Name: EU Data, Global Impact: Achieving ROI with AI-Native Contract Intelligence
Uploaded: 2026-02-17T10:16:57.434Z
Duration: 1 h 48 s
Description: EU Data, Global Impact: Achieving ROI with AI-Native Contract Intelligence

Transcript for "EU Data, Global Impact: Achieving ROI with AI-Native Contract Intelligence": Hello. Thank you so much for joining us today for EU Data Global Impact, achieving ROI with AI native contract intelligence. My name is Hal Marcus. I'm coming to you from the Workday Brussels office. So glad you could join us today. Let me do a little bit of housekeeping to start us off. Firstly, we are recording today's webinar, and this will be made available to you later. So if there are others in your organization you'd like to share it with, we'll make that available to you to do so. Let me go back one. We have there's a q and a box for questions and answers. We encourage you to ask questions as we go along. We'll answer them as we're able as we go or at the time that we'll save at the end. So please don't hesitate. And then finally, a product statement. We will be talking about some upcoming developments in our platform. We're a public company, so we need to give you this product statement upfront about the things we'll be talking about today. And with that, let me introduce myself and my two colleagues that will be presenting to you today. Anya, Lauren, if you could come join me up here. Firstly, my name is Hal Marcus. I lead product marketing for at Workday. Evisort's a contract intelligence and contract life cycle management solution that was acquired by Workday about a year and a half ago. And I'm happy to say one of the key reasons we were acquired about a year and a half ago is Anya Lyons, a woman who has joined me today, Senior VP and Deputy General Counsel for Workday. Anya, thanks for coming today. K. Thanks, everybody. Lovely to see you all, and I look forward to talking to you about our customer zero experience. We'll be bringing Anja up in just a little bit after I do some introductory content so that you can learn about her experience using our platform within the Workday legal team. And we're also joined today by Lauren Guides, principal solution consultant who's been with Eversort for some time. Hi, Lauren. Good to see you. Hi. Thanks for having me. Alright. Thanks to both of you for being here. I'm gonna run through some introductory content just to get everyone who's attending today. We're very gratified that you've all come to join us today. And this is a great opportunity for us to introduce you to the technology that has been primarily focused historically in The United States and North America and less so in the European Union and in England. And we are changing that quite a bit. We've been growing our local presence, our local data hosting, and our regional language capabilities quite a bit within the platform. So I'm very happy to be with you here from, the European Union's, capital here to, be sharing with you what we're doing in this space what some of the possibilities are. And just by way of introduction, I'm a California attorney. I originally practiced in New York and then in California. I'm a former general counsel myself for a software company. I've been in the legal technology space now for many years, and I have been happy to shepherd a lot of really powerful technology into the legal operations and legal practice space. And some years ago I started focusing on AI for legal use cases. In recent years, a top area of focus for that has been in managing and understanding what's in all the contracts across an organization. So with that in mind, let me introduce you to what it is that Evisort began with with our first line of code back in 2016 as a contract AI solution, it really evolved from the ethos that contracts aren't just documents, they're data. And why that's significant is contract life cycle management had historically focused on how do we get contracts through to the signature stage, how do we get them drafted, managed up into the point where they are signed, perhaps put them into a repository. But at that point, there's largely a manual effort to really understand what was in all those agreements, what was the meaning of them, what are the terms that matter so that you could make decisions. Now putting that another way, every department in any organization has valuable data within their contracts that most of the time they don't really know how to get to, whether that's the office of the CFO, the office of the CHRO, or the office of the CIO. Really any part of the organization has contracts that matter to them with data points that they have to usually go through legal to get answers to. And legal teams struggle to keep up with those requests and to find the information they need. And they have to turn off into outside counsel, go through a lot of time and cost to manually derive the information that they need. So the genesis of Evisort was to make that much easier to get to. Effectively there were three things that Evisort introduced. The first is we would connect to your contract repositories wherever they are with the contracts in just about any format that they're in and bring all that data together into one place where we could really analyze what was in those contracts by applying pre trained AI at scale that could accurately derive critical data points across those contracts. And then we empower the user with search capabilities, with reports, with dashboards, with all sorts of capabilities to know what's in all of those contracts. That was how the company began. And then over time, it developed the capabilities of traditional CLMs, which included the ability to create workflows for your contracts on a pre signature basis to get them requested, drafted, negotiated, edited, signed, and then eventually stored. By bringing all these capabilities together in an AI native way, where it was AI from the first line of code, not as a a later add on, we were able to really supercharge what it is that organizations do with their contracts. Now we sell the product in two ways. The first is what we call contract intelligence, which includes those first two capabilities for all of your post signature contracts. But we primarily sell the product as CLM, Workday CLM now, with all of these capabilities, including the full presignature end to end workflow capabilities. Whichever way you buy the platform, whether you're just interested in the post signature capabilities or the entire CLM platform, you have agentic AI capabilities in the platform. And in fact, we call these two agents rather than as we're seeing these days where people like to say we have many, many agents and you can create all of your own agents. We do have all those flexible capabilities, but we try to keep this simple and refer to them as two agents. The first is the contract intelligence agent, which gives you everything that you need to analyze those post signature agreements, and the contract negotiation agent, which gives you everything you need for the presignature agreements. Looking a little more specifically at that, here's what we provide in the Contract Intelligence Agent, a conversational experience so that you can ask any questions of your contracts, all of them at once, one contract at a time, or any group of those contracts. You can filter down by certain fields and then you can ask questions of those agreements. So it's very flexible, very capable, and there's quite a lot that it can do. It can calculate dates and amounts that don't even appear in the contract. It can summarize key terms. It can classify terms into ranks or ratings, which can be a very effective way to look at that data at scale. And we then take it one step further and say, if there's a question that you're asking for contracts as you go that you think would be valuable to save as a regular question, as a question you ask across all relevant contracts, you can do that as well. We call that custom AI. This is the ability for you to create any new model that you would like to answer any question that you can raise. So this is an example from a chief chief procurement officer of a major financial institution who brought in Eversort because he needed the ability to answer many questions but in particular how much can our vendors, our suppliers raise prices on us on an annual basis on average. And he needed to see that in categories so that he could provide that information at scale as a simple figure over to the financial officer. So this gave him the ability to do that. You can create custom AI models for anything that would be valuable for you to know. And because no software company like us could possibly know all the things you would find valuable to know about your agreements, it's more effective for us to give you that capability. Now some of those questions will yield simple numerical answers, a date, a number, or a small bit of text that's fairly consistent from contract to contract. That kind of data displays very effectively in charts and dashboards. Those charts and dashboards are available to you to have as many as you'd like. They're always current. They update very quickly. You set them up on a click and drag basis with check boxes and such, and you can have as many as you like for different departments in your organization. So it's easy to set up whichever collaborator that you would like with the data that they need about the contracts that they have access to, and only those contracts will appear in their dashboards. But some of the uses of this technology go beyond bits of text or small numbers and such or dates. They'll actually go into summaries of terms, for example, or brief explanations of how terms can appear. And by the way, everything I'm showing here can be done on a multilingual basis. This is generative AI capability, which is actually agentic in many ways in that it's continuous and autonomous and can run on a rolling basis making nuance judgment calls. So it can provide this data for you in many, many ways. When you have a summary of terms like this, that data can appear in reports and tables in a very effective way. You've now created data points that travel with the contract, and those data points can be shared into just about any other system that you would like. This is partially why, as I mentioned earlier, we sell the product in two ways, as contract intelligence or contract life cycle management. Because there are major organizations that we work with, some of which I'm happy to say are some of the largest technology and media companies that you might think of, that use us to only extract and generate these critical data points but that have other solutions in place for their presignature contract workflows that they have developed over some years. Well, you don't need to replace those systems to take advantage of what we bring. You can actually be using contract intelligence to augment those systems with all these data points. Now how is this used? Some of these organizations, and these are all examples from our existing customers, will do things like understanding across all their contracts where they have the ability to charge for partial shipments. So if there's a supply chain issue, they have the ability to keep their cash flow growing. Another would be to keep abreast of changing data privacy laws and all the many, many contracts that need to be updated and have the right language in them in order to make sure that you're staying ahead of those. Finally, there's a major technology corporation that uses our custom AI to track all the different provisions that they care about for their internal corporate policies that apply to all of their suppliers. And in fact, one of those requirements is that any technology vendor now that they go forward with need that has AI, I should say, needs to be certified for the ISO 42,001 standard for responsible AI. I'm happy to say that Eversort and Workday generally are certified for ISO 42,001. That, to my knowledge, we are still the only product in the space of contract AI that is. So these are the kinds of things that our customers will track for us. But all of that having been said, we have a wonderful customer to bring on board, which is Workday itself. So I'm gonna ask Anya to come join me here on stage and talk about her experience with Evisort that led to the acquisition of our company by Workday. Anya, thanks for joining. And, Anya, I think you are on mute right now. Yes. Hi, everybody, and apologies. I I woke up with a little bit of a crackly throat this morning, but I hope you can all hear me because I'm excited to share our journey with Eversort, which started way before the acquisition. And as many legal teams, we don't wanna be known as the department of no. We wanna be forward thinkers of legal. And our mission was to really think about how we could simplify contracting for our customers to accelerate our own growth as a company. And I know that's a a mission that many of our customers share. So we were always looking for, was there innovative tech or AI tools out there that we could leverage to sort of move at the pace that the business was moving? So that's how we came to learn about Eversort and had been using them for three years and had experienced firsthand the power of the AI contract intelligence in particular, at that stage. So back in 2021, like many other legal departments, we had been struggling just managing a huge volume of contracts from vendor contracts, partner contracts, customer contracts, lease contracts, employee contracts. In any enterprise, there is a massive amount of contracts, many of which don't always sit in legal. But somehow when somebody needs to find details about those contracts, they contact the legal department. So we were grappling with this, how do we scale and how do we get a better understanding of what the risks, opportunities, and obligations are in all those contracts that we had. And the only way for us to review those at that time was to pour through each document and open up each PDF or each Word document one by one. And for anybody who's known and and had to do that kind of work, it is painfully slow and very expensive. So that was the solution that we were looking for. How do we manage that growing contract volume? How do we reduce that manual contract review? How do we accelerate due diligence of contracts for acquisitions or for large scale analysis that we needed to do to reduce costs. And ultimately, how could we have a single source of truth of a contract depository that was powered by AI, where at the touch of our sort of keyboards, we could get analysis of different contracts that we had in place. And today, Workday has over just in our customer realm, a 100,000 customer contracts and order forms, and we use Evisort every day to deliver faster contract reviews, reduce risk, and unlock, I think, the most important thing, which is hidden contract data and value that we can use in our business to be much more strategic about how we interact with our customers, our partners, our our vendors. Because I really believe that knowing what's in your contracts can give you a a real strategic advantage. And with Eversort, you know, we can run rapidly reports now across all our customer contracts to uncover things like where do we have renewal dates, what are different price holes that we might have put in place, do we have any SLA credit nonstandard conditions that we signed up to? Do we have any publicity restrictions with customers? Do we have termination rights, data center restriction rights, and and and much more that you all know in your own business? There are so many different nuances to what you agree in contracts, and then somehow they get shelved somewhere, and it's harder and harder to unlock those. Well, Eversort really helped us to do that, unlock that value that was in our contracts. And overall, you know, I know on the screen, it's, you know, a a huge ROI, 37 x what we paid for Eversort when we first licensed it. I mean, we have absolutely gotten that back over and over and over again in terms of a return on investment. But it is really the ease of use and the fact that we can move faster is also very compelling, I think, as a a use case. And it's also quite a low risk use case because many of us already have contracts within the bounds of our own companies. We already have access to them. We have permission to have access to them. So from that perspective, it was also an easy place to start as you're entering the world of of AI. So let me talk a little bit about the the use cases, three specific use cases that I wanna talk about. And the first is m and a due diligence for any companies who acquire. If you're acquiring other companies or you're doing a kind of merger acquisition work, you know that you need to go out and analyze the contracts of the target and really have a sense of what they've signed up to. That can be a hugely expensive and time consuming effort. You know, with Eversort, we we've done many acquisitions of late. And just one example is, you know, we had to analyze a thousand contracts very, very rapidly. Normally, that would have taken our outside counsel about a week to do, and the charge would have been around $50,000. But, you know, we were able to internally, with somebody on our team who who really kind of focuses on this work, and she was able to do it in in about a day. And, you know, the the speed as well as the cost saving are, I think, what make it quite powerful. The the first use case there I had talked about, which is the master service agreements. And, you know, knowing what's in those contracts, we constantly get asked by many different groups across the company, what did we sign up to? You know, do we have a if we had a cybersecurity breach, how much notification do we have to give? Are there any special conditions with particular customers that we've signed up to? And that can be a very laborious hours and hours of work. And, you know, each quarter just based on those kind of reports and requests that we get from other functions across Workday, we've saved at least forty five thousand hours quarterly. And I would say today, that's that's higher. That's almost a little bit updated because we've increased the types of use cases as well. But and and also now that people in the company understand that we can get this information, we're getting more and more requests for data around our contracts. I think another one to also think through is from a vendor lens. You know, there's there's a huge amount of contracts in the vendor landscape that you you don't necessarily your vendor groups or some people call them strategic sole sourcing, global sourcing. We've also started to really embrace working very closely with that group using Eversort to understand when our vendor contracts are coming up for renewal, what was the summary of the terms we had in place with that particular vendor, and how can we be more prepared for the negotiations ahead of the renewal times, which I think is is also, very, helpful from a business perspective to be proactive rather than reactive. And I think that's what Eversort gives you the power to do is to be more proactive in your negotiations in the future. Something that is a project that I I really, am very excited about, we're 90% there on accuracy rates we've been testing. And it is, having all of these 100,000 contracts and order forms of customers and being able to do those reports is is is a fantastic first step. But for us, the next step was to do sort of what Hal talked about custom AI. And this was we identified 54 data points that we really wanted to have on a daily automatic dynamic basis pushed through to our Salesforce instance about those customers so that you could go into any customer record in Salesforce, and these 54 key business and legal data points would be available for you almost as a dynamic constantly updated summary. And so we identified those 54 data points across all our order forms and customer contracts, and we have them dynamically pushed from Eversort into the particular customer record. Anytime that they're updated, they're dynamically updated in in Salesforce. And what that means is anybody that works across our lead to cash life cycle, anything to do with selling to a customer end to end, they have access to at their fingertips. What have we already got in place with this customer? So for example, our deal operations team continually had to open up old order forms and try and assess what was the overall discounting rate, what was the renewals we agreed, what was the termination rights, whereas now that is all there ready in that custom AI, summary that we have. And on a daily basis for those teams, not having to open up those PDFs of order forms anymore in Salesforce and just being able to see those summaries has really increased productivity, and we think at a minimum of 30% efficiency gain for all of our rev ops team, which includes deal operations, pricing, and then legal is in that life cycle too. So we benefit from being able to kinda have that summary at our our fingertips. And I think as as if you start using Eversort, I think, you know, you'll learn that there are more and more use cases. So we started with the pure you know, it was on the customer side, then partner, our SOWs, our professional services vendor has been up and running now for some time. And I think, particularly in the vendor space, many customers unlike us, they actually start with their vendor contracts and because they're very interested in they have, you know, hundreds and thousands of vendors, and they're very interested in being much more proactive with renegotiations with more vendors. And I think that's really, really positive. So overall, you know, our our procurement team working very closely with my team, they feel that they have estimated their savings over the last three years at 21,000,000, and that's in being. proactive in your negotiations and that they've had a a massive ROI and been able to, you know, process a huge volume of contracts supplier contracts through Eversorp very, very successfully. And I think it's is a very powerful tool in the vendor space to be able to save money because there's a lot of even terms in there around refunds and different monetary aspects of those contracts that you can really unlock by being much more on top of your vendors. And many of us sign a contract with the vendor, and then it kind of sits there and we're not proactively managing. And this enables your procurement teams to really do that strategic and monitoring management of of their vendors. So I think that's another use case to think about as as you think about how particularly if you're already a Workday customer, I think adding Eversort is really a no brainer because so many parts of your organization benefit from it, legal, sales, your HR departments, your facilities departments, your procurement departments. It really has that massively enterprise level impact that it can have. So overall, I think, you know, for us, we were very, very, I think, cautious in the beginning about talking about our customer zero to story because we really want to make sure that we are validating and being, you know, very upfront about it being a proven solution to real challenges that you have as customers. And but we are, you know, absolutely happy to validate our customer experience, and then that's why we went on this sort of customer zero building out some thought leadership details around our our use cases, which you can find on our website, and very much being very transparent about how we calculate our ROI. What does an ROI mean? So I think when you invest in any tool, you are it's incumbent on all of us to say, what is the return that we're driving when we're spending company money on these tools? And there's so many tools out there. I think it's very important to think what are the real use cases and what's the ROI that we can deliver from from this technology. So that's why we thought it'd be interesting to share our our story with you. Thanks so much for that, Anya. It's been a pleasure to come into an organization. I've been through acquisitions on both sides, but I've been at companies that have been acquired by larger entities several times in my career. And it's great to come into an organization where the legal team and procurement teams have already been using your technology for several years and having such great results with it, and that's why you're coming on board so that they can offer that to their customers. So that's a new experience for me. It's been wonderful partnering with you on all of this. And as Anya alluded by the way, I glossed over a slide. I'm not sure I followed you too well as I was advancing slides before. There's one about mergers and acquisitions, and I'll just call out that it was a new experience also for me that the Eversort technology was used by Workday to analyze the Evisort business and all of our contracts as part of the due diligence for acquiring Evisort. So that was a. very meta kind of experience. Anja mentioned customer zero. This is a phrase we've been using internally to reference the fact that we turn to our own legal team to test out our latest technology and to give us feedback as we're developing. And with that in mind, I'm happy to see that the legal team has begun now working with our contract negotiation agent as well, which is part of the broader CLM SKU. So to a question that came up in the q and a, yes, there are two SKUs like I mentioned earlier. One is Workday CLM, which includes all of the capabilities of Eversort pre and post signature, as opposed to Workday contract intelligence, which is just working with the post signature contracts. It does not then have all of the presignature workflow capabilities. Most of our customers go with the full Workday CLM. The reason we offer that limited option is for companies that would say, you know what? I have lots of workflows for contracts that I've developed over the years. It's a very big process to update and change that. Our answer then is you can bring in our AI to augment what you have right now, And contract intelligence is a relatively simple deployment, that can be implemented fairly quickly. So that can augment your current solutions. Now with the full Workday CLM solution, you also have contract negotiation agent where we use AI to help you draft and negotiate contracts faster than ever. And there's some new advancements on the way for this. So I wanted to highlight a few upcoming agenda capabilities, and then in just a couple of minutes, I'm gonna turn it over to Lauren who's gonna demo a lot of what we've been talking about. But first, I wanna call out that we are very soon to introduce full document AI review and redlining automatically. In other words, take an entire inbound contract, could be a 150 pages, and run it against your playbook, and the AI will automatically identify all of your risk points and suggest red lines to address all of those points. Now part of what makes that valuable is when you have a good playbook that can explain all of the things that you care about in your organization for that kind of contract. But it's it's hard to keep those playbooks current and draft them all and have the ones that meet the specific requirements of this kind of contract. So we're also introducing very soon agentic playbook creation where we can take a sample contract and any other notes or other documents you'd like and create a playbook automatically for you based on what you've given us that we can then use as the analytical base point for any new contract? And then finally, what good would those playbooks be if they become static and outdated? So we'll be giving you ongoing analytics to understand where you are and are not, you know, meeting those playbooks. If there's a particular term, for example, that you request in your playbook but 90% of the time you decide to give in on it, it's really not that important and it's holding up, you know, your negotiations by two weeks on average. Well, these are data points that would be very valuable for you to decide whether you want to update your playbooks. So this is the kind of ongoing feedback loop that we're going to be introducing. Everything that I'm showing here right now is currently planned, to our product statement, as I said earlier, but currently planned for this year. So we're very excited to be moving forward with these AgenTA capabilities. And we're very excited how because we've been working very closely with the product team on giving them our feedback because redlining is the bread and butter of legal teams and procurement teams as well. And I think playbooks are critical, and that's why this agentic playbook creation, I think, is is really a game changer for people using RCLM. So very excited about that. We figure if we can meet your team's standards, Anya, then we're in good shape for our customers. Couple of more things. In fact, this will address one of the questions that came up in the q and a, and I encourage everyone, ask all the questions that you can think of as we go, we'll address them as soon as we're able. And we'll save some time at the end. But I wanna call out that a big part of why we've become part of Workday is so that we can integrate all of this contract data into all the different parts of the Workday ecosystem for the office of the CHRO, the office of the CFO, and for CIOs and all of their needs. So one of the questions that came up was how does this interact with Workday's strategic sourcing, which already has some contracts capabilities? And the answer is we are augmenting and, in fact, offering an effective replacement moving forward for the existing contract capabilities because Eversort goes quite a bit beyond what was in that solution previously. So while the existing solution is still very much being supported, we now offer an alternative to that with the other sort SKUs, that will connect with strategic sourcing, ingest data from there to then create your contracts, and then deliver that data across into Workday procurement so that the contracts become the foundation of how you manage those relationships going forward. We are similarly integrating right now into the accounting side of the house where your revenue contracts, your customer contracts, your invoicing can be automatically populated now by key data points derived by our AI within Workday CLM. So we're finding our way into all of the different components of the organization. And you see it there with a dotted line because it's not quite there yet, but we're also focusing on integrations with human capital management for employment agreements as well. And another important development, some of you may be aware that Workday some months ago acquired a company called Sana, which is an AI company that provides a conversational experience that can go, you know, connect with all of your different data types and make actions happen. So we're excited also to be working with the Sana solution for an even broader range of capabilities. And, Anya, the legal team has already been on the forefront of that as I understand it. Yes. And and I think really powerful to think of Sona and Evisort. Sona for knowledge management and training. Evisort has a CLM and a very powerful contract intelligence. So I'm very excited about that sort of suite as something that can really help legal teams not have to go out there and buy, you know, 20 different tools to do their use cases. But if you're a customer of Workday, you already now have access to these AI powered technologies that can help you manage your end to end legal needs. So I've got just a couple of last quick points, and then I'm gonna hand it off to Lauren for a demonstration. But I just want to call out that we, as part of our desire to bring on more and more EMEA based customers, we have now introduced French, Spanish, and German user experiences into our product so that they and and more languages will be following that. You'll see a reference here that our standard AI models are becoming multilingual. Let me explain that one. Everything I've talked to you about with Ask AI, Custom AI, these more advanced AI agent capabilities. These are already multilingual and have been from the start. But at the core of the solution are the dozens of models that we have tried and tested over the years to extract very accurately and at scale key standard data points from contracts, counterparties, effective dates, governing law, etcetera. And those models now are also being aggressively and rapidly converted into multilingual models using the latest AI so that they can work on contracts of all different languages. And we now host all of your data and the solution with full sovereignty in Frankfurt so that there, you know, no more issue of safe harbor and and cross border transfers and such data, that we're happy that we've been able to, you know, bring more and more EMEA based customers on board with our solutions over the last year, and we're absolutely determined to keep supporting them and expanding that. So we hope, you will, be of it to working with us on that basis. And with that in mind, I'm gonna now oh, one last call out. I mentioned this earlier. But, of course, we are ISO 42,001 certified in addition to ISO twenty seven seven zero one and ISO twenty seven zero zero one for data security and privacy, SOC two type two, and a range of other terms and conditions that I'm sure you will find, you know, very supportive for your needs. We're very happy to be part of Workday, which is also, I think, rare among AI companies in terms of its commitment to ISO 42,001. And with that, thanks for coming here, Lauren. My colleague based in Amsterdam, I will turn it over to you. Thank you, Hao. Great to be here with you all. I'm gonna run us through a demo. We are a little pressed for time, so I'm not gonna be able to cover the entire suite today, but I will get you the high level understanding of what our platform can offer. My name is Lauren Guides. As Hal mentioned, I live in Amsterdam. I actually just moved to Europe to help with the expansion of Evisort or Workday CLM across the EMEA region. I've been with the company for three and a half years. I came to Workday with the acquisition of Evisort slash Workday CLM. So have worked with this product since for for quite a while now. So let me go ahead and share my screen. I'm gonna start with our contract intelligence component first, and then we'll get into the Workday CLM or the Workday, contract life cycle management side of the platform. So we're starting with an executed agreement to get you an understanding of what we're gonna offer on day one when you upload your documents into the Workday contract intelligence tool. As you can see here, I have this document. It's not the prettiest, which is, intentional. When your documents are brought into our system, we're automatically going to run each one through an OCR process, which is ocular character recognition if you're not sorry. Optical character recognition if you're not familiar, which essentially makes all the text searchable and readable regardless of the quality or regardless of the format. We recognize that just because a file might be a PDF or something that you've worked with in a digital format before doesn't mean it's inherently searchable or readable. So by going through this text based, OCR tool first, everything will be searchable from a keyword or phrase component. Once we've done that, then we have over 70 different standard AI models that get applied to each and every document that you upload. So what you see here in the middle column is a list of provisions that we're able to identify. And on the far right, these are gonna be individual data points about this document that we can extract from each and every contract. So when Hal mentioned the standard models that we have, these get applied agnostically to every contract that's uploaded. Now this is gonna get you a really good starting place. And when I say on day one, I mean day one. This happens in minutes of uploading all of your documents. We're gonna be able to categorize the information from these contracts into fields that you can run searches on. So if you have ever been at the mercy of an auto renewal, maybe a free trial membership or something like that. We've all felt that pain. Obviously, from a business standpoint, that's a much bigger risk if you're not tracking your renewals appropriately. So renewal information, renewal dates, renewal notification periods are something we're automatically tracking, so you're gonna be able to know all of the documents you have that are up for renewal within a time period. Another example is if there's a change in legislation and you need to find all of the contracts you have under a specific governing law, that's something we track both at the field level and at the provision level. So you'll be able to quickly find all of your documents that are under a certain jurisdiction. So this information is going to be the day one data that you're able to track, but we recognize that we work with so many customers and so many different roles within each company that there's no way for us to track every single data point that is important to every single customer that we serve. So for that reason, we give you the ability to tailor and customize the platform and create new AI queries against your documents. One way to do that is through Ask AI. So if you remember slide the slides in house presentation about asking questions and having a conversation with your document, You can do this both at an individual contract level as well across as well as across a group or a folder of agreements that might fit some certain criteria. So looking at this document here in front of me, I'm just gonna ask a basic question like, what are the rates? This is a generative AI tool that allows me to interact with this document as you see here. But unlike the ChatGBTs or the Google Geminis of the world, we are only using a large language model that is strictly trained to read and write contract language. This is gonna be a much more secure way to use AI for getting this type of information quickly out of your documents. For one, there's no risk of hallucination because every answer that we give will be cited inside the documents. You know that the answer is pulled directly from the contract that you care about so you can validate it. Very important for legal teams to know this data is correct. But secondly, none of your contract data is being fed back to these LLMs to retrain them. If you were to upload your legal contracts into ChatGPT, you can be assured they are going to use your data to retrain their model and enhance it for other users. This is a one way closed system, which is that responsible AI designation that was on Hal's last slide that we are not collecting any information from your documents to retrain our large language model. So very important distinction there and a very safe way to use AI for queries against your legal documents. Now if this data is something you need to repeat at scale, if you want to be able, in this case, to track, let's say, all of your procurement agreements that have a volume rebate, I can turn this query that I this question that I ask into a new model that tracks across all of my documents. So going forward, I'll have a field here that tracks that there's a volume rebate in this type of agreement or in across my procurement documents. So you have the ability to really fine tune and tailor what the system is tracking at scale here. Last thing I'll mention, and then we'll get into a quick workflow overview, I am mindful of our time, is using that data at scale. So first thing I'm gonna do in my search engine is just run a blank search here, and you can see I've pulled up 8,700 documents in my account. Now any of those data points, whether it's an out of the box pretrained field, or a custom field that I've created, can be used to create a report inside the system. So going back to my renewal example, I'm gonna say, show me all my contracts that have a renewal notice date in the next sixty days. Now I'm going from 8,700 to 36 documents with just a single field. Maybe I only want to track my automatically renewing contracts from here. I'm down to 33. So now I have a report that I can start taking some action on. Maybe we want to free up some spend. Maybe we wanna cancel some of these agreements before they auto renew. I can share this report with other users inside the system by saving it and just sharing it with another team. I can export this report to an Excel file if we wanna work on a spreadsheet, or most helpful is going to be turning this report into an email notification. Rather than running this report as often as I might think that I need it, I can just have the system generate it for me on a regular cadence. Maybe every Friday or at the end of each month or at the end of each quarter, I want a rolling list of all of my contracts that are renewing. I can have this whole report automated and sent to me via email so I don't even need to come to the system to find out what's coming up. So very helpful for staying on top of some of your obligations here. We could talk all day about contract intelligence, but I want to pivot over to the contract life cycle management tool, which is gonna be for everything before a contract is executed. So with that, switching tabs here, I'm gonna go to an intake form. You're gonna have the ability to create as many different workflows as necessary for the different contracting processes that you might have today. If you've used another CLM tool in the past, this functionality is gonna be most closely related to something you may have used in, a legacy solution before. However, because we are con Workday Contract Intelligence or formerly Evasort, we have quite a bit of AI at our disposal to help streamline your contract negotiation and approval processes. So it starts with an intake form. I'm gonna go ahead and generate a new services agreement. I have the option to generate from a template. I can also work off of a counterparty document, and then I'm just gonna input some field data here so that the system knows what the contract should look like. We're gonna be able to generate a dynamic form based off these answers, And not only will the information in the contract be dynamic, but the approval matrix that this contract will route through will also be dynamic. So what do I mean by that? Here you can see that I have a note. If this is over a certain value, then a CFO approver needs to be automatically included. Or maybe if we're including confidential information, then the privacy department gets added. So this is a really easy way to ensure that all the appropriate parties are part of this approval chain without any guesswork. As the person submitting this information, I'm not having to pick and choose who's gonna be involved here. All of that is handled in the back end. So I'm gonna go ahead and create the ticket, and this will launch my workflow. And now I can start running it through approvals. I am gonna start as a legal reviewer and start my negotiation directly inside of the tool here. We have advanced version controlling, you'll always know which version you're working on. I'm gonna go ahead and click edit to launch my internal editor. It's gonna save a new version for me. We'll preserve version one, and I can start working directly here in version two. As I mentioned, we are an AI company, so we're using all the same AI that we saw on the agreement inside of our repository here in our negotiation as well. So we're gonna identify both the language in the document for all of the pretrained fields that I've already talked about and any custom fields that you might have created. We also have Ask AI available here. So you're gonna be able to ask a question in the same manner against this version as I'm negotiating. This is all just to make sure the data is very obvious to you so you're not missing anything as these versions continue to be created. You also have the ability to save any questions. So as you're running through a negotiation, you may need to ask the same question on every version. And rather than just asking it plainly each time, we can just save those queries directly in here. If I want to use AI to help with my redlining, we're gonna be able to leverage a clause library or a playbook that you've created to ensure that your first draft or all of your drafts are going to be in agreements with your legal team. So let me start with this assignment provision we've already looked at here. I'm gonna go ahead and say, let's pull up my AI drafting tools. I can select the variation that I want to use, and you'll notice I have quite a few here depending on how your team has created these. So I've got a preferred here, and you'll see there's instructions associated with each variation. Now I can click this generate button. It'll take those instructions into account and give me some suggestions against the provision that I've highlighted. It may give me a few different options. I can also go in and choose a different variation, but when I'm happy with it, I can accept the edit. It adds the red line and I can move on with my review. So again, this is just to make sure that the reviewers are all operating from the same set of standards and you don't need somebody who is going to go in and manually redline the entire agreement to bring it up to speed. The system already has the information of what you need to agree to, so it makes it that much more efficient and quick to get this through its first round of reviews. I can go ahead and communicate with the other parties by leaving notations on the document itself. When I pass this to another reviewer, all of the track changes are captured in a list so they don't need to read through the entire document. Somebody from a different team that might be looking at this can see what I've added directly in this track changes panel here. So just, again, driving efficiencies, making sure that we're not wasting time reading through the entire document. Then just to move things along because we are tight on time. When I am happy with this review, it was just one change. Probably would never happen, but in this case, we'll say one change is all we needed. I can go ahead and approve it, and it'll move it to the next phase of review. When everybody is in agreement and every phase has been completed, we can go ahead and integrate with DocuSign esignature or Adobe Sign to send it off for signature. The final document, once it is completed, gets routed to your repository so you have it available for your reporting, for all of the data needs that you might have, and we'll close the workflow, but you'll always have access to your old drafts. We just wanna make sure the clean, executed version is what is being reported on in the rest of your, Aviso or contract intelligence tool. So it kind of completes the life cycle here, and we'll make sure that the best and clean draft or clean version is what is being reported on across the board. So with that, we have about seven minutes left, and I wanna leave time for q and a. So I'm gonna leave it here. If you are interested in learning more, reach out to your your Workday point people, and we can get you in front of a more in an advanced demo. So thank you for having us today. I'm happy to stay on and answer any questions. And the questions have been flowing in. Thanks for that, Lauren. Many of them we've been able to answer in writing directly back to the people that asked them. There's a couple that are pending that I'll we'll address now live, and we can identify a few of the other questions that might be valuable for folks. So let's run through them. So a couple that are outstanding right now, does it work with manual signing if needed? Lauren, do you wanna address what what one would do with a presignature workflow if they wanna actually do a manual web signature? Yeah. Absolutely. So the integration into an e signature tool is just an option. If you wanted to download it and have it wet signed as as we call it in the industry, totally fine. You can just upload the final version back to the workflow and mark it as closed instead. So we we totally appreciate that not everybody is using DocuSign or Adobe Sign. And that also works if there's another signing method that you might want to use or if the external party wants to use their DocuSign account or something like that. You can always just upload the final and close it from there. And I see several questions that I'm gonna sort of group together from, several different people about the nature of the LLMs that we're using. What is the underlying AI within the solution? So there there's sort of a multifaceted answer to that. We have an orchestration layer that we've developed, which gives us the flexibility to use different underlying LLMs for the solution. So Lauren mentioned earlier during the demo that we have our own LLM, which is a fine tuned open source LLM that we have given the additional training to specifically on millions of contracts so that it understands that language even better. So that's one option that we use in some cases, But we also are able with our orchestration layer to leverage the best of existing generic LLMs out there at any given time. We are making a lot of use of a clawed by Anthropic right now. But we have used other LLMs in the system and we have the flexibility to do that. And that's an important thing to note because by means of being able to leverage the best LLM at any given time for a particular model or job that's being introduced in the system, this continues to evolve with you. Whereas a lot of solutions that you may look at that I know legal teams struggle with investing in, they realize if we go with this particular AI solution, what if six months from now the best thing out there is from a different company and we are locked into this one? So our approach is not to be locked in to any particular line technology. Instead, we have the sophistication to leverage them as we go. So and that said, there's also, I mentioned earlier, our standard AI models for extracting core data points upon ingestion of contracts. That is based on natural language processing, computer vision, machine learning technology that we've developed over the years that works very well at scale to ingest those data points, and that is proprietary AI that we use as well. So it's a combination of factors. A related question on that was do we work together with external AI such as Harvey or something like that? So we are not specifically integrated or connected with any sort of pan legal solution like Harvey. There are several others that have emerged, and Throttle has its own now that they just announced recently. So there is no one that we are integrated with in that way. Let's see. Another questions. Oh, a couple of questions came up about our integrations. So let me highlight again on that. We leverage, we are already integrated with Workday single sign on. So the one sign on experience will get you into CLM. We are integrated now with Workday strategic sourcing and procurement to to various degrees so that we can use your supplier contracts. We can we can help with the creation of those contracts and then deliver those critical data points into the ongoing procurement solution. We are also integrated with for revenue contracts with the accounting solution to make it easier to create those invoices from extracted data points in your customer contracts and other revenue contracts. We are not yet deeply integrated with the Workday HR solutions. We're at early stages of that because there's quite a lot we can do there, but we certainly have the ability to ingest employment agreements in the Workday system and do that analysis of those contracts at scale. Hope that that addresses it for now. That's obviously a very fluid front, a lot of work going into that development. Let's see. We have another question that just came up about LLMs operating on tokens. How does this affect end customers? Most of what we showed you today does not incur any kind of ongoing additional cost. It's included in the subscription to our system, which actually works on the following basis. You pay based on the number of documents in your system on a tiered basis as opposed to paying for user fees or per seat fees. And that's that's a very conscious choice on our part because we want you to be able to share the insights that you're getting from Eversort with all the different parts of the business and not have to worry about how many dashboards you have or how many users are accessing them. So for the most part, it's very straightforward. However, customization, we talked a lot about custom AI models. Those do incur additional cost the more that you customize. And some of the newer AgenTA capabilities that we mentioned that are in the road map, some of those will incur flex credit charges within Workday to use those, and we can give you more information about that as needed. Question about data retention related to functionalities today. Lauren, do you want to address that in terms of how it is that we manage your data? That you're talking about the data retention question? Yeah. Oh, you know what? I just realized the time. We're gonna get cut off momentarily. So. sorry. I will just leave it. That that one will have to do as a follow-up. Feel free to reach out to me directly, hal. Marcusworkday dot com. And I am meant to launch a survey for those that can stay on for an extra minute or two and tell us what you thought of this webinar. I hope you find it valuable. And we really appreciate all the time, the engagement, all the questions that you raised. Thanks so much for being with us today on behalf of Lauren, myself, and Anya. And I think we could probably keep going but I think we're going to be cut off momentarily on the webinar. So wanted to get that in before we are gone. Thanks for joining us, Sonya. Thanks, Lauren. Thanks, Good. everyone. Take care. Thank you.