Name: Integrating NetSuite and Advanced Salesforce Integrations
Uploaded: 2025-12-03T19:16:03.425Z
Duration: 49 min 16 s
Description: Integrating NetSuite and Advanced Salesforce Integrations

Transcript for "Integrating NetSuite and Advanced Salesforce Integrations": Hey, everybody. We're just gonna wait a couple more seconds here for folks to join in, and we'll get started, in a minute. Okay. We'll go ahead and get started. Thank you everybody for joining us today. This is, the ins and outs of advanced Salesforce and Nettoon integration webinar. My name is Rico Andrade. I head global partnerships here at Zaligo, and I will be joined by my colleague, Nate Bryant, on the solution consulting team. This is a webinar that came, as a result of, by by popular request, a sequel to the original webinar that we did on Salesforce and Netgent integrations. We had so many questions and so many things that we didn't touch on, earlier this year that, we're gonna cover some of these items today. So couple housekeeping items before we start. So first off, the session is being recorded, so we will be sending you, and, other, registrants the recording of this presentation afterwards. If you have any questions or comments, please add them to the chat or the q and a, section. You will notice also that there's a docs tab there that has some relevant links, the and some of them that we're gonna talk about today, such as the recording to this legal AI summit that we did earlier. But, let's go ahead and get started here. So first off, you know, we're a quick introduction, and, we're gonna do a recap in terms of, the overall, larger problem that we typically solve and then what we're gonna do after that. And then, we I will pass it on to Nate to talk about advanced use cases, and he'll also do a demo of some of these use cases. And, we're open to q and a. But please, as you go along, please ask questions. And just as a very quick recap, the Salesforce NetSuite integration is something that we know extremely well. As a matter of fact, that is the root of how Soligo got started as a company. So Soligo today has become one of the largest and most important iPaaS companies in the world. We've been number one on, g two for now two straight years. We have been the, we were the only, iPaaS, that Gartner named as the twenty twenty five, customer choice, which was a huge honor about two or three weeks ago. But, that is so so we do a lot more than Salesforce and NetSuite, but this is a use case that we know a lot about. You know, we've done it thousands of times over the last ten years, every use case imaginable. And so we're gonna talk about some of the lessons today and hopefully get, inspire some of you, in terms of what's possible. And this is what I was referring to. This is, happened, a couple weeks ago. So we're very proud of it. Saligo being the only iPaaS named as a Gartner, customer choice in 2025. So feel free to take a look at the report. You You can go on this legal.com homepage. You will see a link to the report over there. And, very proud of that and the team. So, quickly to recap in terms of where we were last time. Right? So last time, we focused primarily on this, the lead, you know, the quote to cash process basically between the CRM and ERP and the specifically, Salesforce NetSuite. Pretty well known process, straightforward process, something that, we, you know, just just at a basic level, there are certain things that, you know, can and should be done. And we spoke about how Soligo solves, some of these use cases in a way that given that Salesforce and NetSuite are two of the most customized applications, you know, two of the most important applications that any, company is doing that, you know, there's certain things that you need to do to be able to do this scalably, and, you know, really set yourself up for the long term. So this is what the focus was for last time. But, if you recall, there's much more to this process and, these integrations than just, the basic quote to cash process. At some point, there's lots of other applications that may need need to be involved or, additional process. So for example, with CPQ and, you know, suite building and and so on. Right? It adds a certain level of complexity. For certain companies that, you know, maybe they they sell physical goods, physical products, from a, you know, b to b side, there there may be a shipping component involved, you know, sales team and this, you know, shipping component beyond any ecommerce operation. So how how is that typically handled, when involved in these two applications? And, you know, payments and, you know, and so on, so stricture and, billing. But, it also goes well beyond this. Right? Because there's other departments that oftentimes need to be part of this whole operations. And so how do, you know, how how do you integrate these other, you know, processes into the the the quotes, cash, or the, you know, Salesforce to NetSuite process? You know, one of the most common one being, just purely in terms of, reporting and analytics. Right? Because, you know, or perhaps data warehousing and so on. So we're gonna talk about some of these use cases that we see today. And then, and and then really, like, the one that's taken off this year, that's the talk of the town, is how do I add AI agentic, workflows to, these Salesforce and that's what we processes. Right? And, we have a unique perspective on this. This goes well beyond just what NetSuite is capable with MCP or what Salesforce is doing in terms of their agentic, functionality. Right? Because there's so many mother other applications, that are also involved. So AI needs a lot of data to, do its things. Legal is in the business of getting data where it needs to be, and so we always say that there is no AI strategy without an accompanying integration strategy. And so we're gonna talk a little bit about that. I'm using the slide, by the way, because I use the AI functionality on the presentation. There's a little option that says beautify the slide, and it did this. And so I thought it was appropriate for, talking about the AI use case here. But, you know, to recap some of the things that we, talked about last time. Right? So, probably most of you are familiar with the Saligos, Salesforce NetSuite integration app. So we're not gonna there's a whole webinar, and you can access this webinar, the recording of it in the docs tab looking at the link to the ins and outs series of integration. But, it this covers, I would say, 80% plus of the, use cases, out of the box in a way that's very customizable and, configurable. And then, but if you need to go beyond it, right, then a Sligo does have a mechanism to customize those applications and, you know, we will talk about some of those customizations. Right? But this is what you get out of the box with the integration app. It's it's the essence, the basics of, you know, what you need, but it's con in a it it's built in a way that is extremely, configurable, you know, very robust in terms of the different use cases. And then there's a reason why Soligo is the choice, for the these two integrations, in the NetSuite ecosystem. So much so that today, Salesforce, NetSuite is actually selling the, our solutions, legal and NetSuite integration app on their own paper as a integration solution between these two applications. So, yeah. So if you wanna see this and learn more about this, if you haven't seen it before, please, take a look at the, at the previous recording or just reach out to us and, you know, we're happy to provide a a demo and explain this in quite a bit more detail. So with that, let's jump into the advanced use cases, some of which, you know, would like we started to hit on, in my previous slides there. But, I wanna bring, Nate Bryan, on board now who's gonna talk in details and then go into the the, a demonstration of how some of these, use cases are are resolved with our platform. So all yours, Nate. Yeah. Thanks, Rico. So we're gonna walk through a couple advanced use cases, obviously, with Salesforce and NetSuite being the main focus. And I I think it's important as we, you know, go through these use cases that we don't lose sight of why organizations purchase these applications to begin with. Right? So the CRM is oftentimes near the top of the funnel. Sales teams, are using this as they intake data. They're taking orders. They're interacting with their customers, recording those transactions. And then, ultimately, that data ends up in the ERP for finance to, you know, invoice, perform fulfillment, any reconciliation, collect payment. And so each of these use cases that we're gonna talk about is really to actually build on that functionality. So as organizations add additional modules, whether it's, you know, Salesforce, CPQ, RCA, or NetSuite suite billing, or they start incorporating a third application. At the core, these all these advanced use cases are really to help, the business accomplish that core functionality of going to market, getting getting customers, expanding existing customers, selling goods and products, whatever the organization might be doing. This is why you purchase those applications, to to assist in that. And so the first kind of, discussion is the the the natural evolution of a business that's using Salesforce and NetSuite and especially in b two b SaaS, like Saligo, we we do ourselves, is this idea of you're using starting to use a lot of custom objects, you're developing contracts, you're quoting people, you're, sending out contracts for approval. And especially when you're having a SaaS offering, these contracts that you're quoting people can often be complex. They can be multipart. They can be multiyear recurring. And so how do you account for this complexity, across the two applications. Right? Sales is generating these contracts, within Salesforce, but, ultimately, that contract needs to be able to end up within the ERP so that you can, do whatever financial processing you might need. And so, at, you know, Soligo, we we do this ourselves, and we also have a lot of experience releasing templates in this, especially around suite billing or CPQ. The idea is that at the the top of the kind of chart on the right, it is very similar to the normal order to cash process where you're capturing account data, billing information, contacts. And then this is where the complexity starts to to kinda creep into the process. You have complex price books with your different products and your offerings. They often have rules associated with them, so you can't add, you know, the classic example. You can't, add, you can't sell a printer without ink, for example, would be a rule that someone who's selling a physical good might have. So the price look starts to contain, variations. Oftentimes, the, while, accounting or finance might have input into what the price look ultimately is, they're at the receiving end of whatever contract, is ultimately created within within sales, obviously, with approval steps going throughout. And so the complexity of a CPQ process, whether you're using the old Salesforce CPQ, or the new RCA or maybe another entire quoting tool, it really drives the downstream financial structure. And and that has to be accounted for in the integration, because you don't want to create a contract that one, your finance team can't, invoice for or that, hasn't been approved for, you know, by legal or the approval process. And each of these, and that's before you even get to, like, usage pricing or event pricing. And as you start to add in these these modules, this is where you need to really think long term about what does it look like to invoice your customers accurately, and and what does it mean to have your, you know, your subscriptions, your planning, in a way that your sales team can easily interact with it within Salesforce. And a lot of that does live on the application layer, and it's the integration layer that's doing the translation from maybe the complexity of your CPQ contract into the something a little bit more simple to to invoice in. And so when you're thinking about integration between these two, especially as you start to come into subscription billing, recurring, expansion, that sort of thing, that's where you have to have the integration layer do that translation for you so that at the end of the day, you're billing your customers the right amount. Another kind of flavor of this is if you are working, maybe with a non for profit version of these applications. So, again, at at at the top level, it feels very similar. You're collecting, account information. In this case, it's maybe donors. You're collecting their information of where the money is coming from, if you need to reach out that contact information. The big difference with non for profit is oftentimes there's no physical good or fulfillment or service being provided. And so in in some ways, it's simpler, but there's also different ways people can, you know, work with non for profits. Right? They could be giving a single donation, a one time gift that becomes a cash sale within NetSuite, or maybe they're doing a recurring gift on behalf of someone else to even make it more complicated and you start to get into pledges, and and pledge, schedules and that sort of thing. So what I like to do when I talk to non for profits is, you know, a lot of this stuff is really, it's kind of the same process by different names. So instead of a customer, you have a constituent or an organization as a household. At the end of the day, you still are doing a kind of order to cash process. The difference is that the organization, the not for profit is not necessarily returning something directly to the gift giver. That's not always the case, but a lot of times when you're considering these two, it's it's really is that that core order to cash process that still needs to be managed in a way that, if you have a a team that works for outreach in the CRM when they're collecting information and when they're ultimately, you know, closing a donation. Finance knows where that's coming from, who it's coming from, so they can track that, more for audit purposes rather than, the fulfilling the order. So, data warehousing, this is a a very popular, topic as well as a natural evolution of the CRM and ERP as, you know, organizations get more advanced or they start growing or they're looking to scale. Lots of users work within these applications. They're doing various things, collecting various data. And what happens when you hit the limit of the reporting or the insights that you can garner in the two applications? That's when a data warehouse is the natural next step. So there's very, the it it starts with the extraction, right, where you're just extracting, bulk extracting. Maybe you're being a little bit more specific about what data you're extracting, but that data ultimately ends up in a data warehouse. So that's just, the the standard ETL or ELT process, where it's just extracting out that data, from these applications, and they end up in one data storage solution. The advanced use case here is really when you start going the other direction because it doesn't do an organization much good just to have extracted that data. Maybe you're doing some initial reporting, but it ultimately doesn't end up back in the hands of anybody in the business that can do anything. So that's when reverse ETL starts to really matter is you're, you've gathered all that data in your data warehouse. You're generating insights. So you can be doing some reporting. You can do calculations, summarizations in the data warehouse. And then, you can then take that and push that back into the applications, so business users can use it. And that's that reverse ETL action that's occurring. And at Zaligo, we do a lot of reverse ETL. You know, the sales team works in the CRM. Maybe they need a, you know, a snapshot view of what's happening with their customers. They're not gonna have access to a data warehouse, or maybe or to the ERP. And so it's pushing back insights into, in a format that's usable by the customers. And then, actually, then they can do additional reporting within Salesforce because that data now exists. Same thing with NetSuite. Especially with NetSuite or an ERP, you you wanna keep your ERP as clean as possible. Right? You're not trying to put in junk data. You're trying to keep it clean to where, you know, only existing customers are in the ERP or new cross new new customers. You don't have this, you know, prospects or people or information that you're not doing business with. So it's especially important to keep, you know, your p ERP clean, and that's where you can consolidate a lot of data outside of it in the data warehouse and only push in the data into NetSuite that's that that really matters, especially when you're trying to, you know, perform an audit or or or day to day financial transactions. You don't want a bunch of junk data, messing up your process. And and, the insights don't have to be just, you know, a calculation. They can be, more, empirical. It can be, taking lots of data, and forming trend lines and giving, like, a tag to something like, this customer is a, a high priority customer, or this customer based off of the trends we see in their buying and usage, they're ready for an expansion, or they're ready for to be reached out for a a marketing, campaign. And these are all things that can be generated, based off of calculations in the data warehouse, and then, ultimately, the end user is the one that that sees it and uses it in their application. So the next topic, we're gonna go into is AI. Right, can't talk about, SaaS products or integration these days without talking about artificial intelligence, and it's really part of every SaaS offering, in in the marketplace now. But at Soligo, we've, we kinda have a unique position to view the AI, kind of as it goes throughout the the different applications is because oftentimes users are interacting with just the singular AI that they're they're working with. So, you know, Salesforce has Agent Force, Oracle, and NetSuite have talked about their MCP server. You name a SaaS application. There's some sort of AI chatbot, that's been built in. And what that looks like day to day is users are just having to interact with these kind of segmented AI that only have the information, that is one in that application, and two, how it is configured and weighted based off of the offering of that application. So in the back end, you don't know how the language model is weighting different words, how it's, segmenting out your questions and and controlling the return. You're just getting basically the output and hoping that, the AI has been kinda structured in a way that's most useful to you. And and that it's and especially in every application. So it can be very frustrating for a business user if they're trying to get, you know, insight. They're using AI because it's easy. Hey. I have a general question, but, you know, I need multiple data sources to really get this answered. That's not possible if if your AI strategy as an organization is to depend on just the AI that's provided per application. And so what we've seen is kinda what I just talked about is, you know, there's lost information, inconsistent answers across applications. Users don't know which AI to ask, and, ultimately, you're not really getting any value out of these individual AIs. It it's just a a nice to have feature. So how do you take that and really take it to the next step where you're actually getting a return on investment, with the AI from your applications? And that requires a a a unified AI experience, both from a data perspective as well as from a user, interaction perspective. So it's taking all of those all of your data that exists within your applications, running it through a unified AI experience, and then the users can get a consistent output. And so what does that actually look like in practice? Right? So we do this internally, at Zaliga. So the main way that, users interact with AI output is with Slack currently. We have Slack. It has great features where you can, add bots that are tied to Soligo flows in the back end, or, you can have listeners that are sending out the prompts that users are asking in a Slack channel to to the Soligo platform. And but, really, what's important is that every prompt that's given is going through a unified flow and that the person building this legal flows is able to provide a a consistent prompt. They're able to iterate the prompt and control the output. And so, our our users, our sales team, our research team, our expansion team, everybody is able to just go to Slack, and that's really their experience of the chatbot, but it has access to all of the data in our organization. So we take data from the CRM, Salesforce, from our financial, from our ERP. We use Gong to record calls, game sites, Zendesk for ticketing. Right? It's all these other disparate serve, data that lives in Snowflake, and we're able to take all that. And the AI prompting that occurs is able to use all of that as a data source rather than just the data that lives in Salesforce with, like, an agent force or something like that. So this use case is whenever, a someone that's working with one of our customers, whether they're answering a ticket or they're, helping them with an expansion, they're able to ask for insights about the customer before they even get on a call. So they're not having to get on, ask questions twice, not be aware of something that occurred in the history of the customer. They prompt, in Slack, and it goes out, and the AI converts their prompts from large language into a query. It queries all of the data and all the different sources, and it gives them a response back in Slack. So very seamless experience for a user, but very powerful data that's returned, and it's in context. So it's not just an isolated response, and you hope that it that cover everything. So our users are using Slack, but the interaction doesn't just have to reside in Slack. Right? So it oftentimes, it's very valuable to send that to the CRM where you have a field in the CRM that says, you know, current, current customer three sixty view. It itself is a summarization that someone might get in Slack, but instead they're working in in Salesforce so they don't even have to prompt it. Same thing could occur with the NetSuite where, you know, current financial view or, you know, status of billing can also occur. A a critical thing here is, one, connecting all the different applications, but also using a data warehouse layer to store a lot of of additional data, so that it can be reused. It's it's it's efficient. So we we use Snowflake internally, and, again, that's where we store a lot of discrete data that doesn't live in these applications. Right? Someone might, input data into a a a report that they've had, that gets translated into Snowflake and then used as well. So, it's an additional way to store data that doesn't live in the CRM, in the ERP, in your ticketing system. Another great use for, for AI is is doing pipeline analysis. So, it's beyond when you're talking to customers, is there, anyone who's, like, worked in b two b sales or is selling, you know, products to businesses, or even consumers that it's a recurring customer. A customer is not always just their initial purchase. Right? So you have that contract value or that initial sale, that initial delivery of goods. But it's important to note that, hey. This customer is probably going to buy again for these reasons, or this customer is a going to expand in the future, or this customer sees us as a strategic partner, and and we need to, you know, especially focus, our attention on making sure that when they need an expansion, we'd have the details, as an example. So, what happens is, using AI, you can actually if you record your interactions with customers, like we do with Gong, you can then take that and translate that into a tag it as a future expansion deal or x y z, whatever classification you might be doing on your end, and then storing that in the CRM, storing that in the ERP so that it's tagged as something about you. So, this doesn't have to just be creating a tag on a deal. This could be any type of analysis when you're trying to segment out customers. You could say, hey. What kind of vertical are we working in? Where do we have the most success? What type of competition are we running into? So do you when you have these, you know, source of data, in this case, recordings with prospects and customers, able to take that, and convert all of that language from the recordings into, you know, a structured data tag or a a concise analysis is extremely valuable and a great way to use AI. What's, again, critical here is, you know, we use Gong. It has a great AI tool in chat that you can use. It's very good. You can ask it about a specific call or about an account. But, again, it's limited based off of, one, just the data in Gong, and two, whatever prompt engineering Gong has on its tool. So at Saliga, we've even though there is that AI tool within, Gong, we now could control the, the prompt and the output of that, using our own platform. And I'll show you that in the demo, what it kinda looks like, how you're able to iterate, your prompt engineering, how you're able to control the output. And and you can only do that when you're applying your own prompt and large language against the data outside of the application, and that occurs in the integration layer. So I'm going to, jump into the demo. We're gonna walk through kind of the advanced use cases in the platform, keep so you can see what they look like, as well as kind of a a high level view of the platform for anybody who hasn't seen it. So Okay. So I'm inside the Soligo platform now. So, for anybody who hasn't seen the platform, and this is the first view, I'm I'm gonna do a quick understanding of what we're looking at the screen, and then we're gonna dive into those actual processes that I talked about. So the Solio platform is a cloud based integration tool. Right? And what I'm working in is the UI. So the UI is where a user can configure, as well as manage and monitor the integrations that the that the integration platform on the back end is is actually performing. So the user is working here, changing, configurations such as, like, the prompt engineering that I'm talking about, the fields that matter, the applications you work with. And then at runtime, we handle all of the scaling. We have the error management built in. So the user is really just experiencing the the kind of UI experience without having to, like, manage all of the, the infrastructure on the back end. The home screen of Soligo that you're seeing here, these squares are called integration tiles. It's a way to organize all your integrations. So, obviously, we're talking, you know, CRM, ERP, NetSuite Salesforce, But the these kinda same advanced topics, obviously, I mentioned a couple other applications can all be managed right from within the platform. It can be any application that you wanna work with, and you can connect it to any number of other applications, whether it's you're storing data in your data warehouse or, you know, syncing up your own quote to cash tool into Salesforce. It's a unified experience where, regardless of the type of integration, it's gonna be done in the Flow Canvas, and it's gonna be monitored from the platform. So the the tiles act as folders where you can come in and and work on your integration. You can also control access via these tiles as well. So someone who is, you know, working in sales ops is really interested in the CPQ automation, can be and maybe the data pipeline automation can have access to their tile that works on that while the finance team, is more interested in, like, the financial, sync between Salesforce and NetSuite, the quote to cash tile. When you jump into a tile so I'll jump into a tile now. This is this is what it looks like inside of a tile. The the core of, the tile is these these this grid you see here. These are the actual what we call integration flows. These are the where you combine, our connectivity with your applications, the business logic that you might have, any transformations or scripting you might wanna do together, and you, connect those altogether within a flow, and I'll jump into a flow here in just a second. And then this is the, what runs based off of the schedule you provide or runs in real time based off of the application you're working with. And then inside of flow, you have these tabs up here that help you manage these, flows as well. So you'll have a dashboard that shows you the last time the flows have run, any running flows. You can see the status of your connections. You can set up notifications. You have analytics. So there's lots inside of a tile, and it's really to help you manage the flows that you built. So if I jump into a flow, this is around the, CPQ process. So you can see here that although we are talking about, you know, application a to application b, oftentimes, there's intermediate steps that need to occur in an integration to for the actual business process to happen. And it's really easy to do that within Soligo because you're basically adding these steps along your flow, from our connector library. So, when the case of the CPQ process, when an opportunity goes closed one, first, you need to check to see if a the customer exists within NetSuite. Right? You can't create a subscription or create an invoice or an order unless the customer exists. So maybe you're creating that and then posting the final order. Maybe you're going back and writing data back into Salesforce once you've posted that order. And so with Soligo, our flows, you read left to right, and you just add the steps that you need for the business process to occur. Similar in the same way where, as a human is doing it, you're saying, what step do I need to take neck you know, next if I was doing this manually? Well, I need to go check to see if the customer exists, or I need to go make sure the subscription plan exists. And you add those steps in, and then when it's complete when this runs, it's the automation, occurring, you know, all the way from the start of the process to the end of the process. And you can string flows together. You can string steps together. You can do multiple applications within a flow. And so that's really important especially when we talk about, like, a CPQ process where there's there's lots of supporting data that has to be generated first. You have to have the subscription. You have to have the subscription plan. You have to gather all of the, steps from the opportunity or maybe it's the opportunity goes close one and you have a quote object, a separate quote object. So you can imagine, especially in a CPQ process, if you don't have a tool that's able to, one, work with custom objects, or it's hard to understand what custom records are being used, it it can be very challenging. With Solio, we, of course, work with all of the custom objects that you have in both, and a lot of it is generated, you know, in the UI with without the need to, like, go look at the back end kind of classification. So I'm inside of a a NetSuite step here. This is what the all the prebuilt connectors feel like where you're naming your step, you're providing a description, you're establishing which connection you wanna do, and then you're choosing which record type. So in this case, for CVQ, I'm creating a subscription, but all of your records will be available to be selected from a from a drop down here. So even if you're working with a custom record, especially common in CPQ, you can easily just select it, from the the record type here, and then you're choosing which operation you wanna do. In this case, I'm updating a subscription, in the case of, like, a change order, and then I'm able to come into the mapping and select what data I want in in Salesforce to end up in NetSuite. So this is what the mapping tool looks like. It's it's a simple table rather than having to write any code or, you know, drag and drop lines, trying to create, you know, complex connections between. It's simply, available from drop downs. Again, you just select which field you want, and which and and the source destination and then what field do you want within NetSuite. There is that's a standard kind of mapping operation, but there's more advanced mappings you can do if you wanna click into the gear. You can do hard coding. You can look up values. You can do multi field where you can perform functions on your data before it lands. And and so there's there's the ability to build in any complex business logic you would need, but do it in a way that it's easy to understand what's happening on the UI perspective. Again, you know, like I've said, you know, a couple times during this is the CPU process, there's a lot of complexity in the in just by the nature of, you know, the business driving contracts, and you need to have the ability to adjust and actually build that logic and integration layer. Otherwise, you know you know, one change order can break down your entire process if it's not you know, if the data has been structured properly. Or you could be invoicing your customer completely wrong on the wrong schedule or the wrong amount, if you haven't been able to handle handle that complexity. With our with the you know, specifically around suite billing or CPQ, we actually have a template that we have. It's a it's an integration pattern we work with, very frequently, and it's something that we're very familiar with, especially as a as a SaaS company ourselves. So it it's a it's a common use case we help customers with, despite its complexity. You know, customers have a lot of success automating this, and especially it's a process that can cause a lot of headache if done manually. Every you know, someone's having to go in, create subscriptions, you know, calculate out the amount that's invoiced. Right? So, it's a it's a very popular integration pattern, especially around, Salesforce and NetSuite. So next, we'll go into data warehousing. I'm just in a different tile now. Again, unified experience despite whatever kind of integration pattern you're working with. So, that one was application to application, but now I could be going to, you know, database to application or database to database or, you know, EDI to application. Doesn't really matter what your what kind of pattern you're trying to accomplish. It's gonna feel the same. So, this is the that reverse ETL process we're talking about where you're generating insights and sending it back. Well, that starts with the ELT process, like I mentioned. So this is what, you know, an extract out of NetSuite can look like into your data warehouse. This could be any data warehouse you have, cloud or on prem, and you're able to use the NetSuite connector again to come in here. We have the ability to do JDBC connections so you can create your own query or you can, you know, use safe searches to extract data out of out of your instance of of NetSuite, and then you're pushing that all bulk pushing it into into your data warehouse. So that's a that's a pretty standard process, but what does it look like when you're going the opposite direction? So now I've loaded all my NetSuite data. I wanna update Salesforce with all of that financial data. So now it's a it's a second flow that is just extracting data out of sales, Snowflake and then pushing it into Salesforce on the account level. Again, you can come in here and this could be pushed directly to the account level so that, someone on the sales team can see that data or you could be pushing it into a custom object. Like, maybe you make a financial object, and then you're able to come in here and, pick, you know, whichever object you wanna do, and then you would just have to work with maybe your sales operations team to say, hey, sales team. Rather than go into the account, you could come in here and look at the financial transaction, instead. And then maybe that's a cleaner way to do it. Again, with Soligo, any objects that you wanna work with, it it's really just dependent on what the business needs to accomplish. So now let's jump into an AI flow. So there there are, you know, different different AI flows in terms of whether you're trying to, just use, you know, generate insights or do, you know, augmented generation of data where you're retrieving data and creating whole whole new datasets. So this is that customer three sixty, use case that I talked about where someone is able to basically prompt Slack and ask for data. So it starts with a listener where a, you know, a user is able to, prompt Slack. The data gets presented to, Biflow here, and then this is where, it can get, as advanced as you want. So if an account is found, like it's an existing, account in our our system, this is where we can come in here, get, all the data from all of our different tables in Snowflake. We can come across, and then we start, asking OpenAI to summarize their purchase history. So, hey, OpenAI. I've given you all of this data from my Snowflake instance. Give me a concise statement about this. And this is where you're able to come in here and and adjust the prompts that you might have, with your with your own LLM. This is in this case, we use OpenAI, but it could be any large language model that you have, and you're able to come in here and and, perform a prompt. So the prompt is as a is a field in the process. And so you can say, hey, LLM, you're an agent. You give me a concise answer. You can provide your own rules. And what's great about this is a user is able to come in here. They can check the output and say, oh, I didn't like the output from that prompt. Quickly come in here and change it. The flow runs again, and then you'll have a different prompt. So from the and and that's from the builder's experience. From the user's experience, they don't actually see any of that. They're just getting the output. And then you can see it it goes on. So, right, summarize the purchase history, get the tickets, summarize the tickets, get any information about them as well, do an industry search, company overview, right, any large language you want, and it's coming in and generating the insights. And then ultimately, that gets pushed back to, Slack, And the the end user doesn't see any of this. They're just they just or get, asked the the Slack bot, and they get their response, without realizing, you know, how many different disparate data sources are actually used to get that response, which they could never get if they were using an isolated, AI kind of chatbot experience in a single application. It it works very similarly for, the kind of the the analysis of the deal type. So in this case, we're gathering data from Salesforce, from Gong. We're transcribing that, asking again for, to determine based off of the transcripts, what kind of deal it is. Is this gonna be an expansion deal? Is this a is this a partnership? And then and then pushing that either back into Snowflake, for analysis or pushing that directly into the CRM. So really, when you're talking about AI flows, at some point along, the flow, you're invoking a large language model as a step along the flow, and you're controlling that using the Soligo connector, using the prompt engineering. And and so you have the ability to control that output, regardless of the use case, whether it's a deal type, review pipeline AI, experience, whether it's a prospect three sixty where you're actually they're not even a customer yet and you're, based off of leads that are coming in, you're asking for information about that company or whether it's an existing customer. Right? Anywhere that you could imagine you would want a concise summarization of the organization you're working with, that's a great way to inject AI into your CRM and ERP process, and actually get real return on investment. Right? This isn't just, hey. We built this because it's fun. Like, we actually get a lot of value from this. As a sales team, we're more efficient. We can, act faster with more accurate data. And then they are able to just really build on that quote to cash process that you're really just trying to accomplish. Alright. So that's kind of the conclusion of, the demo portion. Okay. Well, thank you very much, Nate. So let me just go over a couple quick things here, and then we'll jump in q and a. But, so first off, just so you know, as we have mentioned, previously, there's a couple links on the docs. So, specifically, we did do a a whole AI summit, you know, because we're seeing so many AI use cases. And this AI summit talks about, individual use cases, but also, like, how to achieve success, in terms of implementation of, AI projects, you know, especially in terms of identifying, certain, existing processes that you can insert AI into. And so I I recommend everyone check out the link that we added there and just watch, you know, the the the presentation, on the Saligo side of, how, we're seeing, AI integrated, in in AI strategies, AI workflows integrated into, our customers. The second thing is, you know, this whole series that, you know, we we've done a season now of, ins and outs series of network integration. They can all be also accessed, the recordings of this, via the link on the docs tab. The the last one in this series that we're planning right now will be in January on, specifically NetSuite and HubSpot, which is an increasingly common use cases. You can also access this via silio.com/webinar. And the final thing, you know, we mentioned this several times before. We have a NetSuite integration handbook, which covers, you know, the whole best practice and and options in terms of how to integrate NetSuite. This has been a really great resource to explain how you really wanna build your entire processes and operations around, NetSuite and, and and the the ERP for for growth and scale. So with that, let's, just jump into q and a's. So question here, we sell b to b products. If a product sales order comes in from Salesforce, do I build the fulfillment flow, and the order entry into NetSuite, within a single flow? You wanna. talk about that's a great, yeah, that's a great question. So it it it depends on, a couple things, most commonly when you're taking payment. So when if you receive the order and you immediately collect payment, like, as a cash sale depending on maybe the size of the the product sale you're doing, maybe you take payment immediately. Oftentimes, then the fulfillment record is immediately created. Right? You create the order and then it immediately create fulfillment because you've already had, the cash and you start the fulfillment process, even though the, you know, the fulfillment, record is created, but it's not fulfilled yet from the order perspective. Right? It has to, you know, be shipped, and then it gets fulfilled marked as fulfilled. If you're taking payment after the fact, typically, what we see is you create the order and then you work through the fulfillment process within NetSuite as you would any kind of standard NetSuite, order process where the order is received. Maybe it goes to the warehouse, or if you're working with the three p l, that can actually be another integration step. And then once that order has been you know, the the process of creating the fulfillment is actually done by a user when the product is packaged up and put on a truck, and marked as as shipped, then you create that you you know, mark it as fulfilled with a fulfillment order. But, really, it it, you know, it can be based off of what your business needs. It can be done in the same flow, or it can be done based off of timing as a separate flow where a three p l says, you know, order shipped. Maybe it's an EBI transaction, then they could create the fulfillment order, or you can, you know, basically do it based off of the timing of of when you ship it. So, just depends on typically when you accept payment, and how long it takes you to fulfill the order start. Okay. Thank you. Any other, questions? Looks like that was the only one. Let me just give it one second here for folks to see. Okay. So if that's the case, that's it. And, thank you all for joining. I hope this was insightful and helpful. Please reach out if you have any questions. We'd love to continue the conversation. Have a wonderful holiday, if we don't, see you, and, we look forward to connecting you for, the next time. Thank you, Nate, for a presentation as well. Yeah. Absolutely. Thanks, everybody.