Unlocking Growth in the AI Era with Zone & Co

As NetSuite accelerates its AI strategy, partners and customers alike are asking how Zone&Co fits into the future. Discover how Zone’s NetSuite-native platform and AI roadmap are helping finance teams automate smarter, connect data seamlessly, and scale with confidence. See what’s new, what’s next, and how partners and portfolio companies are driving measurable impact through the power of NetSuite + Zone.

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Transcript

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Eliot Cohen
Hello, everyone. Hopefully, you can all hear me and see me. Thank you so much for joining us. I want to say good morning, good afternoon, or good evening from wherever you are tuning in.

Again, thank you so much. We have a short but jam-packed session for you today, so I do want to dive right in. And, just for context, this is an encore session from an event we held at SuiteWorld this past fall where we discussed our product roadmap and our AI strategy in some detail.

The title of today's session is Unlocking Growth in the AI Era. So let's get into it and talk about what we are going to cover today.

Today, we want to talk about how we here at Zone & Co are positioning our products and our strategy in relation to NetSuite’s own advancements. As everyone probably knows or has heard, there were a lot of announcements made at SuiteWorld.

Today, we are going to highlight the big ones and explain how our solutions work in orchestration with NetSuite to make the platform better, faster, and stronger. Specifically, we will look at how Zone & Co’s native platform helps you automate processes, surface critical data points, and scale with confidence.

Our hope is that by the end of this session, you will see exactly what is new, what is next, and how we continue to drive measurable outcomes for our clients. So, a quick intro for your hosts.

I am Eliot Cohen. I am a Private Equity Lead on our Alliances team here at Zone & Co. I am joined by Anthony Dixon, a Platform Manager in our AI practice area. So, Anthony, great to have you. Do you want to say hello quickly?

Anthony Dixon
Hi, everyone. Good to be here. Excited to share the AI story with you.

Eliot Cohen
Awesome. Thanks, Anthony.

We will go quickly through this initial intro part and give you the main stage in just a few minutes. Just for level-setting, and then I will pass it off to Anthony to talk in more detail about our products and our AI strategy.

In a nutshell, our mission is simple: we strive to modernize business operations. We build powerful software solutions that unify workflows, operationalize data, and make complex processes streamlined and effortless. We focus primarily on the office of the CFO, and most critically to note is that we sit directly within NetSuite.

Our solutions are all built on the NetSuite platform. We exist to connect disconnected systems and processes, automate manual workflows that slow your teams down, and really make you more successful on the NetSuite platform.

So, to talk a little bit more about our solutions and our offerings, I am not going to spend a ton of time on this slide, but I do want to highlight the areas in which we play. And then on the next slide, I will get into a bit more detail.

In terms of the areas, our solutions enhance order-to-cash, procure-to-pay, record-to-report, as well as some HCM and HRIS areas. I show this slide just to visualize the domains in which our solutions play.

Next, to get into a little bit more detail, what I have on the slide here are the SuiteApps broken out by name and by domain. So in the order-to-cash space, we drive transformation with our ZoneBilling product.

Moving across the slide, in procure-to-pay, automation and reconciliation are covered by our HRIS and HCM tools with ZonePayroll and the Zone Employee Portal. Really, the key thing to note here is that whatever the domain, we extend NetSuite's power without requiring you to leave the platform, and I will speak about that a bit more on this next slide.

And this really is the most important slide when you think about Zone & Co’s technical setup: our solutions are 100% native to NetSuite.

So what does that mean? It means the user experience is the same, the data layer is the same, and there are no third-party integrations for you to manage. We package specialized automation on top of the NetSuite platform that you already trust.

The bottom line is this: operators love to use our tools because we connect dots and deliver capabilities that NetSuite does not connect or deliver out of the box, and auditors and folks who report and rely on the business love us because the data never leaves the system. Our solutions align to provide clean, secure, connective, and reliable workflows that can allow your company to scale.

Okay. So for these next two slides, I want to talk a little bit about strategic positioning and ecosystem updates that were announced at SuiteWorld and beyond, and I really want to explain where Zone & Co fits in.

First and foremost, at SuiteWorld, the Subscription Metrics module was announced. And what that is is a new dashboard for tracking ARR, MRR, TCV, and other more advanced subscription business metrics.

We look at this as great news. Our analysis suggests that this new module will plug in directly with ZoneBilling data that comes from our solution.

When this tool becomes GA, it will provide a visualization layer on top of our solution, and it is a great place to start when you need to look at those metrics that I mentioned. I mention that it is a starting place because our own reporting solutions, like ZoneReporting, can take things to the next level.

And a lot of businesses these days want to go to that next level of reporting because utilizing subscription metrics is a common ask in order-to-cash transformations—ones that are driven by a tool like ZoneBilling. This new NetSuite Subscription Metrics module is a great place to start in terms of visualizing and surfacing those data points that are brought to light by ZoneBilling.

And if you want to get more advanced down the line, a more robust tool like ZoneReporting can take it to the next level. So the Subscription Metrics module is a great tool that we think our ZoneBilling data will plug into natively when it is in GA.

The next thing that we want to talk about is the NetSuite and Bill.com partnership that was announced at SuiteWorld.

NetSuite highlighted a tighter partnership with Bill.com. We see this as validation that the market needs more advanced AP capabilities.

The thing to note about the Bill.com and NetSuite partnership is that it is geared towards a very specific segment: US-based companies, single-subsidiary setups, and very simple multi-currency needs. Those types of workflows are not designated for this Bill.com partnership.

So in summary, if you are a complex global business and you need more, ZoneCapture is a great broad tool that is going to allow you to do some of the things that might not be covered by the Bill.com and NetSuite partnership.

We still see some positioning for us to continue supporting our global, complex customers with our AP automation tools. The final area that I want to mention on this slide is there was a lot of buzz at SuiteWorld about connecting LLMs—large language models—to NetSuite for ad hoc querying.

And while this is exciting, applying a generic LLM to financial data leaves behind critical context. It can lack accuracy, thoroughness, and background.

This is where some of our tools like Solution 7 can really shine. Solution 7 provides a live, secure, direct connection between NetSuite data and Excel.

So you are not just querying. It is a full two-way drill-back live linking. For finance teams who live in Excel, we believe that a structured real-time connection offers more precision and value than a generic LLM chat interface can offer for now. And a tool like Solution 7 with a direct connection to Excel allows teams to continue working in a tool like Excel that they are familiar and comfortable with.

Okay. Moving on here. This brings us to the core of the discussion today: AI.

NetSuite announced their AI Next Vision, but realistically, those advanced features are slated for the later part of next year or even 2027. And some of the capabilities that were announced at SuiteWorld will be restricted to North America. What we are trying to do is move fast.

We are delivering global wins now and doing that incrementally, and we will build on what we deliver over time. Today, we already have AI in ZoneCapture and ZoneBilling.

Anthony is going to talk more about this, but in Capture, we have context-aware 3-way matching driven by advanced OCI technology. And in ZoneBilling, we have our advanced help chatbot interface that can allow you to get up to speed with your implementation and the nuts and bolts of the product.

Next, we are moving toward more agentic AI. These will be agents that independently plan, reason, and provide insights based on your NetSuite and Zone data.

So in summary, our AI differentiator is going to be specialized intelligence. Unlike generic tools, our AI will be enhanced with deep domain expertise and the permissions and controls that you are used to getting with our tools.

So that is just a very short and brief background on Zone and some of the recent announcements made at SuiteWorld. But to take us deeper on how we are going to build into the future, I am going to hand it over to Anthony. So, Anthony, over to you.

Anthony Dixon
Okay. Thank you very much.

Yeah. I am going to talk to you about Zone & Co AI, which is really just a new name for something that Zone & Co has been doing for years or committed to doing for years now, which is bringing in finance-native AI that actually works to the products we use.

And in particular, the way we have been doing this is with ZoneCapture, which, as already mentioned, we have had for a while now and we continue to improve on. We are thinking about AI in four different ways.

If you hit the next slide there, please—you can see that we are thinking about this in four different ways: point automation, smart execution, proactive insights, and active learning.

So what is point automation? It is making things faster. It does not always have to be with GenAI, and in fact, we prefer to use standard AI whenever we can because sometimes it can be more reliable.

What we want to do when we move on from that is look at smart execution. Smart execution is going to take your workflows and complete those workflows powered by our AI, starting with natural language, creating the workflow with the permissions that you have inside of NetSuite, checking in with you before that workflow is completed, and then going and doing it.

Again, saving you time, saving you hassle trying to understand how to use the system, and making it easier and better for you.

Next off, though, we do not just want to make things faster. We want to bring things to your attention that you might not know or might not have the time to go and look for. So we are talking about proactive insights—always-on intelligence that understands what you have in your NetSuite account, understands what you should have, and then will surface that up to you.

Last but by no means least is active learning. All of these systems are great, but everyone has different customizable use cases, and what we must ensure is that we learn from user inputs. So in ZoneCapture, ZoneReconcile, those point-AI matchings, the workflows—we want to close that loop, understand the outputs we have given people, see how they differed, and then bring that in so the next time around we increase the accuracy.

Okay. So what I am going to do now is look at some of the products and bring to life some of the things we are looking at doing in order to increase productivity with AI.

Okay. So ZoneCapture. We have talked a bit about ZoneCapture already. It saves people a huge amount of time in terms of reading invoices automatically and then populating the data into NetSuite.

What are some of the things that we are looking at next? Firstly, document-level processing. At the minute, we do it page by page, but obviously context goes across a whole document rather than just the page, and as we have seen with AI, that context window is getting larger. It can understand more things at the same time.

We are able to move from single-page to document-level processing, and that means it has intelligence across different pages. So it can do things like work out tax on a multi-page document.

Again, I just finished speaking about it, but active learning is incredibly important for ZoneCapture—that we pull that in and we start learning from the different data that has been put into the system. This can be done in a couple of different ways, and people can be sensitive about how models exactly learn from the data.

But what we want to do is, where possible and where customers are comfortable, work with them in collectively sharing that intelligence and making sure everyone benefits in the system. Some of you may have heard about federated learning where the models can see only your data, but benefit from everyone else's data as well in order to improve the system and get better at capturing the correct details into NetSuite.

Finally, we want to broaden the scope of documents. We have seen great success with our customers in what we currently offer, and we want to build on that success by opening up into different document styles and ensuring we still get great results.

Okay, moving on to ZoneReconcile. Similar story, but our target here is touchless reconciliation.

We want to go through especially the first two points on this slide to ensure that those month-end closes are as smooth as possible, that reconciliation takes the least amount of manpower possible.

We are looking at AI-powered matching. Here, the AI will review what has been learned and build complex rules so it can then use those rules in the future, increasing the reconciliation rate while still matching high accuracy so you have confidence that anything matched has been matched correctly.

Again, we want to do that through active learning, whereby we look at the outcomes, feed that back into the system. Initially, more manual corrections may be needed, but over time we reduce that to near zero so that people do not get annoyed about continuously correcting the same things.

On top of that, we want to bring in an AI-related treasury-light solution, and here we will look at four main elements. Again, this does not all have to be generative AI. There is so much happening in AI more broadly that we do not need to focus solely on generative AI.

The first thing is automated liquidity forecasting. We have high-powered AI forecasting tools that allow us to use a similar tool for lots of different customer use cases.

Right out of the box, we expect highly accurate forecasts—30-day liquidity forecasts, maybe more, maybe less.

Next is cash flow and variance analysis. You have these forecasts and projections, but you also have what happened in real life, and you want to know where the difference is. Where did it go wrong? Why did it go wrong? It brings up insights into changes.

We can also do variance analysis from one month to the next. If cash flow is down, we can look at why.

In addition to that, building on forecast, we want to look at scenario planning. You will be able to type into natural language and adjust your forecast to a different scenario—for example, “Assume I increase all of my products by 10%,” and it will change the data and bring back a new forecast.

Lastly, we are looking at working capital insights—FX management, bank fee analysis, optimization insights—all designed to proactively surface insights to help grow your business.

Okay. Moving on to ZoneBilling.

ZoneBilling—again, as already mentioned—we are currently working on a data agent, a question-and-answer tool with access to your data. You might ask, “What was our subscription churn last quarter?” “Which bills are outstanding?” “Who has not paid?” “What is coming up?” If it is in NetSuite, the agent can go in, find the data, process it, and give you an answer.

No more building saved searches. You can ask questions and get the answer.

Next, we want to extend this. What we are building now is read-only. What we want is the ability to also write to NetSuite, and that is the workflow automation I mentioned earlier—to cut down on your time.

Because customization is huge in NetSuite, we want you to be able to take what we build and adapt it to your specific business needs so it does exactly what you want.

Next up, we are going to take a break from me talking and show a little video of the ZoneBilling agent—a demo. So, Eliot, if you can show that now.

Video Audio

Hi, everyone. This walkthrough will demonstrate the new ZoneBilling Data Agent. This represents a significant step in embedding AI into our platform to provide instant answers to complex billing questions.

Currently, getting answers to questions about TCV, billing gaps, or customer history requires running multiple reports and manually consolidating data. The ZoneBilling Data Agent eliminates this friction by allowing users to simply ask questions. Please note that while the UI shown is for demonstration purposes, this exact capability will be integrated into the existing ZoneBilling AI assistant.

Before we get into customer activity, let us open with a simple example. A user asks, “What was the total value of subscriptions that started January 2020?” In the background, the agent translates this natural language question into a precise SuiteQL query, runs it against your live data, and provides an instant answer directly from NetSuite.

Now let us look at a more specific scenario. A user needs to see a customer's recent activity. Notice they type a query with a typo in the customer name. Let us see what happens. The agent intelligently identifies the intended customer, 123 Test Customer, and instantly returns a precise list of their billed charges for August. This circumvents the manual search and error correction process entirely.

Building trust in the AI’s output is critical. For every response, we provide complete observability. The user can click to view the actual dataset the agent returned. This allows for immediate validation without having to navigate to another screen or report.

For full transparency, users can also inspect the exact query the agent generated to pull the information. This confirms the logic used and provides power users with the detail they need to trust the result.

Now let us address a more complex business problem: billing leakage. A finance manager asks a direct, high-value question about unbilled charges with some complex grouping. The agent processes this request and returns a direct, actionable insight—a list of all charges that are past their intended bill date but remain unbilled—allowing the team to immediately follow up and capture at-risk revenue.

What we have demonstrated is not just a query tool. It is a faster, more intelligent way to interact with billing data. It provides immediate, accurate answers, builds user trust through transparency, and surfaces critical insights that protect revenue. Thank you so much for watching.

Eliot Cohen
Anthony, you still there?

Anthony Dixon
Sorry, I muted myself. Yeah. So that is the AI agent, and we hope to have that in production next year.

What I am going to talk about now is the central AI services that we hope to have across all products.

Again, looking out, we have forecasting. I have already spoken about this in terms of treasury and reconcile, but we are also looking at how we can use that same forecasting in ZoneBilling for usage and charge forecasting.

We are also looking at Zone Data Platform and how we might do supply chain forecasting, which has been requested.

Next, we are using a similar system for anomaly detection use cases. This essentially looks for numbers that are out of place—maybe a bill that is too high, or usage that is too low.

We want to surface those immediately so you are not trawling through data or missing insights. Usage anomalies with ZoneBilling, financial anomalies with ZoneReconcile and ZoneCapture, KPI deviation like DSO—you will know if it is up or down.

Finally, reflecting back on the ZoneBilling AI agent capability, we will be pushing that out to all our products—ZoneCapture, ZoneReconcile, etc. We want you to be able to look across not only individual applications but all applications at once, so you get a complete understanding of how your finance team is operating.

Okay. I think that is me done for this. So I think now Eliot, back to you and questions.

Eliot Cohen
We have a few minutes for questions here. So if folks want to drop them in the chat, we are happy to answer questions, feedback, suggestions. We have a couple of open minutes.

I have one or two that I can feed into you, Anthony, but maybe we will give folks a minute to ask questions.

Anthony Dixon
Yeah.

Eliot Cohen
And, Anthony, thanks so much for giving us that overview. That was great. Super informative.

Anthony Dixon
Sure. That is great. Yeah.

Eliot Cohen
I think maybe go ahead.

Anthony Dixon
I was just going to say also, if they want to drop in a question they would like to ask the AI agent, that would be great as well.

Eliot Cohen
Do something live. I love that.

Maybe while we are waiting, Anthony, one thing you talked about with active learning—and you made this point, but I want to double-click on it—is with that active learning, the tools become more accurate, more robust, more useful. Do I have that right?

Anthony Dixon
Yeah. That is exactly right.

Any AI is only as good as the context you give it, and everyone’s business is different. So there will be variation in the responses it gives.

What we want to do is ensure we learn from the inputs users give it as they are using it. They will see it grow—day one will be good, but a few days down the road it will get even better until it is doing exactly what they want.

Eliot Cohen
It is awesome. Very cool.

Anthony Dixon
And there is some clever stuff we can do around data sharing. It can learn only from a customer’s data—that is fine—but we can also do some interesting things so models can learn from everyone collectively while still keeping each customer’s data private.

Eliot Cohen
Amazing. Anthony, which feature or capability that we are rolling out are you most excited for?

Anthony Dixon
I am—do you know what—I am looking forward to the AI agent because I would love to see how people use it. We have had people draft emails with it and all sorts of things I was not expecting.

But I am also excited about some of the point automation because AI is not just generative AI. It is not just ChatGPT. There is a lot we can do to make boring, mundane tasks go away, and I am looking forward to that too.

Eliot Cohen
Very, very cool. I love it.

Well, great. Thank you all for joining. We are right on time here, so we will wrap up. Anthony, again, thank you. Appreciate you giving your perspective. It is always fun to hear from the expert on this stuff, and I am really excited to work for an organization where we are doing as much as we are with AI.

The advancements of our products, I think, are really going to continue to grow the impact that our software can have. So I hope this was informative.

We are available for follow-up questions offline or after the fact. Thanks for the time. Appreciate it, and we will talk again soon.