Name: Builders Showcase: What HR and Finance Leaders Are Building with AI Today
Uploaded: 2026-10-15T19:33:18.855Z
Duration: 1 h 33 min
Description: Builders Showcase: What HR and Finance Leaders Are Building with AI Today

Transcript for "Builders Showcase: What HR and Finance Leaders Are Building with AI Today": Hi, everyone. Welcome. Welcome. We're gonna give folks a few minutes to come on, but we wanted to bring on the builder. So, yeah, feel free to put in the chat where you're, calling from, who you are, and, stay tuned as we get started. But builders, I know we were just talking backstage how you all feeling or... Yeah. Excited to share. Excited to get the collective intelligence, like, the whole build community. Like, we're just a couple people. Super excited to hear other people's thoughts. Just a couple builders. Just... Just. just people, hands, computers. You know? Computers. AI. Oh, there's an AI thing. Yeah. Just that. Yeah. No. This is, really is gonna. be great. I'm I'm kinda excited to see what everyone's been building. I like to keep it simple. So hopefully, I can share something that... That's useful for people today, but really excited. to see what the rest of you have built. I know. As I say, yours isn't simple. It's impressive. Yeah. I was gonna say keeping it. Oops. Is that a teaser? Yeah. It's beautiful. It's beautiful. Yes. It's. a beautiful. workflow. I've never seen anything like it. It's one of a kind. Yeah. Yes. Oh, Draper. Okay. Oh, there's Ethan. Sorry? I mean, I just saw Draper, like, a location nearby, and I was like... Yeah. Never mind. It's one of the one of the crew, one of my teammates. we have we have crew members from, you... Your company's here too supporting. I assume. some. Love it. Okay. It's 203. I think we can get started with the intro. So like I mentioned, hello, everyone, and welcome to the builders showcase. I'm Vanessa, the host of today's showcase, and I am at Rippling doing content and storytelling. So before we jump in, just wanna do a quick housekeeping check. So feel free in the comment section to introduce yourselves like I see a lot of you doing already. Outside of your location, you can drop what brought you to today's event, who you are, what you do, your LinkedIn, all of that. This is an open community and space. And then, also, if you have any questions for the builders as they share what they're... What they've built, you can leave that in the q and a, section. And this will be recorded, so you will get the copy afterwards in case you wanna rewatch. As for the agenda for today, we're gonna kick things off with a little roundtable session, and then we'll dive into the showcase. We'll have a q and a at the end, and stay tuned for the live voting for, an AI builder audience winner. So folks submitted their AI build to us, and we are gonna do a live voting for who wins the $500 Airbnb gift card. So that will be at the end. And if you don't already know, here are our incredible builders on stage. We have Chris, Brendan, Karen, and Leif. So, with that being said, I'm gonna stop sharing. And before we dive into our quick roundtable, I'm gonna go around the table. And could you introduce yourselves for the audience? I'm gonna pass the mic to Chris since you're right, next. to me on the screen. Yes. Thank you so much. So I am Chris Vielle. I am the head of operations and finance at Partnership on AI. We're a nonprofit organization that work on ethical AI. And I take care of, you know, the everyday, operations, building a lot of automations, a lot of workflows, and, working that on finance... On the finance side as well. K. Awesome. Brandon, you're to go. next. My name is Brendan. I'm very fortunate and grateful to, support the people team at chess.com. If you don't know, chess.com is the number one place to play, learn, connect, anything chess related on the Internet. 200 and, I think, almost 80,000,000, users now. If you're looking for a place to play, come on board. Shoot me a challenge. My my username is Brendan w, but, very happy to be here. Very excited. I can jump in. I'm Karen. I'm the head of people and talent at the guarantors based in New York. And I, head up my amazing team that touches all people ops, recruiting, and business partnering. Man, my name is Lay Foldert. I'm the VP of HR at Click Lease, which is a fintech located in Salt Lake City, Utah, and then about half of our team is located down in Costa Rica. So shout out to our TICOs down in Costa Rica. Yeah. We're a fintech company that supports overlooked and underserved entrepreneurs. So we're really out there supporting the weekend warriors that are looking to start up their company or grow their company. So here to support entrepreneurs with access to finance to be able to get the equipment they need to create a business. So I know everybody out there has a dream. Right? This is... We're here today to talk about our dream builds, so I won't talk about entrepreneurship. Entrepreneurship. I mean, that's kind of it's kind of the theme of being a builder, really. So thank you all for doing the quick intros. I wanna kick things off by saying, I think we're in a very interesting moment in time in, like, the state of work and what the future of work is gonna look like. Obviously, AI and technology has just been changing so much, and there's a lot of a lot of uncertainty. But I I wanna pass, or I wanna take a different angle at it because you all have been approaching work with almost like a new lens, being open to build things, being able to design systems and ship prompts, skills, workflows, whatever it is. And so I wanna ask you all, like, what was the moment for you where you decided to become empowered in this moment of time that we're in and and approach work as a as a builder? So, if anyone wants to take a stab first. I can jump in. I think for me, it's, I've never been satisfied with the status quo and especially in the HR world. There's a lot of manual redundant kind of just boring work, and there's so much more work that is interesting that takes more time. So by reducing the amount of repetitive tasks, that we can find a better way for, we can have those more interesting conversations and and time well spent. Yeah. I love that. I agree with that. I think for me, it was less about a moment and more, some of the things that I believe that maybe were a little more abstract in the past are starting to become, the best way forward. So I've maybe gotten lucky or it feels like I've gotten lucky in that sense. I've always been of the mindset of if if we build great systems, then we can spend our time doing more important or more impactful things. And our ability to do that was maybe one of the the leaner things in the past, but where we're at today, our limit is our imagination. So I'm really just excited for the future that we've arrived in in that way. Wait for Chris. Any thoughts? I, Go for it, you. know, I I agree with everything you guys said. I think that, I was always excited about what's the, you know, the new thing and how how it can... I love automations. I love making things work smoother. I love streamlining. That's something... You know, I have a brain for puzzles. Right? Give me a problem. I'll find a solution. So, AI is just a part of it, shaping my work in that way. And especially working... My career has been in nonprofits. So it's always very, very lean teams in nonprofits. Right? You have to wear multiple hats. And so having that ability to create systems that work for very small teams, and we can accomplish a lot with with the lean team is very important. So all of that together, for me is... Yeah. That's what is pushing me forward. I don't know if there's additional, like, comments I can make other than just saying, like, I've been an... I've been a early adopter. Like, I've always been a big... A dreamer or an ideator. So, I mean, workflows... When workflows came out, it was incredible. Right? Super exciting. Let's let's let's get it. Let's automate everything we can. And then AI comes out and it's like what Brendan said, like, our imagination is is the limiter now. Like... So it's just fun being able to collaborate and build as a team and be able to, like, augment ourselves in ways we never were able to before. So... Yeah. Just having fun, being able to create, which is that entrepreneurial experience, I guess, with Vanessa, what you were talking about. Like, it isn't... It's an entrepreneurial practice, but some... Now we just get to be entrepreneurs within our own companies. Yeah. Yeah. Exactly. I feel like the definition of, like, entrepreneurship is expanding too. There are so many ways to, like, express entrepreneurialism, if that's weird. But, no. I love I love what you all are saying. And I think that's also why we wanted to... We've reached out because we knew that you were already, like, pushing what's possible, not only inside of Rippling and with Rippling AI, but in general, you're already thinking this way. And I think that's really special and very inspiring for people, hopefully. So, I guess my my last question here is, you know, even though with AI, we're we're given the opportunity to to now, like, create almost anything we can imagine, there still comes, like, the importance of, like, constraining ourselves to to really understand, like, why do I want to automate this and why shouldn't I? And so I'm curious, like, for each of you within your functions, whether you're, like, finance or HR or even just broader in the business, How have you been approaching, knowing what... Where human judgment is most valuable from where AI should take an offload like that work? Like, how do you how do you draw that line? I have, a saying. Go for it, Karen. I I I was gonna say I... It's more, as I was saying before, like, the the repetitive tasks. Right? So that's where we start and, looking at where does that reduce our workload. And then if there's any friction points with that automation, we we kind of iterate as we go. If If there's a friction point, where is that friction point? Does that mean that it requires a a human touch or not, and kinda take it one step at a time? You know, as Brandon said, our imagination is the limit. I wouldn't say, you know, aim really big, to start. Just kind of start smaller and build on it has kind of been my general approach. I I. think about it as getting the right information in the right place at the right time, and AI has helped us to do that more quickly. And where that line is between human judgment and it just being information is sometimes evident by just going through that process. And what I mean is once you've done the work to make sure the information that you need is present and available, If the information itself is the answer, well, then there's very little human judgment that you need to apply. You may have just automated the whole process. But if you're moving that information or that data from one place to another to help inform a decision, well, then you still have the a human in the loop or a human component to it. So I don't know if that's a direct answer, but that's how my brain thinks about it is all of these things that we're building is moving information. And so much of what we do, especially in knowledge work, but in in all organizations is just, I need to get this information from here to here. Sometimes it's system to system, sometimes it's brain to brain, and those are starting to maybe blur together a little bit now. I love it. I... Yeah. As I wanna continue this conversation, I am looking at our time, and we would love to. start kicking off the showcase. So, thank you all for sharing your insights, and we do have a q and a at the end. So if you do have questions, you can leave that in the chat. But with that being said, I think we can start diving in. And our first builder that we are going to pass the mic to is Chris. And so how this will run is, every builder will share what they've built and, you'll hear the story. So, again, feel free to use the chat or the q and a if you do have questions that come up. So, Chris, I'm gonna pass it to you. Thank you. So today, I'm gonna show you how I, turned a monthly financial update that was a lot of manual work, a lot of manual processes into an overview of the financial health of our organization. So every month, I was sending a Slack update, on our finances. And doing that meant gathering information from a lot of different platforms. So there were Salesforce and Rippling or bank accounts, spreadsheets, etcetera. It was a lot of work, and then you have to standardize that and then put it in a spreadsheet, make calculation, and then finally verify everything, and then write the update. And that took about two hours a month, if not more. And so that was a lot of a lot of work. And so the result of that was that very long, Slack message, right, that was all written. No visual. No nothing. And then once it was done, well, the following month, I had to rinse and repeat. Right? Do it all over again. And so, of course, here, there was a lot of opportunities for growth and improvement, especially in the repetition, you know, that was coming from that process. And we can we can move on to the next, slide. So I have a question for all of you. If you, hear my pain, in one word, what is the hardest part of getting your monthly numbers ready? Like, if you're like me, like I said, the whole gathering, standardizing is a whole pain in itself. But, like, I would love to hear from you. So we also put the question in a in a word... In the word cloud tab like mentioned in the chat. So, yeah, please answer your question, or sorry, answer, answer Chris's question in the word cloud tab so we can see what folks are saying. And I'm not sure if I... Can I see it, Vanessa? Or Yeah. In the... Do you see the tab on yes. the right? Is it appearing, yeah. for folks? Yep. It's coming. It's coming. It's coming. Okay. So feel free to I see verification. Yes. Multiple data source. I feel your pain. Yeah. Data is everywhere. Reconciling is very hard. Timeliness, reconciliation. So... Yeah. I mean, I have... All of those all of those issues are part of that process that I'm talking about. So, from that, I think that what I created was a solution in three parts. One was a dashboard, a financial dashboard that would bring all of the information in one visual view. Then there was a second piece that was an AI skill that would turn that data into PDF report, and then a second AI skill that will then, take all of that information, write an executive summary, and, start an email draft from it. And so I started with a dashboard, and my prompt was very simple. As you can see, it was very, you know, plain language. I asked for some financial data, for some comparison charts, and that's, of course, the first prompt. Right? Then I kept iterating on it, asking for exactly what I wanted. I told it what information mattered to us as an organization and what didn't. And then I gave it also a brand guide. Right? We wanted to keep a visual identity, that was coherent with our organization. And so if you see the dashboard, you can see it's one big dashboard with four, headline KPIs and then some charts that give the story of our financials, right, for the org. And it's a great visual for the exec team. And so it's obviously much better than a long Slack message that is written, and it's accessible, you know, at any point. So they can go on Rippling, look at the dashboard, see the numbers. It's fully live. Once that was ready and I was happy with it, then I turned to the second piece, which was I still need to do a monthly report, right, because, potentially, people are not gonna go every day and check. So I need that monthly check-in. And I created a AI skill that, as you can see here, that will take that data, so same source data, and turn it into a three pages PDF. And so if you can see, it has our brand guide as well. It has a template that I created. This is how I want to see the information. And then, I told it again what was important to us, what wasn't, and very clear instructions. Once it was able to do that, create a perfect three pages PDF, then I turned to the second AI skill, and that one kind of triggers the first one. So it triggers that report, creates it, makes the creation of it, and then it will, using that same source data again, write an executive summary and put it all into an email. So attach the report, write the summary. And as you can see, the summary has very specific information. And I told it, like, this is what is important. This is... For example, if, budget variance is more than 10%, if our cash runway is, you know, below target, those are the things that are important to us. So please flag those. And so it will do so. Also, just a note, all the information you see is dummy data. Right? It's not it's not the organization's. data. But, now I had this whole workflow that was creating and gathering the information for me, making all the calculations. And as you can see, it is a draft email. I'm not making it send it for me, and that's where I think the human judgment comes into place. I then have it in my inbox, and I can review it. I can potentially put some color to it, right, interpret the data a bit more, and then send it to the exec team. So that, I think, is the important part. And this is the the three pronged approach that I took. And to me, the impact of that is, of course, the time saved. Right? From two hours, now, it's taking about five minutes maybe. And so it's a lot of time saved. But more importantly is the improvement on the deliverables. So before, it was as long written Slack message. Now we have visual storytelling. We have live data. We have one source of truth, right, that is pulled from different places but in one, visual dashboard, and that I think is very important. And then at the end of the day, I think that, for me, the value is that I no longer spend my time gathering data, trying to calculate everything, putting all... Putting it all together, but instead, I have more time to interpret interpret it, which I think is the most important part as, you know, as humans, is that judgment, that interpretation. And that's pretty much my my use case for you here. Amazing. That was awesome. Super super cool. That was awesome, Chris. thank. you so much. I had my, like, reflex... My webinar attendee reflex trigger there for a minute when you had the skill on the screen. I was like, I need to screenshot this, and then I was... Wait. I I don't think I have to do that. I I know Chris, but still, it kicked in for me. That's that's so cool. Thank. you so much. Yeah. It is super cool. And that's a fun thing, I think, about the big... The builder community or something, like, us being able to share these and hopefully be able to iterate and grow, like, expand on them. I think that's gonna be one of the really cool things about collective intelligence across the entire community, like, being able to continue to grow these, at least, frameworks that all of us can adopt. Agreed. 100%. Brendan, don't worry. We... You don't have to screenshot Chris's skill. You can actually copy it directly in the builder's gallery. So we have actually uploaded all of our use cases there, and they're public facing. So, for folks in the audience too, don't worry. We will share, so that you can... Yeah. Like Leif was saying, it's really a collective intelligence here, exchanging ideas from each other and testing it out in your own environments. But thank you so much, Chris. That was awesome. Thank, you. yeah. Okay. With that being said, let's move on. So, Brendon, you are up. That's me. Yeah, I... We found ourselves earlier this year in, a really enviable position, which is we were going to be sending out, bonuses to a huge part of our team. In fact, I resented even saying problem like this. This is not a problem. This is a great, great issue to be working through is, you know, how are we gonna get information out to our team members to let them know, you know, how much and, we're gonna be paying them as part of this bonus process that we had kicked off. And so we were really excited to do that, but it it definitely raised some questions because, the way that this process was working out, they were personalized in individual amounts for every single person. And not just from an amount standpoint, but also from a structure standpoint. And there are a lot of different reasons for that that we won't go into here, Just focus on the workflow. But, you know, some were structured over time and some were lump sum, and there are all these different things that we needed to account for. And, we wanted a way to do that easily and quickly. Now this is not the first time that we'd run into this. Again, fortunately, this was the second time that we were gonna be going through a process like this. And in the past, we had done this much more manually. So we had created these letters and signed these letters, and then we figured out, like, oh, we could maybe write some some JavaScript in Google to try and automate the emails. But you go through all the setup to write the code, and then it ships these emails, but you get no observability. And you don't know if it works, and you don't know if the right number went to the right person. And you're just like, I hope so because I really worked hard on this. Boy, would it be a disaster, if the wrong stuff went to the wrong people. So, you know, we were thinking back about how we had approached that in the past and how much time it took to prep all of this. And then I'm thinking, I gotta send out, like, just under 700 of these things. What are we what are we gonna do? So, you know, again, found ourselves in a really enviable position. Really fortunate to be working through this, but, you know, curious for the group. We all we all have kinda questions for the audience. I'm curious how long you would allocate. You know, you think about going through this process and maybe delegating it to your team, or maybe you're doing it yourself. Like, how much time would you put aside, to prepping and sending these 700 letters? Yeah. Happy tears, though, Ava. Right? Like, you... I'd cry first, but this is this is not a not a bad thing. It's it's a... It's an amazing problem to have, but... Champagne problem, I guess. Campaign problems. Yeah. My lobster is too buttery. I'm gonna go over to the word cloud here. I wanna see the numbers start to to roll in, see results. Forty hour... I would die as a response. I think that that's a valid a valid answer. Yeah. It's, it is a nightmare. It is a lot of days and a lot of time. So, yeah, let's dive in here. I'll come back to the the stage here and and see the slides. But, you know, we thought there must be a better way. And so first, where are we gonna store the data? And, who? Jumping back and forth. Sorry. I... That was by. accident. Which... Next slide. Yeah. Go for it. I'm ready to roll. Awesome. So, you know, we we used Rippling to generate, triage, send, notify all of this as just a single workflow and and single step. And it saved a a boatload of time. So I was thinking through this, and I was like, okay. If I get really efficient at this doing it manually, maybe I prep some templates and I can merge things in, and maybe I can be really generous and give myself, like, one to two minutes per letter, which I think is crazy fast. But that was where I started with the math, and I was like, that's gonna be ten, twelve, fifteen hours. And And if we get more realistic and say, even if I am really fast at computing, over time, exhaustion and fatigue sets in, and now you're looking at maybe it's forty hours or eighty hours as a lot of people said. So we kind of prompted Rippling AI and built within Rippling to do this. And so the first thing we did was create custom profile fields to store the data. So we had a spreadsheet where depending on how these things were scheduled and the total amounts and the... You know, for anyone that had a a scheduled payment, you know, what is the amount per year, and we loaded all that data in. That just went spreadsheet to profile fields. That was was super quick and easy. We then created a document per structure. And so there were four different structures that we were able to determine this narrowed down to and and created a unique document within the documents module in rippling. And then we built a workflow that automatically routed, distributed the right letter, created observability with, with Slack, which is our primary communication tool, had delays built in just in case we found something in the, the debugging process, but ultimately created, signed, and sent the individualized letters to each person. Now I went on a little bit of an exploration journey with this, so I will be honest and say that I spent probably forty to forty five minutes, exploring through the prompt and then crafting all of this. You know, if I were to have to do this again, I think it would take me five to ten minutes. But even so, let's say we we round up and call it an hour, and save myself anywhere from forty to a hundred hours based on, what the word cloud looked like there. So this was a huge win. I think on the next slide, we've got a little bit of a look of how this worked where, we're able to check based on what fields were filled, what schedule people were part of. Is it a one year or a two year or three year or five year payment schedule? And then send a debug message to Slack that captured all of their profile fields, validated the information was correct, and dropped it into a private channel that I'd set up. Put a delay on that so that we could audit it as it was running just in case something was wrong with our data. I could feel comfortable, that the information going out in the letter was accurate and then just directly ship the document. And so they get an email with, with all of the information in the email body. They get an attachment of that document. That document was signed on our company's letterhead. And then not only did they receive this information about this bonus, but it's also stored in their profile going forward, and and all of it through just one workflow. So, really excited, for how that went. Obviously, the impact was massive. I mean, champagne problems. Oh, no. We got a wave of employee gratitude and buzz and excitement around the company and people reaching out and going, this is incredible. This is amazing. You know, we have an incredible leadership team who who leads with their heart and and wants to distribute as much as they can to the team. So it's a really exciting scenario to be in, but definitely created a need for some ingenuity, and I need to save, many, many, many hours of admin work through this process. That's it. I love this, and I'm taking parts of what you did, for for my company because it was very impressive. And also, Yeah. like, such a good use case to be able to think about in other scenarios too, Brendon. Like, that's really cool, like, how that could be leveraged across so many different scenarios. Yeah. I love to see that logic. and see how, like... I'm I'm starting to think, oh, I could apply it to this. I could apply it to that. Like, yeah, it's Yeah. awesome. Getting, I think getting like this is what I was thinking about with the data piece, right? Like as soon as you you you start to understand what you're trying to move around, you can start to automate some of those things. And, I I try to think across modules too. I try to think not just like, okay, how can I send a document, and and assume that all the information has to be within the documents? Okay. How can I connect the profile module to the document module to the workflow module? Because at least from a rippling standpoint, it is all connected behind the scenes. So I I figured out to think holistically in that way, and it it really helps. Yeah. Super cool. Nice work. Yeah. Thank you. Thank you, And. nice that that results here some here, I thought I had the boring one. Right? not at all. That's awesome. at all. And I love how you guys are thinking about applying, like, the framework in different problems. With... Lake, did you have one in mind already? Or Chris? Well, immediate... Immediately, I was thinking... But the the... I I immediately have ideas, but then I catch myself. I'm like, wait. There's automated, like, offer letter routing that you can do. But then I was thinking, is there a way to combine this with the workflow to maybe be able to have one singular workflow that maps out every single different offer letter to be able to trigger it when we want to or or kind of a pack, like a packet across different scenarios. But then I'd have to go back in and think about all the different rules you can set related to offer letters. But. there's just all these different tools that we can manipulate to be able to save ourselves time. Yeah. Yeah. That's what I was immediately just kind of mapping out in my head. I don't know what others were playing with. Well, unless ideas. Let's move on to Karen's showcase. So I'm gonna pass the mic to Karen. Sounds good. So I'm gonna be talking a bit about everyone's most favorite topic, performance reviews. But jokes aside, it's more so about the data, and what you do with the information that's gathered from performance reviews. So, looking at, you know, as we've grown and the sheer number of reviews that come in, and then if you start adding in three sixty reviews, so from multiple facets, what do you do with the data to act on it so that it's not just a, yep, we did reviews and it's a tick the box type exercise, and it's actually adding value in doing what reviews are supposed to do in terms of helping the the business grow and identify risks and, in addressing concerns. So, next slide. So before Rippling AI, I was spending a lot of time, exporting the data into spreadsheets, trying to manipulate it, working within Rippling reporting, which was great with with the general dashboards that I could build with reports, but it still had some limitations of having to analyze the data and manually flag any talent risks. So I would love to pass it over to, to you all and hear what does your team actually do with the performance data after reviews have wrapped up? Instead of the word cloud, we're gonna do it in the chat. So feel free to drop in the chat your answer to Karen's question. Hold on. So I'm seeing to do something with this data? That's. Exactly. It kinda feels like a trick question. Right? Yeah. I see shelve it, pay bonuses, nothing. I'm seeing a couple nothing. So, yes, these are all things that I... Exactly the types of things that I was thinking, forgetting about it, or it would be very reactive, or it'd be something that we'd reference back to if we did have some sort of performance concern. We're like, oh, wait. Did we know about this? And then we did go back and look and see if it... You know, we could have caught something. So I thought, well, why don't we flip that and how can we be proactive? How can we have AI help us flag items? So what I started to do was, I wanted to have a live dynamic dashboard while reviews were going on and this information was coming in of how could we look at look at the information and then also a holistic view once everything has wrapped up. So what I started with was a very basic prompt, of, you know, how... Build me a leadership ready performance analytics dashboard review cycle. Right? It sounds great. It spit out something really basic like the distributive ratings. It looked a little wonky. So I was like, okay. What do I actually wanna see? I wanna be able to look at overall performance and potential and retention risk based off of, you know, the information that we're gathering. So there's some prework of how you structure your reviews and the types of questions and rated questions that you are already collecting. And I wanted to see them in talent quadrants. I wanted to be able to have the overall company view and then easily filter depending on the type of conversation I was having with a direct manager or department head or looking at it from a rating or tenure perspective. Right? So there's different iterations you can look at the data. And then I thought, okay. Well, that's great that it's showing it in a clean way, but how can I have it surface the trends and the issues and the concerns that me and my team were already booking and trying to spot? Can it just set those alarm bells off for us? So I gave it specific prompts of items to scour the the information we had, not just in the reviews, but also externally. So, it... Was there a manager change or a role change that may have prompted some of these alerts going off? So I'll show you, kind of a version of the dashboard. It is sample data, not exactly what the dashboard looks like on the next slide. And so this will be happening and populating real time. So when the review cycle kicks off, all of this will be zero, and then you'll start to see as the information is submitted and reviews are completed, in real time, we could see if something is popping up in one of the red quadrants. Is that a surprise? Is that something that we need to talk with the manager right away of, hey. I thought this person was an exceptional performer at the end of year. Why are they needs improvement now? And we weren't flagged. Rather than having to wait for everything to be submitted, conversations had, and then kind of doing damage control, so to speak, at the end of the review cycle, or it's just forgotten. Or maybe there's a flight risk of someone not feeling valued and not feeling great about what's going on in the role, but they're in a critical role. We can have early intervention conversations and address it in the moment. So then going to the next stage, if you, for each of these quadrants, this is a view of, like, you can drill down into each of those quadrants rather than just seeing, oh, there's 40 people in this specific quadrant. Well, who's in that? Does it make sense that they're there? Also different views not outside of the standard overall distribution, but maybe the talent quadrant distribution. Right? You can start to think about how you wanna view that data to flag the specific information you're looking for. And then the next view, which is the really exciting part for me that I got kind of nerdy about and and started geeking out about is I could pull the historical data. So this is for our longer tenured folks looking at the past three review cycles, and it will... This report will flag if there's been a rating drop during that time, and then we'll also flag I won't have to go and hunt for the information if there was that role or manager change that may have influenced that rating change. If there was nothing that we have captured that would indicate why there's a reasonable rating change, then that's a flag for my team to go in and have a conversation. Similarly, for new hires, we also have forty five to ninety day reviews. And then... So this would be their first review cycle. So it's taking that historical data of how did they ramp up, how did they onboard. If the manager was indicating everything was smooth sailing, but then the first review, they're not doing so great, Why is that? Again, it's that additional human touch kind of as we were speaking to, before of this is great to flag, but now we're spending the time to have the important conversations, and it's happening again. I can't stress it enough of real time. It's not two months later when the business has already moved on because we've had a chance to pull the data together and and and synthesize it. And so with that, on the next screen... So, I'll be real kinda similar to what's been said of, you know, if I were to iterate it now, it would take way less time. I probably spent about a day building the actual dashboard, and I'm being generous saying, like, it used to take me a week. It was probably more real... Realistically, like, a month of pulling all of the data together, really taking a look at it team by team. And as you scale, it just becomes even more cumbersome. But what's really cool is now the dashboard's built. So I can just prompt it to pull in the most up to date data. And, yeah, we're able to have stronger manager conversations. We're able to say, here, this is what the data is showing. Let's talk about it, and what can we do to help. So that's the overall build. Powerful. Amazing. Yeah. Super cool, Karen. Oops. Yes. Lots of lots of comments going on over in the chat, but that's awesome. And I think the thing that's so exciting is with the dashboard, then we can just keep iterating on it. Right? Or be able to keep building on that, but also empower if there's HR VPs or whomever across the team that might be able to meet with, their business leaders Exactly. and then walk through walk through the story. So people... Like, with visuals, we're able to actually, like, capture the story instead of people looking at a spreadsheet and being like, screw this. I'm not gonna take... Nobody's gonna take time looking at a spreadsheet because it's boring, but when we can actually visualize it, it's so much more powerful. That's awesome. Yeah. And I've even thought, the next iteration of, you know, encouraging managers, we use one on ones. We're working on building a a performance tracker within the custom apps. So all of that information, it could be like, okay. This person had a score drop in there on a PIP or there's something that conversation that's been happening in their one on ones. Right? It should be able to start signaling from that data as well. Yeah. That's Thank. Gonna so much, taking. that one. Yeah. It was... I love seeing, like, how many people in the chat said that they did nothing with. their performance. That was really, like, insane to me to see how many people weren't taking action. And so I think, like, you're solving a genuine... Like, a really interesting and tricky problem. So, yeah, thank you for sharing. Of course. Okay. So we have our last showcase. Leif, we're running a little bit tight on time, but I'm gonna pass it to you. can test... I will move fast because I think q and a is the most exciting part. Okay. And let me know when you want me to press your your your video. Let's just... Actually, you know what? Let's just... I told everybody I'm an early adopter, and I wanted to play with motion, if anybody hasn't played with motion in cloud yet. But, let's jump to it, Vanessa. Okay. So I'm gonna I'm gonna play the video, and and, yeah, we'll be back right after. So just? having a little fun. Dude, that was so easy as well. Like, thank you, Claude. Thank you, Motion. But, I'll be really fast here because I really do think the most exciting part of these discussions is the q and a, the brainstorm. So here's, my question for everybody if we can follow-up in the chat is fragmented data, like scattered data, but can we trust it? Do you trust your data integrity? That's my question to everybody. It's a yes or no in the chat. Like, do you trust your data integrity? Do you think your dashboards are accurate if we were audited? Do you think your reports are accurate if they were if they were audited? See nopes. Yes. No. Yes. Mixes. I like the better. I don't want to answer. That one. that one speaks to me. As a neuro major, this would help a lot with our ace coming. The data is always fluid. Yeah. Yeah. 100%. Yeah. I think what this exposed and, what we're playing with... And I... Hopefully, everybody saw that in the video. Like, building is the active. Like, that is... We are building. This is new. This is new for us and our team. But it's so interesting that all of us are being forced to become kind of a... To wear another hat of data management, data governance. Right? And figuring out how we do that with more and more connectors, more, plugins coming and us pulling in data from so many different places. I mean, Chris's example was perfect talking about this as well. How do we make sure we're creating a a a standardized rule book to guide us on that? So, this is one of the things we we learned. Like, rules lived in a document. They were not in the system. They were not in Rippling. So we were just stumbling across errors later downstream. Right? Like, maybe we'd be hiring somebody or off boarding somebody or something. We found this, anomaly between job levels or sublevels or between... You name it. I mean, so many different, object fields across across the ecosystem. So, really, what it was identifying is that there's really no feedback loop to catch this as well. So that's where instead of doing random prompts, we we built a governance or this is the idea, and the one we wanna brainstorm across the rippling community is building a governance system that helps us catch the bad data before it becomes real, before we're... While we are entering it into the system. But also, well, how can we measure existing debt? Right? In a sense, this is kind of like tech debt on our side, on the people ops side of, well, what's in there and what do we need to clean up now? Like, what do we need to catch up on as far as creating a good standardization rule book? And I know a lot of people maybe have external, like, Excel sheets. I mean, entire workbooks about... Think of it like a marketing style guide. Right? In a sense, it's kind of the same thing, like, what's our data governance kit? So there were random prompts we used to ask about, various questions. I mean, you name it. I'm sure everybody here could imagine tons of questions. But, like, how many active workers are missing a level? Are they missing a assigned department or manager? Or are there discrepancies across what departments that title should be assigned to? Right? So these are some of the sample prompts that we were asking. And then, well, how do we standardize those? So how can we ensure if everybody's asking the same question that it's actually has guardrails, that it's following the same rules, or it's calling on the same tool or the plug in. Right? So built out two, prompts that guide us on it. So a gate, basically, that we can pass things through when we are hiring somebody. And this is even... This is where the collective intelligence is going to get really fun. That's that's the accelerant. So how can we create a gate that helps us make sure our architecture is clean, and that we're doing a good job managing our data? And then a sweep that feeds into a dashboard. So we can go to the next slide, and this is a snapshot of, just the v one of a dashboard in uncovering the debt that we have. Like, what we need to clean up, what we need to, bring into the system or connect. Right? Like, we're not able to build, sublevels, so then our job subleveling exists externally. But how do we make sure all of this information is packaged together, is working together to make sure that we are managing our data and keeping it clean? So this is just one of the ideas. And moving on from the moving on from the dashboard, this is also v one of our workflow of a pre offer. So where a gate... Where this would flow down into running these prompts, being able to communicate with the internal talent acquisition team saying, hey. We caught something. Like in the video where, like, hey. There was a title anomaly there. Like, we used a number instead of a Roman numeral for maybe a sales development representative two. But finding simple catches like that that aren't so simple, but making sure we're keeping our data clean and we have everything else downstream is clean. So being able to create these learning loops. So here's what we found. Lots of debt. We have an opportunity. But this is what's so cool is with AI, we can do things that previously, how long would this take? I mean, how how large of a team would it take as well? And maybe we'd have to work with data eng. Maybe we'd have to bring in a data scientist and, like, bring in tons of different team members where now, like, people ops teams are empowered to tackle items like this, but also create the tools that help us become data managers to to install a data governance policy over all of our platform. So that's the really exciting part. That's the vision here, and the piece that we wanna be able to build with the community. I think, let's see. Do I have another slide, Vanessa? I'm trying to go fast, so we have time for q and a. I think that might be... I think that was it. I think. that was all was slides. it. That was it. Hopefully, I didn't fast forward too quickly, but I just wanna make sure we have time for q and a because, really, this is the most exciting part. But, hopefully, everybody gets the vision there as well where we can build on this and continue to increase the pace of that flywheel together as a building community. Amazing. Thank you, Leif. Absolutely. It's fun. I love it. I wanna implement it now. I wanna I wanna brainstorm on it because it has a long ways to go. And then when you plug it in with maybe a departmental or company brain, like, when you start bringing everything together, though, that's where the real accelerant is. Right? But... Yeah. Super super geeked to continue building together. I wanna move us quickly into a, a live q and a. Thank you again to everyone for presenting. Thank you, Leif, Chris, Karen, Brendan. We are coming close to time, so wanna give, like, a few minutes. So one question we got from Carly or Chris was, what was the feedback from end users going from Slack message to the new summaries? So we just started we just started implementing, this process. So so far, it's been great. I mean, it's much clearer. Right? The... Again, the quality of the information, like, Liv said at some point, a visual is much better than, like, a a long, you know, text. So that's been the the biggest benefit and and, what is really... What people really, like about it. And also the fact that it's live. So if our CEO tomorrow wants to go check the data, they can. They don't have to wait for that monthly update. Right? So it's also much, easier to get to that information. So it's been pretty positive. And, of course, I'm gonna keep iterating on it so it will get better and better. But at least, so far, initially, it's been, really good. Amazing. And, Karen, one quick question for you from Sarah was, are you able to capture the qualitative HRBP feedback in the dashboard coming out of that one on one check-in with the high risk employee? And then quick for the audience... Sorry. Quickly for the audience, stay tuned, and we still will do a live voting for, our AI winner. So, stay tuned for that. But, Karen, passing it to you. Yeah. It's a good question and that is the next iteration. So, similar to to everyone else, these have been active very recent live builds. So that is the the next, iteration that I wanna build into it. And so it's building the behavior of adding one on ones, and utilizing that in rippling, which, is an uphill battle for different reasons. But at least for, my team, yes, we're actively starting to collect that information through rippling one on ones to then be able to pull forward into the dashboard. Amazing. Can I ask a question? Let... Maybe we save it. for the end? I just have to do. a few other things we don't mention before, this session ends. We have four minutes. I know there's been such good content throughout this whole thing. I wanna keep talking. But, really quick for the audience, if you don't know, I wanna just quickly mention who we are as Rippling. So, Rippling, we are the... We are a connected source of truth. We are a platform empowering HR, IT, and finance leaders. And, really, what makes Rippling AI different and what you've been able to see today is just the fact that everything in Rippling is connected from all of your HR, IT, or finance systems. So your data is living in one place. And when you add AI on top of that, it's what empowers builders and what empowers you to create solutions, and create dashboards, skills, workflows. Everything you saw today is possible because of the way that our system and platform is built on top of the employee graph. So I wanna make that quick plug in case you are interested in learning about Rippling. If you want to, book a demo to learn more about Rippling AI, There is a poll going out, there. And if you wanna learn more about different use cases, you can also check out the AI builders gallery. We have all of our builders, use cases that live on the site there. And so you can explore it to, get inspiration, to copy and paste different types of use cases and test them out in your own environment. And, lastly, we have a builders program. So if you are interested in becoming an AI builder similar to our builders today, we also have a poll for that so you can share whether you are interested, in being... In joining the program. And we have three minutes left for our live voting. What happened was we asked folks in the audience to share a build, and it doesn't have to be made with Rippling AI, but, any AI build. And we wanted to, see what folks are doing. And so these are our three runner ups. And, you know, there's a bit of information on the screen there, but we want... What we wanted to do is select our winner for, the gift card here. So I wanna give folks a minute to read the screen and see which person they think, is worthy of winning this fun award. We have Mario, Maria, and Jeffrey. So I'll give a minute for folks, and And we can vote on this... On the side. These are fascinating builds. I remember, like, even just a few years ago, you know, build a Python script to do this thing. That's how you automate your life. Like, that was the the. conventional, I feel like, wisdom for non engineers, non developers. It was like, learn some Python. Right? And now that's all just so accessible and so within reach. So I. I find that one really, really interesting. So I think I think people are answering maybe in chat with some of their, votes, but there's a poll tab. I don't know if I can see what they see, but there's a poll tab that they should be able to click and click the the... Their selected winner. Yep. So, folks, could you... In the audience, you can put it in the in the poll chat. Do you see there? And we're gonna close the poll in thirty seconds. So put in your win... Your your vote and... Not not in the chat, in in the poll. Thank you. I love that in... Drumroll. I'm in the... I'm like, I, am, not. part of that. Hold on. We're getting voted. on. Yeah. So wait a minute. Okay. I will So I I think I think we can close the poll now. Thank you, rippling team in the back. Okay. So the winner for that will be announced. We will we will share that in a second. I'm not sure where I'm seeing the results. Do Oh, okay. Let's see. I got it. you wanna drum roll? Drum roll, Drum. roll really quick. Alright. It's on screen already. Okay. So Congratulations. congratulations. So stay tuned for, getting that announcement. We will email you for next steps, the team in the back. So, yes, thank you all for for going through that with me and the team. And, yeah, that was the quick run through we wanted to give. I know that we are now at time, but, life... Circling back to your question, if you still wanna ask it in the remaining minutes we have. But with that being said, I also wanna thank the audience for taking the time to join us for today's showcase and, of course, to our amazing customers and builders. Yeah. It was just a brainstorm with Karen. I was thinking about iterating on stuff, but this... There's tons of stuff for everybody what was take brainstorm? offline. Just like like if you do pulse checks or any pulse surveys, like, how we can measure improvement or the impact of having this tool and then measure it moving forward. Like, are we improving one on ones? Is our performance reviews improving employee satisfaction and performance and engagement? And, like, I'm just trying to think of all of the... Like, all of it. Oh, Aleif, So I was just... there with you. We should chat on the side. Yeah. Super cool. Yeah. The building never ends. There's another... No. There's gotta be another season. Let's go. Any other cool. final final questions or things from the audience or folks? See lots of positivity, in the in the chat. So, you know, grateful to to feel like what we're sharing is useful for people. I think sometimes we all, not just in this call, but everyone watching, like, we all get into our own heads about what is and what isn't helpful for others and, you know, don't... Nothing that you do is too simple or too complicated. I think if we just get into the habit of sharing with each other and sharing what we're building, all... That that sea, that rising tide will lift all boats and and we can all, have a better work life and, be more. impactful. So Just try. Right? Just try. try. Yeah. Yep. Karen, there. was somebody asking if you use Rippling's performance management. I do. Yep. Yes. Oh, we gotta count down timer. Yep. 12, 11. Twelve seconds. Who's gonna. get the last, word? thank you, everyone. We are officially wrapping it up, and we appreciate you all for taking the time to watch. And thank you again to our builders. Thank Thank next. time. Thanks. You guys are awesome. Oh, we didn't get booted off right away, you. but I'm worried we can leave the stage now.