Aleph for Fractional CFOs

00:00 Okay. I think we're gonna go ahead and get started. We've got a big group here today. Thank you everyone for joining. I'm David. I'm from the Aleph team and I work in the fractional CFO channel. We're excited to have you all here today. Over the course of the next forty five minutes or so, what I'm going to do is go really deep into the Aleph product and talk about how Aleph is being used across fractional CFO firms today, with clients of all sizes and client counts of all sizes. So over the course of the next forty five minutes, we're gonna go through an entire month close process from getting a client stood up on a left to automating budget versus actuals and actually building some dashboards together. I'm excited to have you all here today. I'm going have Lucas pull up the slides. I promise we'll do a couple of slides here and there, but this will be really in-depth into the Aleph platform. And where I wanted to start for you all today is just explaining a little bit about Aleph and our perspective in this channel and how we've worked with fractional CFO firms to date. But just for those of you that are new, Aleph is an AI powered FP and A tool. Originally, it was founded by Albert, one of our co founders, because he saw a need internally at a finance role that he was in.

01:22 He was spending so much time cleaning data and less time doing the strategic analysis work that he knew was most important to the business. And so founded Aleph a little bit over six years ago today. And what we found is that while Aleph is incredibly powerful for internal finance teams, it actually has a magnifying event for those of you that are working in a multi client environment, whether that's CFO advisory, FP and A advisory. And so we're excited to share a lot more today about how Aleph is being used across fractional CFO firms. I'll go really deep into the process of how it's easy to set up clients and manage a multi client workflow. But just a little bit of context about myself and why I'm in front of you all today. So as I mentioned, I'm David. I lead our CFO partnerships here at Aleph. My whole career has been in early stage finance work. I've worked at pre seed and pre revenue companies all the way through companies that have raised hundreds of millions of dollars and then gotten acquired by much larger companies. But right before this, I actually led an FP and A practice at a firm called Graphite. And there, I was managing a team of folks that were serving upwards of fifty to one hundred clients.

02:37 And I actually bought Aleph. We went through an extensive RFP process. We compared Aleph among a lot of competitors out in the space, and we actually bought Aleph, implemented it across all of our clients. And the team was really able to find all the scale and efficiency that I'm going to talk about here today. And so I'm a real life case study and excited to share a lot with you all about how the workflow works together. And I've been in Aleph for about the last seven months, I spend all day talking with fractional CFO and FP and A advisory firms, leaderships, people in the trenches every single day serving clients. And so put this webinar together to really show everyone at scale how Aleph can supercharge and empower your teams in serving a multi client environment. So I've got two more slides I'm going to cover and then I'll outline the agenda for us today. But we all know that the world of FP and A and CFO advisory is changing what feels like every single day. When I first started this role, Claude for Excel didn't exist and many of us didn't know what an MCP connector was. And today that world has dramatically changed. What has not changed, however, though, is Aleph and our position of where we think that finance teams are able to find scale and leverage in the work.

03:57 And that's really using Aleph as the center and the hub of all of the activities that you're doing, your teams are doing, that your clients are interacting with the data. By using the left as the source of truth, as the centralizing function in this work, no matter where you and your teams are doing their work, you're going to be able to get consistent and the same answers across whatever workspace people are working through, whether it's in Excel and in spreadsheets, whether it's in our web app, or whether it's in your LLM of choice or Slack and Teams. I'm going to show a couple of those workflows here today. I won't go into all of them, but the general premise that we want to cover is that we know there are so many bespoke and unique use cases across all of your clients, but using Aleph as the standardizing and galvanizing force across all of your work streams is what's going to allow you to find that scale and leverage. And so to talk about it a little bit in detail, where this entire process for us starts is getting your client data into their own workspace, getting it centralized.

05:05 That's on the far left of the slide on our screens today. Today we have over one hundred and fifty integrations that are live, all of the most popular ERPs and HRIS systems, CRMs, and we're continuing to add integrations every single day with the idea that finance teams are spending too much time logging into systems and pulling reports and not doing enough time in the analysis. So we're solving that on the first part of the slide. In the middle part of the slide, this is gonna be really the pain point that many of us feel day in and day out. There's often a lookup tab in a model that's based on the GL codes and we all know accounting adds new GL codes or clients adds new codes. And the downstream effect of that impacts our models, impacts what we do, or we have budget scenarios that maybe somebody left the firm and we lost that budget scenario. We don't know what the board approved version was. Our belief is that when you put all of that data into Aleph and you use Aleph as the standardized and centralized warehouse, that's what allows the supercharge of all the efforts here on the right.

06:12 So whether, again, whether you're working in Excel or Sheets, or you want to work in your MCP of choice, Aleph is going to work in all of those use cases to help you access the same data. So that's enough of me talking to talk a little bit about the product. What I want to talk about now is what we're going to achieve over the next thirty or forty minutes together, which is really a five step process of a month close process. We're going to go all the way from helping get a client set up in an Aleph workspace, understand a little bit about permissions, and I've got some ERP data already connected. We're going to go all the way through dashboard experience and the AI experience in our dashboards, and we're going to cover everything in between as well. I'm going to show some pre populated data to do some illustrations. I'm going to show some brand new data along the way, but excited to have you guys along in this journey. If you have questions as we're going on in this process, feel free drop them in the chat. We've got both Lucas and Joaquin from the Aleph team managing the chat. I'll keep an eye on it as well, but really wanna make sure that we get a great perspective and a great insight into the power of the Aleph platform for you all today.

07:26 So without further ado, we'll pull the slides down. Let me share my screen and let's go right into the Aleph platform. And I'll give you an idea of what it looks like behind the scenes. Great. So first thing that I'm looking at here is the Aleph web application. What I want to start with is that every single client, every single workspace has its own individually set permissions with its own rights and user access, and that's incredibly important in a multi client environment. What I'm showing here is a demo workspace we'll use for our purposes today. You can see I've got people that are in different groups. I'm able to set up different groups with different permissions. So as we think about what internal teams are gonna do versus what our clients need to be able to access to do, we can get down into the permission level access on an individual budget scenario or an individual integration so that the right people are gonna see the right level of data every single time, and we don't have to worry about them seeing incorrect information or information they're not supposed to see. That's the first part of the Aleph platform that is specifically designed for a multi client environment.

08:36 You can see here, I've got a bunch of demo workspaces that we'll play around with to start. That's where we start every single new workspace. Every single new client that you bring on to Aleph gets its own workspace, your team gets added. And then the first step of what we do is we run-in integrations. And so I've got a couple of what I think is our most common tech stack that we see across our client base, whether it's NetSuite data or Rippling data. I've got some CRM data we'll use along the way, but being able to add an integration for us, and many of us probably interact with QuickBooks Online, is a quick five step process logging in using your accounting credentials. I don't have a QuickBooks account, so I can't do that live today. But basically, as soon as you enter through your credentials, you can determine who needs to get access and it walks you through just logging in using your QuickBooks credentials. And we would basically have data available using QuickBooks or sometimes even Net Suite by the end of this demo today. That to me is the second part of the value prop for Aleph that's incredibly powerful is the right and the ability to be able to control data, be able to spin a new client workspace up with just a matter of clicks is what makes you be able to go back and actually do the work on your client engagement and not have to worry about a week or a month long implementation process.

09:58 That's the first part of this process. The second part where I want to go is one of these hidden features of Aleph, which is going to be called the mappings. So the mappings, I alluded to this a little bit already, but this is that lookup tab that exists in every single model. What we're doing is we're bringing that into Aleph, we're building that into a systematic approach, we're being notified when new accounts are being created. So let's say I just linked my NetSuite data and I want to go through and I want to map my entire income statement. And so normally what people are doing is we're grabbing things like the account type and probably the account name. I could add as many dimensions. Maybe I want department names. Maybe I want, specific transactions to be coded a certain way. But for purposes of today, let's just say that I've got a new reporting category, and that's what I wanna call it. What I'm going to be able to see on the screen is here's my full list of the GL accounts that I want to map, and it's going tell me all of these are pending. I've got fifty six accounts to map. Now, if I already have this as a existing client and I already have done the mappings myself in the model, we make it easy to be able to download the report, copy and paste your values in and upload it, and it ultimately is able to be uploaded in the system.

11:15 And you've mapped all fifty six accounts in probably a couple of seconds. But for me, this is a brand new client, so I actually want to use our AI features and I want to be able to have our AI start to identify these categories based on a series of information based on what my team standard mapping is. What I'm going do is I'm going click into this gear icon and I'm going to copy and paste this prompt, which I have about seven mapping categories that I like to do, whether it's revenue or COGS or some of my OpEx accounts. I'm going to hit save into my rules, and then I'm going to let the AI agent go through this process. It's going to take me about fifteen or thirty seconds to go through this process, and the AI agent is actually going to go through every single account, propose what it suggests the mapping is going to be, and then give me a chance to review every single one before I actually accept it and map that back to my GL account. For me, when you build around standardization and processes that are repeatable across the entire team, that's where you're able to find the scale and efficiency, and our AI agent is already done. Okay. I'm looking through this.

12:23 There's a couple here that I probably wanna reject. Maybe I wanna call this one cogs. Let's see. I think this one is also cogs. I can go through every single one and either accept it or I can reject it as you saw me do. And you can see it's moving them from pending to okay. That's the process to go through the mappings for the first time, and then you never have to go through that process ever again. I've just accepted them all. You can see I have no pending mappings here, but let's go back to my list, and I've got some other accounts where they're pending. I can actually get alerted over Slack or email or Teams every single time that integration runs when a new account is added, and I can actually let me or my team know that new accounts are added and we need to triage it, in order to be able to update our model correctly. To me, that is the time and the efficiency of where Aleph is able to be incredibly powerful in a multi client environment. And for me, what I set up my team for is they basically had their own set of Slack channels that were specifically related to the alerts. And that's how they were triaging them, whether it was every day or every Monday at eight am.

13:33 That was the first thing they were doing when they were coming into their work week. So they knew that what they were pulling and sharing with their clients was the most to date information. So I'm going to pause there for a second. Let's bring the slides back up. And I want to just show that over the course of our first ten minutes together, what we were actually able to accomplish was we stood up new clients by showing individual workspaces. We connected ERP in a pseudo environment here today. And then what we started to do was we actually mapped all those entire GL accounts, fifty six accounts, all within the first ten minutes of us together. That's the process I really wanna, make sure we're clear about is this is not an abnormal process for us and the firms that we work with. Being able to connect the data and being able to pull the information down is literally that simple in a multi client environment. So where I'm gonna go next is I'm actually gonna show you how we're gonna start to use that information. We're gonna prepare a mock budget for you all, so that we can actually see what it looks like to then automate the BVA process, and Then we're going to go into the dashboards. Again, if you've got questions as we go through this process, drop them in the chat.

14:45 Our team's monitoring there. Let's go back to Aleph. Let's go back to Excel, and I'm going show how we're going to start to use some of that model information that we just loaded in a standard financial model package for us. So what I'm sharing now is this is my fractional CFO template budget. This is where I want to start doing my monthly reporting for a client and these same reporting categories that we just used in the Aleph web app. I want to use that information to start to populate what my monthly package is going to look like in the client. Now, I've done a little bit of prep work to get this set up for today, but you can see here, I've got my months across the top. I've got these reporting categories here. And what I want to do is I want to pull all this information in. It's going to take all the information that came out of NetSuite. It's going to populate all that information into my model template. And as long as you're following the consistent formatting and styling, you can see I was able to populate all this information in just a matter of clicks. Now you may be thinking, David, these look like hard coded values.

15:52 You don't actually know what's underneath them or you don't know how to quality control them. It couldn't actually be further from the truth. So let's say I wanted to drill into the sales and marketing expense. Using the Aleph add in both Excel and Google Sheets, I can actually get to the underlying general ledger transaction details in just a couple of clicks. You can see here, I've got a multi entity scenario in NetSuite. I've got all the GL information. I know exactly what month it was spent in, and I know exactly where it came from, but that information is incredibly overwhelming. So what I can actually do now is I can start to use, another feature of our add in to actually drill down by any additional field that's been brought in through our integration. So for me, drilling down into sales and marketing by vendor name is oftentimes where I'm starting to think about how I want to look at financials from the prior month. Again, my team is not doing any of this work manually. You're not doing this work manually. The system is doing all the work, and it's empowering you to be able to look at your financial information and your client's financial information in just a different way. If I wanted to keep going down and say, hey guys, I don't know what happened here with Google Ads, or I don't I really wanna understand what this variance in Trade Desk is.

17:08 I can keep going through every step of this process to ultimately get back to that same source level of information. I'm not touching the ERP system. I'm not going back into NetSuite to run my saved search or QuickBooks to change what client I'm in and where I'm going to toggle. All of this information is at my fingertips and my client's fingertips to be able to use in their modeling exercise. That's the first thing is, okay, I've started to get some data into a model. I'm starting to understand what's going on, and then it's time to actually go through a budget. And so for the purposes of today, what I've done is I've prepopulated a budget based on what I think the business was gonna achieve in the year. Normally, as we all know, this tab gets hard coded and copied into another file. It said board approved, final version d probably seventeen, and maybe somebody's initials. The source data is all missing. I'd never know how to actually get back to it, but what we're gonna do is we're gonna let your team continue to model and accelerate Google Sheets, and I'm gonna use our feature functionality that we call a connect push to actually get this data back into Aleph.

18:17 So I've done all the modeling. I've done it at a reporting category that we just mapped out. All I'm gonna do now is I'm gonna push this data back in. Let's say this is the DGR o eight twenty six twenty six forecast, and I'm gonna push the data back into Aleph. I started with a completely blank table in Aleph to automate this process, and now what I'm gonna show you is this is gonna take about fifteen or thirty seconds. All of this data is getting housed back into Aleph, and Then we're going to automate the entire budget versus actual process. It just told me the push completed. Let's go back into the Aleph platform. Let's go look at that forecast table that I just filled out. It tells me it was just filled out a couple of seconds ago. And the part of this here is that you can actually see all of the revision history, all of the history that happened on the table. I can actually roll and restore any of these versions back. And so there's never any questions about who did something on my team or when was that number changed. We have a full audit log across every single dimension that exists within OFF, and I can trace and I know exactly where that information is.

19:26 What we can also do is I can also set up permissions, especially in a budgeting scenario where maybe what I actually want is like, everyone should have access to this forecast. What I actually want is that, okay, this forecast is actually only for, by default, no one gets access, but maybe my finance team gets edit access and everyone else doesn't. This is where we're able to collect inputs in a budgeting process from multiple stakeholders without having to change their permissions in an Aleph workspace because I'm able to go down into the individual rows and transactions, and you can see with just a couple of clicks, I was able to edit who can actually see the budget forecast scenario that we just pushed in. So it's living in Excel and the work that my team is doing. I'm able to control it on the permission side. And now let's see what this is gonna look like in a budget versus actual scenario. And let's just pick on the month of April twenty six. So what I've done in the background is I've actually, combined actuals from our ERP system. I've combined that forecast data we just pushed in. And so what I'm gonna use is a function that we call explore. This is think about this as just like a pivot table style experience. It and what I'm gonna do is I'm gonna use this, EVA version two table I created for the purposes of this demo.

20:47 Now what I wanna say is I wanna filter, and I wanna do this just for the month of April twenty six. What I wanna be able to compare is those scenarios side by side. I'm a little lazy, and I don't like to do math, and so I'm actually gonna have the tool start to generate, the math for me and compare the VBA. And then let's just use things like account type. And remember, we use that reporting category to standardize the accounts. And let's just format this as financials, and let's, pull the data. In just a couple of seconds, it's gonna run a full BVA for me, and it's gonna do all the comparisons for that entire month. So you can see here in my actuals, it looks like I actually had a revenue beat for the month of April. It looks like I, had about an eighty three thousand dollar beat in the month of April, but I massively overspent on my expenses. And it looks like a lot of this is coming from my payroll and benefits line item. Now one of the downsides of how we push this budget is that we pushed it at a very high level without all the supporting information. I'll say some firms like to do it this way. Some firms choose to do a more of a bottoms up approach.

22:05 What more of a bottoms up approach is actually gonna allow us to do is go actually a lot deeper into this use case and start to see some of the feature functionality of Aleph and some of our AI features with a little bit more detail. So I'm gonna show now and shift a little bit more of like a bottoms up forecast to show a little bit of like how probably many of you are budgeting today, which is at a vendor level for your clients across the GL. So sorry. And so this is probably very similar to how many of you are budgeting across your clients today. It looks big and ugly, and maybe you don't have all the analysis behind this, but this is how they're proposing how they're going to spend every single budget across every single vendor. So now let's take this approach one step further and show what it looks like if you're pushing the most granular level of data into Aleph, and what that means from a budget versus actual process. So I'm gonna use a different BDA table, but we're gonna run the same prompt. We're gonna do the same differences month over month. I'm gonna come back to the same month, and we're gonna run, twenty six zero four zero one.

23:17 And we're gonna run this by account type. And in this budget scenario, I only have it by the GL account. I don't have the full, mappings like I just applied, and I'm gonna repull the data. And so now what you're able to see is it did I've got a couple of different budget scenarios. And so maybe I wanna filter down into just my actuals and my current version, and I'm gonna pull the data. And now I've got a full BBA for the month of April. And I've got some variances here, definitely that payroll is over budget, but what I wanna show here is our first AI feature, which is our pull and scan. So on any report from any data source, what I can actually do is say, actually, what I want to do is go down to the underlying transaction level information and start to understand what changed over my budget assumptions. So I set a threshold of, I think, five percent and five thousand dollars Our AI commentary is gonna go through all the underlying transactions at the general ledger level. It's gonna start to understand exactly what's going into those accounts and come up with a conclusion of what we want to be able to drill into even more. And so I'm gonna give this about thirty more seconds.

24:30 You can start to see the level of granularity that when I push vendor level information in, I'm able to get out of this. So let's click into this advertising for just a second. Really long list of items here, but it looks like I've got some Google Ads and some Meta Platform and some Amazon. So, but I don't understand exactly how that actually was occurring against my budget. So let's select these values here and let's do this drill down again by the vendor level. And you can see it's already highlighted in purple as a suggested way to summarize the data. And so what it's gonna actually do now is be able to compare the full budget, which is my current version, against my actuals and give me the variance. And so instead of me and the team having to spend time pulling data, building a custom report like this, probably in a bespoke pivot table, I'm actually able to get much faster to the analysis of the conclusions of the conversation I want to have with my clients instead of having to make sure that I downloaded the right report, that I understood exactly what I was going to do. And I've started to work through some of the AI variance commentary that's most meaningful to my client because now the conversation is, hey.

25:45 Was this overspend on advertising across Meta, Amazon, and Google Ads? Was this a onetime use, or do I actually need to build a new forecast? And we should think about what this is gonna do to our cash burn for the rest of the year. That's the work that your clients really want out of you, but you need to do all the groundwork behind it to be able to find that initial conclusion. So I think, Lucas, if we could pull the slides back up, I wanna do a quick pulse check now that we're, about twenty five minutes into the presentation. So where we had just left it was, we had just started to do the budgeting process. I think we can call the next one complete, which is we loaded a budget in, we're able to automate the BVA process. And now we've actually knocked off the next one as well in the first twenty five minutes of our presentation where we've started to let AI surface exactly all the variances that are worth us investigating. To me, this is unheard of. Like, I know I used a little bit of dummy data for our purposes today, but all of you are building models for your clients today, and you're doing this exact workflow that I just replicated in the first twenty five minutes of us spending time together today.

26:54 This process, when I was doing this work myself, would have taken me probably three, four, five hours. And the whole premise of Aleph is that if I'm able to find two hours per client per month, every single month across all the clients in my book, think about how much more that's either going to allow me to take on and serve in more clients, or how much if I'm billing in a fixed fee model, how much margin I just was able to drop to the bottom line, and then I can take on more clients at higher margin work as well. That's the whole value prop I wanna make sure that we all leave here with today is that these are not the most complex workflows that we could for. We can do that more on a tailored demo. We can do consolidations. We can do eliminations. We can do foreign currency conversions. All of these unique use cases that just take your team time month in and month out, that's how we're using Aleph across all of our firms that we work with to help them support and automate their workflow so that they can spend time doing the forward looking, the analysis, being that strategic partner to their clients. So we've got, about fifteen minutes left. Where I wanna go next to show you a little bit about our dashboarding and some of the AI features that exist.

28:13 But again, if you've got questions, feel free to drop them in the chat, send our team a note. But where we're going to go next is we're going to show a little bit of the dashboarding in our AI agent to understand specific workflows and how you're ultimately going to be able to present information to your clients. So what I'm going to click into, you can see I have a laundry list of dashboards. Part of how we work with every single firm is actually building a template dashboard that's able to be used and deployed into a client engagement in just a couple of clicks. That's what we solve for in the for thirty days working together so that you can get up and running and delivering your clients analysis. But let's click into the CFO dashboard, which is the one that I feel personally about being able to deploy for my clients. So remember, we just closed April in this dummy data. Now I need to think about what I'm going to do to ultimately deliver to my clients. And so I've got a combination of written text summary. I've got some combo charts and bar charts. And what I'm trying to do is surface the most relevant information to my client so that they can understand what's going on in their business. And we know that every client maybe have a different financial literacy in how they interact with their data, and so we can customize this based on what is most pressing to them.

29:31 First thing I'll highlight here, this is an AI written summary that just is built around a skill that we embed into every single client workspace. So I've told that I want a specific format that highlights budget versus actual information. I've told it, how I like to receive formatting information and number formatting. You can continue to customize it, and you can even put your client's logos and colors on every single page of the dashboard. You can see across the top, I've got a slew of information that I can share with my clients. I've got all their standard financial statements across whether it's balance sheets or cash flow statements or income statements. All the charts, every single data source that exists on an Aleph dashboard is also interactive just like what we saw in Excel. And so if you remember, we clicked into that advertising budget, and I can use that same drill down here, go down to the same vendor name. And because we're bringing the source data into Aleph, I know I'm gonna get the same answer whether it's my financial analyst, whether it's my CFO, or whether it's my client, we're all gonna get to the exact same answer every single time. And that's what gives me the peace of mind being able to deploy Aleph across my client engagements.

30:46 So those are kind of the pretty standard. You know, I've got financial statements. Maybe we've got some expense information that we need to drill into. We can even do department level budgeting and analysis, and we can use in our interactive filters to say, I want to be able to drill down into whatever information I have available, whether it's departments or classes, or I want to look in specific departments, I can use all of our filters, all of our account names and say, okay, I really want to click into, let's pick a COGS account. I really wanna drill into legal fees. And you can see as soon as I make changes on the dashboard, I broke something on the dashboard, but you can see I've got a vendor summary. I've got information that's available for me and my client to be able to drill down in real time. All of that, what it also means is that I can drill into my budget versus actuals in a web based format. I've got, my prior month on the left side. I've got year to date, but I'm not very good with numbers, and I wanna be able to understand to my client, help me understand my marketing budget variance for twenty six.

32:00 That's a type of question that many of us are able to understand. Our clients are asking us this as we go through our monthly financial call, and it and it means we need to go then research all the work. We need to validate all the numbers. And what we're starting to do is we're using our AI to actually answer that question for us just like any good analyst, senior analyst would do. But what it's also gonna do is be able to produce a sourceable and traceable answer. AI is only powerful enough and only trustworthy enough when I can actually know exactly how it got that answer. I'm gonna get the same answer ten out of ten times, and I know whether it's my CEO of a my client asking a question or one of my accounting team members, they're going to get the exact same answer every single time. And part of what we do here is you can actually see the thought process. It's showing exactly, okay, here's where I pulled the data from. Here's exactly what it's filtered to. I'm gonna work through all the conclusions, that it works through. For me, this is a very simple use case. Help me understand my marketing budget variance. We know that there are so many more powerful AI use cases that we can bring, to how we serve our clients. And so one of the ones that I love to show most is every board, every, month quarterly financial review has a slide that says the three things that went well and the three things that didn't go well.

33:24 Well, I built a skill in Aleph and I said, I want you to build it in exactly this format every single time. And it did this entire work for me. And what I don't have to worry about is that it didn't hallucinate because at the bottom of it's work, it gave me the sourceable and traceable information. This prompt, takes on average, like two to three minutes to run, so I won't do it here today. But think about that most complex workflow that you're running on behalf of your clients, and how do you take the low level work that's ripe for disruption and have AI use it because now you've got all your client data in one source of truth that allows you to do your work. I just got a notification our AI agent is done. So let's go take a look at how the marketing budget did. So looks like a year to date, we were pretty unfavorable about one hundred and twenty seven, but wow, actually all of that work actually happened in April. You guys can see the prompt that I asked it for. I didn't ask it to do year to date and I didn't ask it to do the April alone, but now I know that all of my variance is actually happening in April. And let's see, did the agent actually give me some more conclusions? Yes, it did. Okay, look, here's the spend. Oh, it's gonna tell me the exact source data that it used to be able to produce that information.

34:42 Wow. Here's that same summary that I saw in Excel. I was able to replicate it in an Aleph dashboard on my own by using the drill down, and now our agent was able to, replicate and produce that exact same report entirely on its own with very little prompting from me. This is what gives me the peace of mind to be able to deploy Aleph in a multi client environment is that it's all sourceable and traceable, and that I'm able to present this to my clients and deploy this at scale without having to worry about them getting the wrong answer. What it gave at the very end, who owns, worth buying who owns the marketing budget. The annual overage will compound below this. Do you actually want me to pull a trend of actuals versus budget, or do you wanna do this as a one off? Our agent is trained in specific FP and A context around our semantic layer, which is letting us know exactly where to look, what tables it's gonna pull from, and that it's giving me the source of all untraceable information. I think Lucas, we might have achieved everything in the first thirty seven minutes of this webinar, but let's take a look at those slides again and let's see if we answered everything that we set out to achieve. Okay. So we had left with the AI summary right before this.

35:54 And, wow, yeah, we just delivered a full client financial dashboard. Okay. Well, wait. I did the dashboard, but now how do I share it back with our client? Let's go back into the dashboard for just one second to close this off, and then we'll close with a couple of slides. So we know that dashboards are only good if and when our clients are actually going to use them. And so how do you notify them, that a dashboard is ready? How do you use this during your monthly financial review? And how do you keep a record of it along the way of what was ultimately produced to your client so that it's not just a flat dashboard? Put a lot of features around this first and foremost. So first, anytime you want, we can actually export this entire dashboard as a PDF. It'll ask me which pages and which charts I wanna generate, and it'll give me a really nice looking PDF package if I want it that way. We don't recommend sharing it that way. It generates it as a flat file, which we know some people want. What we love is this feature that's called, send an update. Think about this as your favorite Google sharing settings where I can determine exactly who I'm gonna share it to. I can customize the message and say, April dashboard is updated.

37:03 I can send this out via email. I can send this out via Slack or Teams if I have, if I've connected to my client, channels that way, and it's gonna send them a note with this message and a direct link to their dashboard that they can actually log in, they can interact with their data, they can come back to you with questions. We've got some great features coming on the dashboard side that's gonna include some, versioning and some version control, which we know is really important. We also can use this in presentation mode if I have specific slides or views I wanna be able to share. And every single chart, every single part of our dashboard, we have a plugin that exists both in Google Slides as well as in PowerPoint. So if I wanna put this management dashboard slide of my revenue versus my gross margin mix, I can do that and directly link so that every time I update the dashboard, I hit refresh in my PowerPoint slides, and no more cutting and pasting, no more worrying about what the latest set of information was because everything is entirely sourceable and traceable back to the left dashboard. I think Lucas, let's bring the slides back up. I'll stop sharing my screen and we can, feel free to we'll go through the last little bit of, the presentation.

38:13 If you guys have questions, feel free to drop them in the chat. Send Lucas or Joaquin a note over the DM. Here we go with the slides. So over the course of the last forty minutes, what I really wanted to make sure that we could achieve is that we did an entire month close package for you on behalf of one of your clients. We linked the ERP data. We pushed the budget into Aleph. We ran an automated BVA process, and we used some of our new AI features to be able to highlight variances and ultimately present a client facing dashboard all in the course of forty minutes together. That's the most time investment it takes in order to get Aleph up and running for one of your clients. You're not pushing a new budget probably every month. You're not having to relink their ERP. That process just happens automatically every single time. So if you think about, wow, can I spend twenty minutes actually getting a model out the door to my clients? I've got a dashboard that they know and I customize to them and it's in their branding. How do I go spend the rest of my time and how do I think about how I'm going to continue to be able to grow my practice now with this technology at my fingertips? So I know I've covered a lot here today.

39:24 For those of you that I'm connected with on LinkedIn, we just released actually earlier today an ebook on my thoughts about the fractional CFO and FP and A, industry, talking a lot about automations and AI. And a lot of the features that we covered during the course of this webinar today are going to be talked about in a lot more detail. So there'll be links at the end of the presentation. We'll send out follow ups after this, but there's about a five part series about implementing AI and FP and A tooling at your practice and what you can expect out of it. It's a really important read. But the most important part of that ebook is there's a full checklist at the end where we give you a real view of what's going on in your business and how do you monitor and measure success. I see Lucas just dropped that here in the chat. So thank you, for that. And I know you've heard a lot of me talking today. We know that social proof is the really important metric of this as well. And so we're supporting some of the best fractional CFO firms, private equity backed companies and funds, and standalone companies are using Aleph.

40:34 And I know some of you may be thinking, well, I only have one or two clients. Aleph isn't for me. We've designed our pricing and our structure to be able to support people with two clients all the way through two and five hundred clients in a multi client environment, all focused on finding the scale and efficiency in an ROI positive way. Greg from Ativo is a great champion of ours. There we have a whole dedicated web page of the Aleph website devoted to the fractional CFO channel. You can watch testimonials from folks like Johnny Walker at Rule and Chris Masa at Graphite and Greg as well. All of them are great partners of ours, but we're adding new firms onto the Aleph platform every single day. And that's the part of the job that gets me really excited because that means that people are getting time back in their workflows. They're able to generate more efficiency at the firm level, and ultimately, you're able to serve your clients better and faster. The last slide I'll share is, well, what do we go do next, David? We're interested in learning more. Well, first, we've got some time here today. If there are any questions from the audience, feel free again, drop them in the chat. Oh, I saw one just came through.

41:46 This hinges on the client having an ERP setup. The short answer to that is it works a lot better if you have a client with an ERP that we integrate to, but actually we have some early stage companies that are keeping kind of a makeshift general ledger just in an Excel spreadsheet today. And we can actually work through a process like that as well. And then of course, we support all the clients through, very popular and large ERPs like NetSuite and Rilla and Campfire. So it doesn't have to be just that your client has an ERP. It's a little bit easier if they do and if they have the systems in place, but that doesn't have to be, the hard and fast rule. If you're interested in learning more, please feel free to add me on LinkedIn. I love to connect with Fractional CFO and FP and A folks all day. Download the ebook that Luke has linked here in the chat, but also we'll be posting that and we'll send it out to everyone after the webinar along with this recording. Then if you're interested in learning more about how Aleph could be embedded into your firm workflows, drop us a note. My email, we'll send in the follow-up.

42:50 It's just davidgetaleph dot com. We're excited to have the conversation with you all. We know that this is an environment that's changing what feels like every single day, maybe every single hour. And we're excited to partner with you all in learning more about what your tech stack is and how you're serving your clients. But lastly, I just wanted to say thank you to everyone here. We've got an entire team that supports this channel. Joaquin, who many of you will hear from works on my team as part of the CFO partnerships team. We've got dedicated customer experience folks that are designed to work specifically in this channel, been supporting all of our firms and our thousands of firm clients that are with us. And I feel really passionately that Aleph is the only FP and A tool that's really designed for the fractional CFO space. And I can say that having bought Aleph now talking to many of you every single day, and I get up excited every single day about what we're doing in this space. And I hope to have the ability to have a conversation with you all very soon. Thank you so much for your time. It was a pleasure. Thanks for spending about forty five minutes with us today and excited to talk to many of you soon. Have a great day and we'll talk soon. Bye bye.