moving, by the time we got to June, we were running closer to 50% of PS being AI-enabled.

Based on what we see in the pipeline and the current transformation process, by Q3, more work will be done with AI than not. I expect by the end of the year, very little in our catalog won't be AI-assisted.

Over the next 24 months, the actual percentage of work completed by AI will keep climbing towards the majority. While a lot of transformation has been in the delivery of PS work, the foundations of the scaffolding put in place to build PS with AI, it forms the basis for ongoing AI managed services.

We've now launched eight new or transformed AI-enabled services so far this year with only a handful of legacy offerings left to convert. The shift is already showing up in the top line.

So 22% of our Q2 revenue again came from AI-enabled services as we're measuring it today. We expect by Q4, everything we sell will carry an AI-enabled component or be completely deliverable with AI.

We ended the second quarter with $13 million of cash. The reason I raise this is this is up $600,000 in the quarter.

It's the highest cash balance we've held since the first quarter of 2023. That's including spending $400,000 on an NCIB.

What this keeps reinforcing is the discipline of the management team, that this group has retooled the org, created all kinds of great capabilities, is starting to show real benefit to customer through the R&D work we're doing. Through all of that transformation, they continue to show they can build cash.

Again, I think what's really exciting about this is the optionality on what we're building, and we're funding it ourselves and we're producing cash at the same time. I think this is a team that's worth betting on.

I'm going to transition this to Mo to take you through the detailed financials.

All right. Thanks, Bill.

We'll talk through the financials. I'll start with our bookings for the quarter.

Total bookings was $12.5 million in the second quarter, and excluding LMS, MEPS and PS bookings was $10.6 million. That was up sequentially quarter-over-quarter 18%.

Let me talk about the MEPS bookings first. So $3.6 million in the quarter.

I'll highlight two kind of keynote contracts and that helps illustrate some of the success and the strategy behind what we're doing and how we're going to continue to drive recurring and sustainable growth. We closed a contract with an existing Fluent Professional Services customer.

We stood up Fluent, and we extended our services now to managed services to help support their Fluent OMS. We also closed a three-year contract, and this three-year contract was to optimize the client's technology roadmap and assets over that period of time.

That's aligns well with our strategy, and that three-year contract is off of our AI capabilities, which the customer saw and just saw confidence in our ability to help them drive their roadmap over the next three years. Professional Services bookings were $7 million, and that's driven by a reduced volume of new system implementations as we experience customers pushing out decisions.

We still remain optimistic. The conversations are continuing, and these opportunities are still live and available for us to continue to pursue in the market.

The LMS bookings was $1.9 million in the quarter. Again, whenever you see this, is largely on renewals with existing customers.

As this customer base continues to shrink, there are a few remaining customers that look to extend the life of their legacy technology. Obviously, with that booking, do not expect that to yield revenue growth, and we expect this business to continue to decline over time as they transition away from those legacy technologies.

As we all know, and Bill touched on it, pipeline is a good leading indicator into bookings and future revenue. We are encouraged by what's in our pipeline and the ramp-up of activities and conversations that happened in the quarter and going into Q3.

As Bill mentioned, this was our strongest pipeline building quarter in almost two years, and we view that as a positive leading indicator into the market and the opportunities out there. Let me shift to revenues.

Total revenue was $12.6 million in the second quarter. MEPS revenue was $3.5 million.

The decline is attributed to the completion of a SKU enrichment project. As we mentioned on prior earnings call, we had a ramp-up of SKU enrichment.

The customer came to us, they requested faster completion of the SKUs than we originally contracted, and we applied our automation to exceed that expectation and complete that program in Q2 of this year. As a result, this ramped up our revenues, and you can see that in the bar chart in the dark blue, and we started to ramp down in Q2 of 2026.

That's the primary driver behind the MEPS trend that you see in this chart. If you exclude that program, that SKU enrichment program, the underlying MEPS revenue delivered modest growth quarter-over-quarter of roughly $100,000.

Our legacy managed services business continued decline year-over-year to $1.6 million. That's entirely consistent with the continued fully anticipated wind-down of our Oracle ATG customers.

Professional Services was $7.4 million, reflecting the completion of system integration projects across our categories and the result of a slower year-to-date bookings for our Professional Services. We expect near-term revenue moderation.

We deliberately are looking to convert our PS to outcome-based PS with AI-enabled managed service structures as we built our service catalog to support. That's the right trade-off for the long term.

It improves revenue quality, it improves margin and durability of our customer relationship. As we mentioned, this revenue trend is largely predicated on bookings and converting pipeline to bookings.

We have the pipeline of opportunities. It's really focus is on closing them.

Reporting the bookings will be the first leading indicator to turning around this revenue trend that we see here. On to profitability.

Gross margins was 46.9% in the second quarter, and it's up 70 basis points year-over-year, and we continue to maintain the improved margins over recent years. That improvement reflects the cost efficiency of our Professional Services delivery, the discipline across our cost management in MEPS, LMS, and as LMS winds down, and the continued leverage of automation and AI as well this year.

We continue to structure this organization to generate positive adjusted EBITDA. Our adjusted EBITDA was $900,000 for the quarter, 7.2%, compared to $1.7 million in the prior year and 10.1%.

The decline reflects the revenue contraction, obviously, while we optimize our operating expenses, and we are still continuing to maintain spend to focus on growth initiatives. Adjusted EBITDA excludes a $600,000 restructuring charge that we took in the quarter.

In reviewing net income, the prior year comparable of $2.4 million, let me address that first just to set a reminder. $2.5 million, that included $2.4 million from the sale of our WMS business, which you can see from the gray bar on this chart.

Normalized and adjusted to exclude that sale, the comparable period produced $200,000 of net income. During this quarter, Q2 2026, we reported a net loss of $400,000, and that included a $600,000 restructure investment.

When adjusting the comparable for the divestiture and the one-time restructure investment to support future profitability and growth, the year-over-year comparison is less dramatic. We will continue to manage this business in a way that considers future profitability and maintaining the healthy balance sheet we have in place today.

With that, let me move on to the balance sheet. We ended the second quarter generating cash and closing with a balance of $13 million, which is up from $8.6 million in the prior year.

Cash flow from operating activities was $1.2 million in the quarter, up from $700,000 in the prior-year same quarter, reflecting an improved pace of collection on our trade accounts receivable. In Q2, we repurchased 241,000 common shares for approximately $400,000.

In the six-month ended June 30th, 241,000 shares for $400,000. We'll continue to look for opportunities to buy back shares through our NCIB, but while also considering the cash balance health.

In addition to our $13 million cash balance, we have no long-term debt, we have access to an undrawn secured line of credit with a national bank, plus a $15 million accordion to support any future acquisitions. With that, I'll turn it back to Bill for our strategic priorities.

Thanks, Mo. Q2 was our strongest qualified pipeline building quarter in almost two years.

It's a leading indicator we watch closely. That's only one quarter of strong pipeline adds, it's a little too early to call it a trend.

Key here for revenue growth is converting that pipeline into signed, delivered bookings, and that's our primary focus for the second half. Again, I really want to focus in on our transformation.

This is really about getting the mix shifted towards AI-enabled higher-value services that's real and that's ongoing. It's that real intelligence that force multiplier, again, that strongest pipeline build in almost two years, and we're moving fast without burning cash.

Now, again, I want to set realistic expectations. You'll continue to see some volatility in our reported numbers as we move through the transformation.

MEPS bookings continues to be lumpy, but more of what we're seeing now with the MEPS is actually the managed services on top of AI-built PS, and I think we're going to start to see that level out a little bit instead of being quite as lumpy. They tend to be three-year managed service contracts, they aren't these big balloons like in our SKU enrichment.

I think we'll start to see this level out a bit. We're investing to transform, but we're choosing to do it with discipline.

Again, I think you'll continue to see us managing our cash balance very carefully. This is a team that's moving fast, but doing it with discipline.

I'm really excited to see how AI is transforming our industry, transforming value to customer, and helping drive our transformation to some really differentiated services. I think this is going to be an exciting second half.

Over to you, Andy, to manage Q&A for us.

Hi, good morning. Thanks for taking my questions.

My first one comes around the qualified opps that you spoke about in your commentary. I'm just wondering if you can get some color around were they specific products or services, types of customers, just a little bit more detail on what you're seeing in that.

Thanks.

Sorry, you cut out for a sec there. Which opps, Daniel?

Your qualified opps that you mentioned.

Oh, in the pipeline adds?

Yes.

Honestly, it's the same stuff we've been doing for years. It's in our data, it's in commerce, it's in integration.

We're seeing a lot on the integration side. Probably our most advanced set of capabilities right now is what we can demonstrate we can do on integrations across multiple platforms with AI.

That's probably been the biggest qualified pipeline build out of everything. A lot of it is existing customers.

We had another good pipeline build of new logos, but again, those are the hardest, they take the longest to convert. Our existing customers are really consuming more of our AI abilities across the things we've been doing.

It's the same folks: retailers, complex retailers going through transformations, AI-enabled integrations embedded in almost all of them. A lot of data continues to be, again, the key theme.

Everybody recognizes and realizes data is the foundation of commercial transactions, but it's also the enabler for AI. This is not something we have to evangelize, everybody knows and understands it.

When you show up with some tools and capabilities, then you usually, at the very least, get the meeting. Then you've got to turn it into evidence that it can add value for the customer, and that gets you to your bookings.

Thanks. Then moving on to just the AI enablement that you mentioned, I was curious to hear what's the low-hanging fruit in terms of AI products and services that you're able to monetize versus that longer-term roadmap or I don't know what's long term these days, medium-term roadmap, let's say, of what we wish we could do with AI at this stage, just any specifics on where the rubber meets the road in terms on that front.

I think that's a really insightful question, Daniel. I would say the reason we're having success today is because the AI we're using is enabling an existing process.

A customer who knows they have a data problem, a product information management problem, it's the similar problem solved in a modified way. It's not hard to explain.

You can demonstrate evidence of moving quicker to deliver that result. Think about it as an improved or augmented existing known process.

I think the reality is everybody in the market that's having success is having success modifying known processes. I think where things start to get tricky, and to your point why three years from now is hard to predict, because AI actually has the ability eventually to replace that process, eliminate the need for that process, change the way the human's going to work in the loop.

A lot of the processes we're automating today is so people can work in these systems. When you start to think about the future where AI becomes more agentic, starts making decisions itself, you won't be rebuilding these same processes.

Again, I think this is an evolution we're on with our customer: show them how AI will solve today's processes, but as you build the scaffolding of this AI infrastructure, it really then becomes solving the process problem in an entirely different way. We are starting to see that with a number of the customers we work most closely with, our most innovative customers partnering with us.

We are starting to look at brand-new processes. Again, we don't call them out as much right now because I don't think they're going to be big revenue drivers in 6 to 12 months, but they will be the transformation that everybody keeps hearing about.

I wish I could tell you when that's going to happen, but my guess is, it's 24, 36 months from now, we start getting into wildly different processes as a result of AI. Appreciate that.

Then

that question leads me to think about just the improvements in using AI and adopting AI, just where that line is drawn between you as kind of a service provider versus the customer themselves implementing, especially a large enterprise. How are you thinking about that roadmap as you think about making sure that you could monetize the solutions you're building versus people building things in-house?

It's a great question. In fact, part of what we're trying to do is help our clients establish the scaffolding, the capabilities, and then start teaching and showing them where they can build some things on their own.

Where we see the greatest value is in how you take a converted process and enable it for production. That's the managed services we're describing.

I think building things is becoming the easiest thing people can do. What becomes harder is managing it, securing it, governing it, keeping track of it.

We're moving almost to a state where we're building disposable code on a regular basis. It can create a lot of clutter and can create management confusion.

There's still going to need to be folks that help our clients organize their technology because again, most of our customers aren't technology service providers. They're retailers, they're manufacturers, they're distributors.

Staying on top of all the latest capabilities in technology isn't what they do, and nor do many of them want to make those kind of investments. I believe there's always going to be a role for a service provider, but the key is you will have to stay one or two steps ahead of your customers to be valuable to them.

If you're not moving faster than them, if you're not embracing the latest tech and enabling them to use it, then you become redundant. The key, I believe, is stay ahead of them because this is still moving quickly, help them organize, manage, govern, and secure.

Again, I think you're going to see us reverting back to some of our history of managed services. One of the things that does differentiate us from many other service providers, we have a history of managed services, which is securing, monitoring, governing, creating visibility into what's going on in your tech stack.

We were doing that for years, even before we really started to get into Professional Services, and that's what we're starting to see a return to: help people build things, but ultimately, help them manage them.

Interesting stuff. Last question for me, maybe just one for Mo here.

I was thinking about the dynamics you're describing on the top line, wondering how you're thinking about that inflection point growth if anything has changed since we last spoke, and then kind of a similar story on the margin profile, how you're thinking about directionally where that trends to as you work through a legacy business and these kind of AI growth initiatives in the pipeline.

Look, I think with the bookings that we had in Q2 with the PS kind of recovering from the kind of low point we had in Q1 of PS bookings, that helps stabilize, that helps our PS kind of recover some of and kind of stop some of the declines that we've seen. I think part of the strategic kind of path with PS is I think the value is in the long-term relationships where as we get into conversation, how much of the PS do we essentially kind of use as investment vehicle to get into the long-term, intelligent managed services programs that are, again, more recurring in nature, longer-term relationships that might take an impact on PS revenues, but it helps drive PS growth.

That's the trade-offs that we're continuing to work with, and some customers are very excited about those type contracts and the value that we add over three years. That's kind of the revenue profile.

PS somewhat stable now with the bookings that we had in Q2, and then really how do we leverage that channel with our customers, new and existing, to support the MEPS growth. That's been our focus.

From a margin perspective, at times, we are investing margin in PS to be able to secure the longer term, which will be stronger margins in our MEPS and then our overall business as the weight shifts to MEPS and our AI-enabled managed services. For now, I'd say short-term, steady margins.

I think we're producing strong margins versus where we've been in the past, and the margin acceleration is as we ramp up the MEPS, which should all be generating stronger margins versus what we've seen in our reports.

Thanks for taking my questions. I'll pass the line.

Thanks, Daniel.

Hey, good morning. Maybe just going back to the pipeline build, can you just contextualize maybe that pipeline build over what you would have seen in recent quarters or last year and just any further commentary there would be helpful.

I'd say there's two parts to it, Gavin. It's the largest by quite a margin in terms of qualified pipeline adds.

What we look at isn't just leads coming in, we look at qualification, it's the usual BANT. It was sizable this quarter, again, the biggest we've seen in quite some time.

We're seeing positive continuation of that in Q3 as well, we don't think it was just a one-off. The qualifier I'll put on it is we're using AI, as I mentioned, in a lot of our delivery.

A lot of the pipeline we're seeing still has room for more evidence for customer of benefiting from the AI. Said a slightly different way, I think what we've seen is just a little bit of a return to the old days.

People seem to be buying again. Again, I'm hesitant to say that's a massive continuous trend, but we are seeing more activity, and I wouldn't say all of it was AI sales motion.

Our pricing, our delivery, how we try to win these now are going to be affected by our AI capabilities, but I wouldn't say what brought them in the front door was the AI. To me, that's a great trend.

If the pipeline is growing not because we've been blasting a better, cheaper, faster message, but rather because the problems are real, customers need solutions and they're coming to us again in large quantities, our opportunity to win now is going to be enabled by this message that isn't necessarily what drew them in. My belief is that message is also what's going to drive the future of our pipeline.

I think there's a little bit of a tailwind that picked up this quarter. Obviously, my hope is that tailwind is sustained, but we don't control what is going on in the industry.

I'm sensing some optimism.

That's great to hear.

Yep, go ahead.

Good to hear. Just on the sales cycles lengthening, you've been talking about it for a few quarters, what commonalities are you hearing on the root cause from clients?

Is it still trying to determine what the roadmap should look like, is it overall budgets, how they allocate the budgets? What are you hearing from customers?

I'd say two things. One is the overarching 24-month trend of everybody, including us, is focused on cash.

How do you produce it? How do you produce more of it in an economy like this?

It's got an uncertain feeling to it, every deal you're working on is being heavily scrutinized for ROI. It's probably the biggest theme for the last 24 months is business cases.

That continues to push folks to take longer to make their decisions, and again, what kind of return and how quickly am I going to get it on this. I'd say the second thing that's contributing to the uncertainty, and it's why I cautioned around the AI piece of it, people increasingly are finding concern about making the wrong decision.

In fact, I think they're getting so conditioned to believing some of the language in the market around AI is going to change everything. We've seen a couple of examples where we came in to show a customer a better, cheaper, faster, and they had just signed a two-year license on something they can't get out of now.

There's this evidence of people being reluctant and afraid of making wrong decisions and that things are changing so quickly that they're waiting and delaying probably more than they have in the past. It's two factors really, right?

Protect the bottom line, but fear of making a mistake in a really uncertain AI economy. It has its positives when we can show you better, cheaper, faster, but it's also got the, "Jeez, if I wait another quarter, what else is going to change?

Could it get cheaper? Could it get faster?

Could there be a different solution?" It's been an interesting dynamic to work in that kind of environment.

Appreciate that commentary. Then maybe just going back to that real-world example where you could deliver 50% to 70% faster.

When you think about your business, maybe in 2027, where it's even more AI-enabled, to what extent is that capability around speed going to create a lot of spare delivery capacity in the team that could maybe be soaked up if we start to think about the record pipeline and bookings picking up and overall just kind of driving margin expansion next year?

That's the belief, Gavin. When we talked right at the very beginning about creating force multipliers, we have really deep domain expertise, and you can't just go build that overnight.

You can actually teach AI rapidly. You can't build domain expertise rapidly.

Making sure that we find places to put those great folks to work because they're hard to replicate. I would say the pipeline is showing evidence that we've got places to now put them to work.

They've got transferable skills because they're really about solving a specific problem and increasingly less focused on a particular application. That flexibility in problem solving again makes them valuable as we go forward.

Look, I think that's the expectation and what we're seeing with customers right now is we free up a lot of time. We've cut some recent delivery times and costs in half for customers on latest project, but they're actually taking those dollar savings and investing them in more technology roadmap additions that we're getting to participate in.

We are seeing better, cheaper, faster on the stuff we do, and we are starting to see clients embrace and give us more work, especially the most advanced ones, the ones who are really driving accelerated roadmaps using AI, we're finding we're doing more work for them. Our hope and expectation is we will be soaking up this capacity with additional work.

Great. Then maybe lastly for me, maybe for Mo, just you talked about some of these deals for AI-enabled services where there's a PS component and an MS component.

How are the deal sizes kind of split out between PS and MS? It sounds like in some cases you want to subsidize the PS to get the longer-term MS, higher-margin revenues.

Maybe you can just talk about the gross margin component in those two pieces over the term of that type of deal.

In the examples that I shared, I'd say probably a third or a quarter to a third of it is the upfront, the implementation, get it set up, get it going, and then that kind of builds the AI foundation for us to kind of manage off of as well in the AI and combined with our processes and in the domain. I would say they're still healthy.

I wouldn't say that we're heavily discounting it, but I guess what I don't want to set the expectation is that PS margins are going to skyrocket because of AI solutions. I think part of it is we're still delivering kind of within the PS margins that we've been delivering even with AI-enabled solutions, but that is essentially embedded in that kind of stable margin is the investment that would support landing the MS, the managed services work over the three years.

The managed services is where we expect north of 60% gross margin profile. That's what we're after and that's kind of what we're yielding.

The PS, again, upfront is probably steady to what we have been generating in a traditional sense. That's probably the expectation I'd set, especially where we sell more Professional Services bundled with managed services.

If we're doing a stand-alone, just Professional Services, there's opportunity to increasingly boost margins through our AI-enabled solutions, but in bundled arrangements in some longer-term deals where we're willing to invest some of the margin.

Thanks, Mo. That's all for us.

All right. I think that wraps it up today.

Thank you for joining us for the Q2 results. Look forward to being back in another quarter and sharing our progress getting that pipeline converted.

I hope everyone has a safe end to summer, and we'll see everyone in another few months.