Name: Build Your Contract Playbook with Workday CLM, powered by Evisort AI
Uploaded: 2026-04-30T04:16:09.427Z
Duration: 1 h 12 s
Description: Build Your Contract Playbook with Workday CLM, powered by Evisort AI

Transcript for "Build Your Contract Playbook with Workday CLM, powered by Evisort AI": Hello, everyone. Thanks so much for joining us. Really glad to have you here. Let's kick things off. So this event is build your contract playbook with Workday CLM powered by Evisort AI. Really glad to have you here with us today. I wanna give you a couple of, notes right up front, questions that we always get. Yes. Today's webinar is being recorded. We'll make it available on demand later. Please don't leave. We would like having you here live now. We will make it available so that you can share it later with anyone else in your organization that you think would benefit from this. We will take q and a, through the q and a window, and we encourage in fact, please ask as many questions as you can think of. We look forward to receiving them throughout the event. We'll either answer them in real time or in writing, or we may hold some for the end, depending on the nature of the question. Please use the q and a box, not the chat box to ask your questions. You will not see each other's questions as they come in just the way this is structured. So don't worry that you're not seeing others. We are seeing them all, and we will address them all. And with that oh, one more quick note. This is our product statement. We will be talking about some road map items, some things in development. We are a public company, so I think this, legally says don't take us too seriously in all the things that we say. Alright. With that, let me welcome on my partner in crime here, Ben Kane, a solution consultant for Workday. Ben, thanks for being here. Thank you. I wanted to introduce yourself real fast. I'll do the same, and then we'll kick things off. Absolutely. Hi, everyone. Thanks for taking the time. My name is Ben. I'm a principal solution consultant here at Workday. I'm based in Chicago. I focus on our spend management areas within Workday, Evisort being a big component of that. So excited to show off the tool. Thanks, Ben. Your my name is Hal Marcus. I'm a principal in product marketing here at Workday. I'm a lawyer. I'm a former general counsel. I'm a former, litigator at a large Wall Street firm. But many years ago, I got into legal technology, and now I've been doing that for a long, long time. I've had roles in a lot of major companies, Thomson Reuters, LexisNexis. And about three years ago, I joined the team at Evisort. At the time, I I previously been at DocuSign and focused on AI for contract and e signature use cases for quite some years, AI for ediscovery use cases before that. But I joined the team at Evisort about three years ago, and then a little over a year ago, we became part of Workday. And there's a key reason for that. Workday was a customer of Evisort. The legal team and the procurement teams for several years were both using Evisort to manage their contracts on the on the, buy side and on the sell side in different ways. And their results were so strong that eventually, they just decided to buy the company and make it part of their suite that they could offer to the, you know, the vast Workday audience. So very glad to be here, very glad to be launching, in effect, the CLO focus, you know, the office of the CLO as a key focus area for Workday. So with that bit of background, let me launch into, what it is that that Evisort was about, which is now Workday contract life cycle management, how we approach the market, what some of these capabilities are with an eye toward how you can create your own workflows, create your playbooks, and really use AI to take a much more intelligent and effective, and successful approach to how you manage contracts. And then I will hand it off to Ben. He's gonna take you live into the product, walk you through a lot of the things that I've just talked about. So the ethos of Evasort, how it came to the market, could hear how, but not been. Okay. Hopefully, that's not an issue going forward. But as long as you can hear me for now, Ben, we'll make sure your mic is, is working when we come in later. They, and please keep those questions coming. I hope others will not be about technical issues, but welcome any questions that you have. So, this is the ethos of Evisort. This is how Evisort approached the market back when it was founded in 2016, And it was picked up by actually a a few students at Harvard Law School and a friend of theirs over at MIT, and they developed it in the Harvard Innovation Labs. Their focus was that, you know, contracts are really critical to business. But most of the world of contract life cycle management, really the whole historical focus of contract life cycle management for decades, had been to treat contracts as documents that you're trying to get signed. Now that's critically important. Don't get me wrong. And all of those tools have been, you know, valuable to various degrees over the years, but their concept was to use AI to look at contracts a little differently because contracts are not just documents. They're also data. They're a series of data points. They're unstructured data in in, artful language that really often needs to be turned into structured data that you can leverage throughout the business. And that's a real challenge is a challenge for businesses. Really, any kind of organization has multiple departments that care about different kinds of contracts across the organization, and they need data points from those contracts to do what they do to make informed decisions. So this is about more than just getting a contract through the signature and then being able to find it later. You need to, without having to reread the contract on a regular basis, get quick access to those critical data points. And that applies whether you're in the office of the CFO, the CHRO, CIO, or otherwise. It's particularly important for corporate development, business development, and post m and a and even pre m and a activities. So, that is critically important, and these teams have been going through legal to get those answers. Legal often can't get those answers. And based on the the, you know, great response we got to this webinar, so glad to have so many of you on with us today. I'm confident a lot of you in legal have had that experience as well. So what this is about is empowering you to answer really any question that you have around your contract and sometimes get those answers without even having to ask. So with that quick brief overview, let's talk about how Evisort pioneered AI native contract management. AI native mean AI from the ground up, from the first line of code, not as an afterthought to enhance a CLM solution. Big difference. Three core things that we do. The first is to connect with your contracts wherever they are in virtually any format that they would be kept in. And this means cloud stores. This means, you know, hard drives. This means tools like DocuSign, SharePoint, Salesforce, wherever you might have contracts that need to be pulled into the system. We bring them all together in one place. We apply advanced OCR and AI that augments that OCR and helps create great data even from things like tables, even from handwriting, cleaning up bad scans, all sorts of things that throw off the ability to make these contracts truly searchable and and workable. We have AI that improves all of that at scale, and we we we get top marks for it year after year. The second stage then is to empower you with everything you need to analyze all those contracts to literally know everything about them. And I I don't I choose those words carefully. I mean, everything because you can ask anything about those contracts. You can make it really easy for you to get those answers that you need. And then there is a third key piece, and this is where CLN historically was always focused. And that was about your workflows, your approvals, your routing of those contracts during a ticketing, editing, negotiating, drafting stage, presignature, including with the signature. So we provide all of those capabilities as well with self-service workflows that you can control, and we empower them also with AI in ways that I'll show in a moment. So these are the three core things that our solution provides. Now we go to market in two ways, with Workday contract intelligence, which is these first two boxes, because that is geared for companies and organizations, legal teams, etcetera, that want to have all of this visibility into their post signature contracts that they've amassed over the years, but aren't necessarily right now looking for presignature workflows. So we do have that option available. However, our contract life cycle management solution includes all of the above. It's all of the workflow capabilities, all the presignature capabilities, integrations with e signature through DocuSign, through Adobe Sign, but also all of that contract intelligence. And that's important because the best way to guide your presignature workflows and enhance your processes and make this all faster and smoother and lower risk is to learn from your post signature contracts. What is in them? What do you agree to? What do you not agree to? Inform your playbooks, and that's the theme of this, session today about creating your playbooks. Using all of that intelligence to make sure that your playbooks make sense and that they continue to make sense as you go forward. So we bring all of that together under Workday CLM powered by Evisort AI. Now we often in this space, and and and you'll hear it more and more these days, talk about agents. What does that really mean? This is about going from a traditional AI, if you will. I've been doing this about twelve years, but I I, you know, feel like that's a little early to call anything traditional in in my view. But that's about where we are. It's moving so fast that we have traditional AI just based on natural language processing, computer vision, machine learning, other tools. Those technologies have been, you know, in our solution from the beginning, and it's how we ingest so many contracts so quickly at scale with such a high degree of accuracy. But then generative AI came along about three years ago and really supercharged those capabilities. Now we are at the point where the interactivity, the ability to customize, the continuous nature of what we do is putting us at, admittedly, an early stage of what is going to be an impressive continuum of agency, of the AI being able to take on more and more of these capable of of these requirements, of these tasks for you, and you're entrusting those agents more and more to deliver that information and take action for you. So we are at a stage now where our solutions effectively include two agents. With Workday contract intelligence, you get what we call our contract intelligence agent. With Workday CLM, you also get our contract negotiation agent. So let me take a couple of moments before I turn it over to Ben and talk about what are some of those more agentic, more advanced AI capabilities that we're talking about here. So here's the first, and that is our conversational experience, what we call Ask AI, which is the ability to ask questions of one, all, or any subset of the contracts in your repository. Let me be clear about that. I think people are getting used to the idea of, you know, being able to ask questions about one document or maybe even a few after they've gone through a loading process into an AI experience. What we have here is the ability to ask questions across your entire contract repository even if we're talking about hundreds of thousands of contracts. You can also be much more specific and ask questions about a folder, about a type of contract, or about contracts you've already filtered. Perhaps in a dashboard or a search, you've already narrowed down the contracts with a particular choice of law, particular jurisdiction, that are above a certain contract value, that are also MSAs. Whatever parameters you put on that, now you have the ability to ask questions about those. These questions go into a specially trained, fine tuned environment with heavy guardrails for this kind of use case. This is very different from throwing it into chat g b t. Considerably more advanced and pointed for this use case. And from the beginning, we've had links to the part of the contract that gives you these answers so that you can always validate the response you're getting. Plus, we use advanced technology like retrieval augmented generation, WAG, which, is really about leveraging the information we already have created about your database of contracts to inform these answers. So, again, very different from just sending it off to a generic large language model and asking questions. So it's built for this use case. So that's Ask AI, and you'll see it in action soon. But an equally important aspect of this is the following. We've provided the ability not just to ask questions, you know, based on the full text of the document and on those core extractions that we do when you ingest the contract. We've created the ability for you to customize the AI to go further and ask anything you want. And once you turn that question into a custom AI model, it will run automatically against any contract in the system on a rolling basis. The example here actually came from one of our customers where the chief procurement officer of a major financial organization, had an issue one day. He was asked by the chief, finance officer, what is a good benchmark to use for how much our vendors can raise prices on us next year? Do I have a risk if I go with 3%? You know, that's just my guess. Is that is that fair? And his chief procurement officer, unfortunately, had to answer, you know what? I have no idea. So he has instead implemented Evastore and used the ability to ask these questions to come up with these standardized answers across all the contracts. That's custom AI. You have complete control over it, and you can create these new questions independently. You don't need to invoke services to do it. It's very straightforward. So these are core capabilities, core skills, if you will, of our contract intelligent agent. Now what do you do with all this data? Well, if the data that you're creating is a simple number or a date, or a small piece of text that's relatively consistent from contract to contract, well, this is great for charts, which go into dashboards, and you can have as many of these dashboards as you like. Also, self-service, create them as you go, check boxes, click and drag, very straightforward, always current, lightning fast, and fully interactive with your contracts. So when you click on any of these, it will automatically filter down accordingly based on whatever you've clicked on in the chart. By the way, I've a few questions have come in. I'm gonna try to address them in real time. One of them that is right on point. Does contracts include documents like handbooks and handbook addendums that are configured in Workday Drive? So, obviously, a Workday customer has already has this. Yes. The short answer is yes. You can and our customers have long ingested noncontract documents that are, you know, that are related to contracts, that are supporting documentation, handbooks, agenda, statements of work, invoices, things like that that relate to the contracts. Now I don't wanna overpromise that in that our AI is not necessarily fine tuned for any kind of document that you could conceivably imagine. But we have, you know, it does work very well with many kinds of documents. And one example would be a lot of our health care clients pull in, physician licenses, because for HRSA audits for for Medicare, they need to be able to show that all of their personnel are are current in their licensing, and we can extract those, renewal dates or expiration dates on their licenses very effectively. So there's many kinds of creative uses that are very effective. And so I think the use case you put forward is certainly viable and would be good good one to to discuss with you. By the way, to that end, any questions I don't get to or anyone that wants to reach me after this event, I'm just hal.marcus@workday.com. Not hard to find. You can also get to me on LinkedIn, so don't hesitate. Happy to take your questions. Okay. Back to the what we do with this data that you're creating. So what happens when the data that you create with these models is not actually just a simple number or a date or an amount that's been calculated or a date that we have figured out or a date we've extracted? What happens when it's something even a little more advanced, like a summary of terms? This first one on this page, I particularly, gravitate toward because so many of our procurement customers find this really valuable. A rebate, a volume discount, and early payment discount, these can be scattered across six different parts of a contract. We know that these are not easy things to just extract and understand. So how do you make them readily usable by other teams? Well, REI can actually go ahead and summarize all of that in one sentence and put that in pretty plain, simple language. Yeah. There might be a slight nuance that might get overlooked with that, that a lawyer like me would wanna dig into the contract for. But generally speaking, we can provide this information out at scale and make that information available, not just in our product, but essentially anywhere you want it. So we're looking here at a table display of contracts for master service agreements within Evisort, within Workday CLM. And as you see, there's now a new data field that's been created by custom AI summarizing that, all those financial terms that we had so we can make sure we take advantage of them. But all of these data fields can be sent across through API to virtually any other solution where that information would be valuable. And, of course, it can easily be, you know, exported out into, you know, basic text format to be used in other ways. Also, and this probably will not surprise you now that we're part of Workday, we are aggressively integrating all of these capabilities with Workday financial solutions like, strategic sourcing and procurement, where CLM now is becoming part of a seamless transaction from sourcing vendors over to starting the contract with them to feeding all that contract data into an ongoing relationship management, service through procurement. On the finance side, we are, doing this with revenue recognition for customer contracts where we can now extract core terms, deliver those into Workday financial solutions. So more and more, you will see these types of when I just saw the question pop up of how will Evisort work in conjunction with Workday strategic sourcing. So hopefully, the quick overview I just gave was helpful, but certainly much more to cover there. I we will not have time today's session, but we'd be happy to schedule a follow-up. And we also do webinars on that topic as well. So, great thing to explore. Reach out to your account rep, and we'll walk you through it all. Okay. So, one quick, summary here. I I don't wanna take too much more time away from Ben's demo, but I wanna cover a couple more things. Firstly, these are just some of the examples of how our customers use, custom AI, not just our core extractions, to, automatically identify terms. In fact, we've we've identified over 200,000,000 contract terms for our customer base using custom AI models. And these are just a few of the examples from some major corporations, where they're trying to understand how do they manage their supply chain, how are they staying compliant, how are they going to be able to you know, during the supply chain disruption, how are they going to be able to maintain their cash flow, and that required analysis of a whole lot of customer contracts. So these are the kinds of things that no system is automatically programmed to identify across all your contracts. This is why we use that language of know everything about your contracts because you can choose what it is you wanna understand. Alright. Now everything I've talked about so far in these agenda capabilities has been about our intelligence agent, which is really more about the post signature contracts. Again, critically important to inform what your workflow should be, to bid good into your workflows, if you will. But, also, our contract negotiation agent uses advanced AI as well to suggest red lines, draft clauses, compare terms in a presignature contract against a playbook to automatically find those pinpoint changes, which can make this a much smoother, faster process. So these are just some of the ways that AI gets used in a presignature contracts in conjunction with your playbooks. Now here's where our product statement from the beginning of this session kicks in. I wanna talk a little bit about some of the things that are coming and give you, a sense of what's coming soon with our contract negotiation agent. This is the two core new developments, really three, but, I'm grouping them into two for simplicity. The first one is about reaching agreement faster, negotiating better contracts in a faster way. Second is about getting aligned internally around what your preferences are and keeping that real as you go. So here's the first. Auto redlining, we heard from customers, is a great time saver. Adoption has grown. People have seen this over the last two years and been very impressed, but they really wanna now take it to the next level. Doing this on clause by clause, very specific basis. Now they wanna start handing it off in a more agentic way over to automated capabilities, and that is why we are now introducing full document review and redlining, where the system will compare your playbook against a presignature contract. I should really reverse that. Compare a presignature contract against your playbook and find the areas where there are gaps, where there are inconsistencies, identify the risk as high, medium, or low, and suggest red lines that will make the difference, make this easier. So you can go through and just approve those, do that first pass review quickly and easily, validate it, and then send it off to the other side. I negotiated several 100 contracts personally back in my my days as a GC for a a midsize software company. I would have loved to have had these capabilities. Now here's the other piece of it. Playbooks are obviously central to what I just described. They document your preferences, the terms you care about, what you will or won't agree to. How can you make them easier to build and to maintain? Well, we already have a clause library capability. We already have the ability to enter prompts and store data. We wanna make it even easier for you to do this. So we are introducing, a little later this year, custom playbook capabilities with AI creation capabilities. So the AI will look at existing contracts, will look at the data that you give us, documents that you put in that are unstructured format, and turn those into playbooks that we can use to compare your contract to the playbook and make your presignature process infinitely faster and easier. So, you know, this will make, even more sense when I hand you over to Ben in a minute, and you get a look at what we have in the product right now. This is a matter of months away, and it's something that we're very excited about. Also, we don't wanna just theorize here. We wanna keep it real. And that is why you will see not just the ability to create these playbooks in a more agentic way by just grabbing the documents that will inform it, but also, a bit later this year, the ability to track how you are, you are trending against those playbooks. I've worked with so many council over the years that say, well, this is, you know, our standard. And then when they find out from their post signature analysis when they bring tens of thousands contracts into Evisort that, actually, that's not their standard. They deviate from that standard about 80% of the time. Then they come to understand that perhaps they're holding up negotiations over something that they already determined in practice does not matter that much. And it's time to revisit what those preferences are so that they can have a smoother, faster process. That's what playbook analytics is about, reports to show you at any given time where you stand so that we can enhance your processes on a continuous basis. Alright. So that is what's coming. Again, subject to the product statement at the beginning, our full document review and redlining and custom playbooks and analytics, two key areas of AI focused innovation this year that we're throwing a lot of energy and resources at. Resources at. So I'm gonna hand you up to Ben now for a live demo. I'll come back in to answer q and a, and I'll be answering some in writing on the side. But one quick quick quack. One quick last little plug before I go. If you found what I've described so far useful and this is an area of interest to you, I wanted to let you know that we have a podcast that we introduced about 18 ago, where every month, my colleague, Memeo and Woodyway, and I interview thought leaders in the space of legal AI and talk about a range of issues, but in particular, how this affects contract management. So there's a code there. You can find this wherever you get your podcasts, and, hope you find that useful. And subscribe and reach out to me if you have further questions. With that, I'm gonna hand it over to Ben and go off stage and start answering some of those questions in writing. Thanks, everybody. Alright. Fantastic. So, hopefully, everyone can hear me now. I'll I'll ask you to come back on and tell me if we're having issues with audio as someone may have mentioned in my introduction. But I'll do that again just to say hello. My name is Ben. I am a solution consultant here at Workday. My specialty and focus is in our spend management areas of Workday, for which Evisort falls squarely within. So I'm excited to show you, Evisort today and show you the CLM capabilities. Any issues with audio so far? Alright. I think we're good. Alright. So what we're gonna walk through here today is going through the process of getting a new contract to signature. So what we're looking at here is our workflow capability. So this would be the perspective of really anyone within the business, whether you are in legal, whether you're in procurement, whether you're in sales, whether you are, you know, a, entry level employee. No matter what, you're gonna have this workflow, menu available to you where you can pick all of the different options for types of contracts that we would wanna get put in place. So this could be sell side agreements, could be buy side agreements, could be employment agreements, could be simple NDAs or very complex services agreements that we actually need to negotiate with our vendors or customers. So for today's example, we are gonna use a vendor services agreement as our example. Now this is taking us to a fully configurable, form for creating this contract. So you can build specific to your organization exactly what you wanna see represented, what questions you need to ask from your business users in order to get the right contract put in place with the right terms. Now the first question that we see here is, are we gonna use a contract that we're using, counterparty paper for, or are we gonna use our own internal template? Either one is possible. So if we're using counterparty paper, maybe we received that via email, maybe we received that through strategic sourcing, when running an RFP. No matter where it came from, we can go ahead and upload that document directly from our local computer. And as you can see here, we we support a number of different file standard file types. For the purposes of our demonstration today, I actually wanna show you the capabilities, we have related to utilizing templates, within the tool. So you'll see some really cool functionality as it relates to Evisort being able to generate contracts based on those templates. What we're seeing here in terms of these fields and questions that we're asking are just simply examples. You can make this very simplistic. You can make this very complex. Really just depends on what your goals are for collecting this information from your business users. But what you'll see here is a number of questions that are gonna be things that ultimately end up in the agreement. So things like, who is the supplier or counterparty? How should we refer to them? Are they an LLC, a corporation, a partnership? What is gonna be our jurisdiction, in terms of geographic location, state, country? What is the internal entity if we have different variations, different, legal entities within the larger organization. What is gonna be the start date for this contract? What is the term length? What is the contract amount set to be? And you'll notice here, these type of things can drive approvals. So if a contract is over a certain spend threshold, that's gonna be subject to an additional level of approval, maybe from the office of the CF. We can dictate or ask questions around what kind of provisions and language we need to build into the contract. Maybe we need to include non competition language or confidentiality language. Maybe we want to go ahead and put placeholders in the contract for our signatures, both internally and externally. So all of this information that we're filling out here can drive approvals, drive the workflow, drive what happens next, and also drive the template that is gonna come out the other end, when I click create ticket. So when I click create ticket, what it's gonna do is give me a fully compliant first draft utilizing our templates or your templates. If it's something simple like an NDA, this can be a really quick powerful tool for generating that simple document and making it available for us to download and share it, to our counterparty. Or for something like a vendor services agreement, we'll probably wanna wanting to actually go in, do negotiation, do redlining, and review. So that's where we get to this kind of, ticket workspace here. So as promised, we have the contract document available to us, and we can actually make edits to this document, directly. So we have an in app editor that allows us to make changes, redline, do all the great things that you expect from a document editor, or we can take this offline, and do it on our local desktop and upload that new version. That will also be the same way that we share the contract with the vendor or the counterparty. So if we want to send this out to the vendor to take a look at after our first pass, we simply can share the current version from the tool or download it, put it in a more personalized email, and send it off. Every single change that is made to this contract, whether it be, internally or on the counterparty side, is always going to be tracked. So you're always gonna have a history of every single version, every change that has happened no matter how small, and we can always make comparisons, between versions to see what's been changed. And that's true even if there has been a change, if track changes, for example, has been turned off in Word. The Evisort tool can still make sense of how the documents differ from version to version. Now what we're seeing here on the actual document, there are some really cool things built in here. You'll notice these highlighted areas of text. Notice that all of these highlighted areas are the bits of information that I entered into that intake form. So the start date, the California jurisdiction, the counterparty name, the confidentiality language that I said I wanted included, the non competition language, the three year term that we designated. So all of those things that are event or contract specific outside of the template are gonna be highlighted for you here in yellow, so you have that peace of mind that that information got embedded into the template. Now at this point, what we can do is start using AI to review this contract. So instead of me having to read through this entire document, being nervous that I may have missed something, I can start asking AI, questions about this document to ensure that we are not agreeing to anything, that we that is suboptimal or that may put us at risk. So at this point, let's imagine that we've sent this to the supplier already and they've made some changes to the language. I and from there, we would wanna start asking questions of this document, and we can build questions out so that we don't have to write them out every time. So we can have sets of questions related to things legal would care about, things related to supplier compliance or procurement. So that we really can democratize those questions that a legal team member would normally be asking and have those built in as standards that we're always asking about. So for example, maybe I care or wanna make sure that our indemnity requirements are sufficient. So I can ask the question, does this contract, meet our acceptable criteria for indemnity? And tell me yes or no, and then give me the rationale for why it is compliant or not compliant. So using that natural language, I'm gonna get a natural language response from the AI here, and it's gonna tell me that, no. This, indemnity language is not, in compliance with our preferred language. And it's gonna give me two reasons why. One, that affiliate affiliates are included and that the standard of conduct is too broad. And it's even going to cite its sources. So it's gonna take me directly to that place in the document that it made that determination so that I can go investigate it further. This isn't meant to be just a run the run the review with AI and just trust it implicitly. We wanna use this to more quickly find things that we should be paying attention to, and taking action instead of just having to read through the entire contract. So now that I know we have an issue with our indemnity language, I can actually start using my playbooks here. So I can highlight that bit of text for my indemnity clause and bring up my, AI drafting tools. And I can say, I'm trying to edit or make changes to my indemnification clause, and I wanna try and get it in line with my preferred indemnity, terms. Or maybe we've already lost that battle, and we now are, at our fallback terms for indemnification or our walkaway terms. These, constitute our various playbooks. So for every clause, we can have these different variations, and with these variations come instructions. So the AI can be instructed, either with very simple instructions as we see here, or a long explanation of of what constitutes our preferred language. So in this case, we're saying we can't indemnify affiliates. We must require gross negligence or willful misconduct to trigger indemnity, and written consent to settlement must not be unreasonably withheld. So with those instructions, the AI can go to work on this existing language and provides a really targeted red lines and changes and additions and subtractions, to that language. So I don't have to spend that time going through, writing out the legalese and making changes. I can use the AI to save me a lot of time here and simply accept that edit or make changes to it as I see fit. But that's gonna save me a lot of time, in the aggregate, when we can do that kind of review across all these important clauses. Something else that's really cool here is it doesn't necessarily have to be, a specific standard clause. I could just take any bit of language that I don't like or have issues with and utilize the same functionality, and just giving bespoke instructions to the AI for how we should make changes to this language. So, again, I'm saving time not having to write up that legalese. Similarly, I can use clause creation, more generative, AI here. So maybe I wanna build in net new language into this contract that falls outside of a standard clause. I could say something like write me a dispute resolution clause in which arbitration must occur in California. And with that simple instruction, I can now get not one, not two, but three different variations of how we could write that language. Again, saving me time, and I can just utilize that language and insert that language into the document as I see fit. So I really want you to think about this as democratizing, the knowledge that your legal teams have and putting this kind of guidance in the hands of really any user. We can give everyone an idea of what legal's the legal team's preferred, variations are, And that is gonna help make these contract negotiations go much quicker and allow people to have an idea of of what needs to happen in terms of changing this language. Right. Wanna point out as well that we can really use AI for anything as well. If we're going through the review and we have concerns or questions about any bit of language, we can use AI to ask those questions, or maybe generate things for us. So really good example would be, folks in the approval chain not wanting to have to read through the entire document. So we might be able to ask the AI to say, write me an executive summary of this contract. So, again, instead of me having to read through the entire contract as a approver, I can just get the high level details. And I could, of course, get more specific with my prompting here. I could say, give me an executive summary that includes termination rights, key clauses, start and end dates, contract value. So I could get as specific as I wanted to. But you'll notice here that even with that fairly basic prompt, I get a really nice natural language response, where the tool is also citing its sources. So that for those key terms, I can navigate directly to the place in the document and read a little bit further and and see the edges of that language to better understand. So these kind of things are really powerful. And for any of these questions that we feel should be automated or done on all contracts, maybe we want to always have an executive summary, created. We can actually automate this and use a custom AI model to always have the AI generate an executive summary and place that into a reportable field so that we can more quickly, find that for any given contract we hold. Alright. Now lastly, I wanna point out how all of these contracts are gonna be, examined by the AI and all of the key language is going to be identified, across these different clauses. That's very important for understanding your contracts in the aggregate as well. So, you can start understanding trends, understand the language that you've agreed to in the past, and see how, what kind of patterns you have in terms of what you've agreed to. And then lastly, wanna point out we also have an approval process built in here. So you can build out various rules for who needs to review and approve these contracts, and that can be really be based on any criteria, whether it be the type of contract we spend, the counterparty, the category, whatever it may be, that can drive who needs to approve it, whether it be multiple groups as we see here with a legal review, compliance and security, as well as a finance review, or whether that's made up of multiple individuals, single individuals, we can really get, very specific in how these contracts should be approved. But I'll go ahead and act as all of these approvers here for the sake of our demo. And once we get that, all of those approvals done, we then can move to the signing stage where we can send this out to DocuSign and or Adobe Sign. We have direct integrations with both. So once the signatures are, given, those tools will send back the signed copy and will store that contract within the repository just like any other contract. And that's really where the power of the AI comes into play in terms of being able to extract data out of these contracts and provide some really powerful reporting to us around what we've agreed to, what patterns do we have, where do we have governing law, who are our big counterparties, where do we have effective payment terms, where do we have terms for convenience. All of that reporting is gonna be more or less automated because the AI is able to extract it as soon as the document enters the system. That's helpful for procurement to understand when contracts are expiring, when we have to take action on contracts that may need to be manually renewed. It can help us understand where we might have, benefits in terms of, early payment discounts or volume pricing, or, again, just simply having terms for convenience. We're able to understand that across all contracts without having to do the metadata entry that other systems would require to do this type of reporting. This is all gonna happen through that automated metadata extraction. So with that, that was a very, quick overview of the contract life cycle management piece and a bit of our contract intelligence piece. At this point, I'm gonna pass back to Hal to, close this out and finish up. Hi, Ben. That was great. We've got a lot of questions that have been coming in. I've been trying to keep up. Let me call out a couple, and I think at least one of them will warrant you're going back into the product and showing some more things. So we will run down you know, we'll go to the top of the hour here. And and, again, any questions we don't get to, just my first name dot last name at workday, and we'll we'll do follow-up for you. So couple of questions. Oh, one that just came in. Actually, let me get this one out of the way fast. Do we price based on the number of users? And there's more to it, but the short answer is no. We do not price this based on the number of users, but rather based on the number of documents in the system. And that's very intentional because we want you to be able to share access and dash boards and all of that with whomever you'd like across the organization. All the different business teams benefit from this data, so it is based on the level of use. And that also makes the system very scalable from small organizations up to some of the largest companies that you can think of, some of whom I'm happy to say are our customers and have been for years. So we have a very, very diverse user base from small to, you know, solo, GCs, all the way up to, again, some of the largest companies that you can think of. So, other questions that have come in language support. What language support and translation capabilities do we have? Are those legal translations or literal English translations? Well, really neither. Let me be clear on this. So while we are for in many ways, a multilingual platform and more and more of our capabilities are becoming fully, you know, multilingual, at least across a range of languages, and that range is always growing, we don't literally do translations of the, of a contract in our system. So if a contract is in English, we won't translate it legally or otherwise into a different language. However, you can interact with it in different languages. You can ask a question in Spanish, and it will give you an answer in Spanish. You know, the capabilities of the generative AI that we invoke are are, you know, we were quite strong on that front across the range of languages. That, you know, there's a much more nuanced answer to be given to that, but probably now we're taking the time here for it. Happy to delve in deeper to, you know, what your needs would be. Many of our customers are global companies, and their contracts are in a range of languages, and we can support that to a large degree. There was a question that was a bit broader that was more about sort of work core workflow capabilities, you know, a user administration, that kind of thing. Then might if you're you're up for it on the spot, might be good to just go back in the product for a few minutes and just highlight a few of those aspects of it just so people get a broader sense of our CLM workflow capabilities above and beyond the AI. Yeah. Sure. Absolutely. Questions more about, you know, what can admins do within the tool? Exactly. Yeah. Creating a workflow perhaps on the fly, a little bit about routing, and perhaps a little bit about custom user roles, that kind of thing. Yeah. Absolutely. So, really, most things in the tool can be done by an admin. There's very little that you would have to reach out to Workday for, but you will have full control as an admin to create various workflows. So, again, that would be all of your different types of agreements, whether it be simple NDAs or complex, customer or supplier agreements. And this will allow you to, change things over time, control templates, control language, control how those intake, fields and things you're asking from your end users, how those end up in the ultimate contract. But all of this, as you can see, hopefully, is a, simple user interface for the end user. So there is no real technical expertise required. Admins could typically be a member of the legal team or procurement team or sales team, and manage this on an ongoing basis. Hopefully, that answered, most of the questions. And then I just saw I'm sorry. I was typing answers while you did this. I wasn't paying close attention, but looks like you're, focus more there on workflows. Can let me take a quick look at, user administration. Yeah. Absolutely. What we wanna get across here is because I think that was a very good question someone raised. They said, you know what? As I've looked into this product, I've seen a great deal about the AI, but a bit less about the full fledged sort of end to end CLM capabilities. And some of the questions that followed seemed to point to things like, how do you manage, you know, your user base? How do you manage access to different kinds of contracts within the system? So while Ben is setting this up, I'll, just sort of give you the highlights that this is a a system, again, that is in use, by some of the largest, you know, corporations you can think of, including some leading AI companies, that are using our system instead of, you know, their own AI, inherently. And one key reason for that is we have this full fledged, you know, capability to manage your users and their access points in a very granular, very secure kind of way. So that's a bit what I was hoping to get across. You can define user roles within the administration module so that users have very specific capabilities about what they can and can't do. For example, you don't wanna have every user have the ability to create a new data field on the fly and create a a custom AI model to populate it because that can lead to really messy data inconsistency. You wanna have that more controlled, more centrally. You certainly don't want your users in procurement to have access to employment agreements, where they can be looking up the stock grants of major executives. You know, we have very tight controls around all of these things. And one last quick plug on that is a key area to look in terms of the security parameters around all these things is the certifications that apply, not just SOC two type two, which is important, but things like ISO twenty seven zero zero one, twenty seven seven zero one, which are about data security and privacy. And often overlooked, though it's growing in importance, ISO 42,001, which certifies a system as, an AI management system that is managed with an eye towards security, accuracy, transparency, ethics, and more. To my knowledge, which could be incomplete, but to my knowledge, we are still, well, something like a year and a half later, the only product in our space that has achieved an accredited certification price of 42,001. And I'm happy to say that all of Workday does that has that as well. We take this very seriously, and we think, customers should too. Thanks for hearing me out on that data dump. Ben, was there one you wanted to address or something you saw there? Unfortunately, I I can't show the user administration, but just wanna double down on your point that, you know, you will have full control over, access, at the user level as well as groupings of users or roles. You're always gonna be able to control who has access, number one, but a capability to not only just view, but also make changes. So you will have all of that capability down to the user level. We've got a couple more questions that have just come in, interesting ones. One of them is, can Evisort look at configured absence plans, compare with handbooks and addenda, and then tell me inconsistencies? That's a really interesting one. So, this must be coming from a user of Workday HCM for managing, you know, and and I know not everyone on this call is, but probably many are Workday customers that use the HR functionality. We are aggressively looking at more and more integration points for this technology with HR. So I welcome these kinds of ideas. That is not one that we have looked at to date. It is certainly theoretically possible, and we certainly can apply our AI to handbooks and addendums of HR policy documents. So, that that's an interesting one. Thanks for that suggestion, and we'll take a look at that. Another one that came in relates to what I was just describing with all the ISO certifications and such Is the company's in oop. It just bounced. Is the company's information secure and not shared or trained on by the AI? So that can seem to a slightly more nuanced area. The short answer is it is highly secure. However, they're subject to approval, depersonalized cleansed data can be used to inform the AI in limited ways. So not a not the simplest answer. There's some language to look in. Be happy to have that conversation with you and have you look and make sure that that meets your standards. Again, this is one of the reasons that we are ISO 42,001 AI certified. And, you know, I do not see that anything like a standard in contract management, surprisingly, even though you would think responsible AI is one of the top considerations for, legal users. We've had a couple of questions about WSS, Workday strategic sourcing and procurement, and how we integrate there. Again, not the kind of thing I can answer in one minute too effectively. Very high level. Let me describe it this way, and I'd encourage you to reach out to your account rep so we can walk you through it in much more detail. And or keep an eye open for future webinars where we will get much more in-depth on that in those topics where, you know, we we have done some dedicated webinars just on this topic. The short answer is this, start your process in Workday strategic sourcing, kick off a contract from WSS in Workday CLM that will automatically create that contract workflow or or kick off the contract workflow, I should say, and we pick up the basic data from strategic sourcing to kick that off. And then when there's a signed contract in Workday CLM, that is delivered across to create the record in Workday procurement so that you then have all of that information to inform the ongoing relationship with the vendor, the supplier. And that, you know, stays true even to renewals and such. So we are rapidly working toward a seamless, fully integrated, solution with Workday strategic sourcing and procurement. So that entire source to pay process is leveraging all the capabilities that we have. We're making very good progress on that front, and, we have some customers using more reversions, and, we will have much more to announce in the next few months. The question also follow-up on that is what is the CLM product offered through WSS different from the main CLM product? That's an easy one. The answer is no. In other words, you you would have to have Workday CLM to take advantage of this. It is not a watered down product that just sort of gets baked into WSS. So you'd have our full capabilities, including the integrations. And as we described, the integrations on the revenue side, we are doing similar things with supplier contracts. You will actually see a supplier contract agent in our road map that will take this even further, and give you more advanced agentic capabilities to leverage our folk, you know, AI capabilities against those agreements. I think that is more words than I have used in an hour in quite a long time. Thanks for your attention, for your focus, Ben. Thanks for the demo. We are just about at time, so barring any last questions, we will wrap it up. Again, I hope you will, I'll put this back on the screen real fast. I hope you will, tune in to our podcast to learn more on this front. I I hope you'll reach out to me directly, hal.marcus@workday.com, with any further questions.