Name: Unlock Your Contracts: Workday CLM & Contract Intelligence
Uploaded: 2025-10-09T10:16:06.209Z
Duration: 1 h 28 s
Description: Unlock Your Contracts: Workday CLM & Contract Intelligence

Transcript for "Unlock Your Contracts: Workday CLM & Contract Intelligence": Hello, everyone. Really excited for today's conversation talking about Workday contract life cycle management and Workday contract intelligence. We're gonna give it just a minute or two. We got a lot of folks in right now. We have a lot of folks joining every second. So let's just take a few more moments for folks to trickle in. Then after a minute or two, we're gonna kick off today's session in earnest. While we wait, feel free to use the QR code on the screen just to learn more about different sessions that we offer here. There's a lot to learn about the opportunities and capabilities of Workday. And so by using the QR code here, you can actually learn about some of our other sessions, customer stories, demonstrations, use cases, etcetera. But like I said, we have a lot of people in actually well already. A lot of people kind of joining every few seconds. Before we just give it a minute or so more for folks to hop on, and then we're gonna kick off today's session. I hope you're having a good day, Fabian. Absolutely. Yeah. It's a it's a good time. Yeah. I know for you, it's a little bit, late or early depending on how you look at the at the time, but it's, it's not raining. Let's call it like that. It's not raining in Vienna right now. Okay. That's that's good to know. And, we got folks joining from, you know, across the European region. So if it's raining where you are or not, we're excited to have you. We got a lot of people who joined so far. And, you know, we've given it just about two minutes, and so let's go ahead and kick off today's session. I know it's gonna be an exciting one. So today, we're gonna talk about really unlocking the contracts with Workday contract life cycle management and Workday contract intelligence. If you don't know what the difference is between contract life cycle management and contract intelligence, I can assure you that you will by the end of today's session. And so just to kick off, I do wanna share this product statement. We're gonna talk about a lot of capabilities within Workday today. There's a lot of exciting AI capabilities, off on offer. But as we may talk about some capabilities on our road map, please do just keep this product statement in mind. Excellent. Well, excited to be alongside Fabian today. My name is Memme. I'm Onwudiwe. I'm part of the founding team of Evisort, now Workday contract management and an AI evangelist here at Workday. And I'm alongside Fabian Jeckel. I'll let you, introduce yourself, Fabian. Thank you, Nena. Hi, everyone. I'm Fabian. I'm a solution consultant here at Workday. I joined the company over a decade ago. It's been quite a ride, and I'm extremely excited to have Nena today with me. It's, not every day that you got someone from a founding team, with you in a webinar and a Harvard lawyer as well. Right, Memme? So truly exciting. Yeah. Awesome. And yeah. No. Really excited for today's conversation. And like you said, you you know, Evisort was actually founded out of the Harvard Innovation Lab, with Harvard Law students and data scientists from MIT. And, you know, we were founded back in 2016, And, you know, we're gonna dive in today first with me just talking a little bit and introducing contract intelligence and contract life cycle management. But then after introducing and talking about it, really gonna dive into the meat of how these technologies actually work with Fabian taking us through a demo. And then from there, answering some questions. Although, if you have questions throughout the conversation, do feel free to put them into the q and a section of, you know, the presentation today. Now just kicking off and talking about contract intelligence and contract life cycle management. You know, like I said, you know, Evisort, which is the base of, Workday Contract Intelligence, was founded out of the Harvard Innovation Lab back in 2016, even before a lot of the generative AI really hit the scene. And from my founding, you know, something that we really believe is that contracts and other kinds of business documents, we're really the lifeblood of an organization. In reality, every time your organization purchases something, every time you sell something, every time you hire someone, every time you partner with someone, there's a document that is created in accordance with that. Right? And so when we think about contracts, we often like to say, you know, they're not just documents. They're actually really vital data about your organization. And a joke we have on our side is that contracts are tiny jails for data. Right? And so what we really wanna help you do from a contract intelligence perspective is get to the important data of these contracts and allow you to better use them to drive your business forward. Okay? Because if you're just approaching these contracts or invoices or other kinds of business documents, it's just legal documents, you're leaving a lot of value on the table from a data perspective. And especially now when everyone cares about AI and people might joke that data is the new oil. You know, this might be some of the most important data at your organization. And so if they're sitting under legal and you're not approaching them as valuable data, you're leaving a lot of value on the table. And so let's talk a little bit about how we approach contracts from an end to end contract life cycle management perspective and exactly what we mean when we say Workday contract intelligence and Workday contract management because we have two different approaches here. Right? And I'm gonna talk about them through three key capabilities, but then we'll dive into some more exciting capabilities as well. First things first, it's about connecting with your existing contract repositories. Right? You might have documents in SharePoint, in Box, in Google Drive, in Salesforce. You know, throughout your organization, you have documents and contracts in different repositories. And so the first step from our perspective is syncing and connecting with these different repositories to get access to these valuable documents. And something we can even show in the demo later on is that with Workday contract intelligence and Workday contract life cycle management, it is ridiculously easy to connect with these systems. Actually, we have natively built kind of syncs where, let's say, you might have documents in Box or in Google Drive, you're able to actually select Google Drive, and then you log in to Google Drive or you log in to Sherpa or you log in the box just as you would normally log in to them within our system. And then from there, you're just really selecting which of the folders in your existing folder structure that you're comfortable with have the key documents that you care about. And then those folders with those key documents are brought into the system, but they're mirrored. Meaning that you don't have to go and reinvent the wheel and kind of put everything into a folder and subfolder, you know, structures anew. You're able to leverage your existing folder structures. But what does it mean to actually connect and bring in those documents simply? What it enables is a deep level of analysis and visibility. And so we're able to and I think you saw in that last kind of slide we had, we're able to structure the unstructured data of your agreement. And so if these documents represent high levels of unstructured data, if you maybe have lots of payment terms, lots of governing laws, lots of execution dates and effective dates and data scattered throughout those different documents, once we pull them into the system, we're automatically analyzing those. And our system can analyze over 400,000 documents in under twenty four hours. Right? And so you can go from a mess of scanned PDFs and documents across multiple different folders to structured data and dashboards like you're seeing here incredibly quickly. And that's the power of the kind of artificial intelligence that we're using at the core of this technology. Now after we have this analysis step, you know, we still can do so much to accelerate the way that you do contracts more broadly. Right? And so, yes, those first two steps of connecting and analyzing gives you rapid access and visibility into your existing corpus of contracts into all of the agreements and business documents that your team might have signed or managed up until this point. But we also have tools from a contract life cycle management perspective that allows you to be able to generate new contracts, draft them, negotiate them, and then different folks on your team actually approve them all within one suite of tools. Right? And so we actually use artificial intelligence, which we'll show you, to help you negotiate these contracts. And so if you have playbooks, if you have a standard language, if you have things that you always agreed to and things that you never agreed to and things that you kind of always go back and edit when you're kind of negotiating these agreements, we can actually have AI go in there and do those negotiations for you, meaning that you're not copy pasting deleting the same things from contracts every time in these negotiation processes. But you can actually have AI streamline that process for you. So a lot of that tedious manual review can be very much automated. Now how do we actually package this? This is where you see the difference between Workday contract intelligence and Workday contract life cycle management. So these first two pieces, this connect and analyze, this is that Workday contract intelligence. This is basically being able to say, hey. Let me go to all of my existing documents and structure that unstructured data and be able to turn it into dashboards and other kinds of information. That's something that can be done incredibly rapidly. Right? But if you're saying, hey. Not only do I want visibility into my existing agreements, I also wanna be able to manage the entire life cycle of these documents and be able to draft new agreements based off my templates, review agreements from third party leveraging AI, and basically manage that entire process from the moment someone raises their hand and wants to request an agreement all the way through execution and signing in those agreement and we sync with tools like DocuSign, Adobe Sign, etcetera, that's gonna be Workday contract life cycle management, which includes everything that Workday contract intelligence has, but also adds that workflow negotiation all the way through execution piece. And so when we talk about Workday contract intelligence, even if your team maybe has an existing contract life cycle management system that's managing the creation, negotiation, and signing of agreements, you can still layer on top Workday contract intelligence to give you deeper visibility and data into your existing agreements. We've got customers globally who, you know, found it difficult to leave their CLM tool, but still wanted deeper AI and put, contract intelligence on top. But if you're saying that you want the full shebang, you want to have that building to your contracts, but you also want the native ability to generate, negotiate, approve, and basically do that full CLM process, that's when you'd be looking at that Workday full suite of tools. And so I hope that brings a little bit of clarity into the difference between those two different kinds of tools. You know, there's additional capabilities from an AI perspective that we offer on top, though. And so I what I just showed you is a very, very high level, and I know that even with the amount of time Fabian, Fabian's gonna be having in going through the demo today, It's really just gonna be scratching the surface on the immense capability of these tools. And so within the platform, and this isn't Workday, you know, you'll be able to dock with your documents. Right? Here you're seeing Ask AI, where you're able to actually converse with your agreements, ask it questions. This works in multiple different language. Even if you're working on an English language document, you can ask questions in French. You can ask questions in Spanish and German. Same if it the document is in other languages, and you might have questions in other languages. It's gonna meet you where you are from a language perspective. It'll also tell you, when you're talking with the document and getting answers, exactly where the document is getting those answers. And so it's not just gonna say something and maybe kind of hallucinate. It's gonna tell you what in the document it's basing its response based off of. And you're gonna be able to ask these questions across one document, across groups of documents, maybe if you have kind of, you know, a family structure, you know, amendments with it, or across all of your documents. So beyond Ask AI, we have even more powerful tools, tools like custom AI. And so Ask AI is more of a one off. Hey. I have a question about this document about about these groups of documents. But we always say, hey. You're tracking x amount of things in your documents. You almost always need x plus one. There's always that additional question, that additional data point that you wish you had about all of your documents. And so with our custom AI, you're able to actually track new data on demand and train new models with our incredibly powerful AI engine. And so even if you look at the example that we have on the screen here, you know, you're asking a new question. You're saying, hey, how much can we the vendor raise the price annually? And you can actually save this as a new model and now have a new dashboard where across all your documents, this new data point is being tracked. And Fabian is gonna be able to show that within the demo as well. But it's an incredibly powerful tool for you not just to track the data that is available out of the box, but because we serve customers in so many different industries, in so many different regions, we care about so many different things. And sometimes folks care about the same thing, but just approach it in different ways. You know, maybe you might want to know exactly how much of something is tracked. Maybe for you, the question might be, hey. We consider a contract risky if it has x elements. Maybe it's medium risk if it has y elements, and maybe it is low risk if it has z elements. You can actually give it that schema and then have the AI go across your documents and kind of do that risk score, a high, medium, low. And so, yes, it can pull out specific information. It can also summarize information, abstract information, but it's an incredibly powerful tool for you to track and deal with new queries and information requests across all of your documents. Next up, we also have different kinds of AI drafting tools. And so we talked about the fact that we have AI redlining within the platform where you're able to put, you know, what your stances are from a contractual negotiation playbook perspective. And then instead of having to go and redline each and every agreement, have the AI implement those rules for you. Right? And something that you'll see is it's not just gonna go in there and delete an entire paragraph and replace it with your paragraph because that's not how negotiations really work in real life. Right? It what you're typically doing is trying to delete as few words as possible to change the meaning towards what you're looking for. And that's exactly the kind of functionality that you'll see within the platform here. It's gonna be doing that fine tooth kind of red line negotiation, within your contracts. And so this is incredibly powerful, solution and AI tool within our technology as well. Excellent. And so just to really underline the point before, you know, passing it on to Fabian, you know, we have Workday Contract Intelligence, which is that full post signature capability. So for all of your existing documents and those new documents are assigned and added to your repository or into our repository, it's that ability to be able to pull in those documents. And even if it's, you know, not one of our out of the box, repository connections that we have, we do have a robust suite of APIs to be able to connect with your documents no matter what kind of tool they might be stored in today. But that Workday Contract Intelligence gives you that full visibility into your existing agreements, into your signed agreements. And then Workday Contract Lifecycle Management still does include all of the robust AI capabilities available within Workday Contract Intelligence, included in that Workday Contract Lifecycle Management side of the house. Excellent. And so, you know, just taking a step back and looking at, you know, some of the incredible outcomes driven by these technologies, you know, they allow you to surface risks within your documents. You know, you might say, hey. We only do, you know, governing law in these regions. You know, we only like to do a payment term of these days. We don't do, you know, early payment discounts, etcetera. But have you actually done a statistical analysis of all of your agreements and said this specific percentage of our agreements are in these regions from governing law. This percentage of our agreements have payment terms under thirty days. This allows you to actually statistically surface those risks, which, of course, goes hand in hand with spotting opportunities. Right? Spotting potential situations where you may be able to negotiate better terms from yourselves that may have gone hidden without that increased level of visibility into your agreements. And, of course, ultimately, it's all about tracking obligations. Right? Being able to track with high fidelity several different data points across your documents that if you're instead trying to track these things manually, maybe using Excel sheets, you know, would not otherwise be possible. And, you know, we've worked with so many different customers. You know, from a contract intelligence perspective, I told you we can analyze over 400,000 documents in under twenty four hours. I mean, that tool has an average day to the point of twenty one days, and which really allows you to get to value quickly. You know, Kelly Williams was able to, you know, basically within 30, have an intelligent repository of ten years of contracts. You know, NetApp analyzed 90,000 contracts, saving thousands of hours and $2,500,000. And you see Workday here as a, kind of customer story as well. You know, the the joke we kinda have here internally is, you know, Workday, of course, before acquiring Evisort, was one of our customers. I like to think our happiest customer because they actually bought the entire thing at the at the end of the day. But, know, with Workday's use case, they analyzed over 80,000 documents, with our kind of tool, and that was able to achieve over 35 35, a 100% return on investment. And, you you know, a fun interesting story is the fact that when Workday was acquiring Evisort, they actually used Evisort AI to do diligence on Evisort, which is kind of not every day that you see that kind of, kind of circular, capability. But, you know, this is, of course, you know, just one of the many different, you know, large companies, you know, leveraging our technology, but just some kind of fun statistics, to share here. But, you know, at the end of the day, what it's really all about is stop reading contracts, and instead, you need to start driving outcomes. Because there's actually is it's a little bit ironic, but when you're leveraging contract intelligence tools, you're gonna be reading way less contracts, but you're actually gonna know way more about all of your agreements than you ever could by approaching these with manual solutions where you're kind of tediously reading every line of every document and maybe keying in that information into Excel sheets, even into other kinds of tools that might require that level of, manual entry. And so I know I've talked a good amount, probably far too much. You guys are probably bored of my voice by now. And so, I'm excited to pass it on to Fabian, who's gonna bring some of my words to life and show you a little bit of the platform and how it works. And so I'll go ahead and stop sharing my screen and pass it over to you, Fabian. Miss Memme, I could listen to you two, four hours, so I hope I can bring as much of the stuff you told us to life. Let me quickly share the screen and give a shout whenever you see something because we had a couple of hiccups before. So I get the message. I'm sharing my screen. Can you see it, ma'am? I am not seeing it right now. You're not seeing it right now? Okay. What would be an AI demo without a proper glitch? So let's do another rep here and share this one here. Okay. I am seeing your screen now. Excellent. Seeing the screen now. Brilliant. Alright. Cool. Then let's go ahead. So as many told us, there are a couple of stages within the Evisort platform, the three pillars, right, of first ingesting documents into Evisort, the contract intelligence. And that can really happen either through the out of the box integrations. And as I told you, it's really a plug and play thing. It's as easy as this, and you see it here in the repository. Got a couple of examples in here from the usual suspects, whether that's Box, Google Drive, or SharePoint. That's really about syncing up those structures and then having those live impacts in every sort because we know, well, it's great to have only one place for all your documents but the reality is what we've seen so far is customers and prospective customers have loads and loads of places where they have documents. So Evisort is is an easy way of ingesting all those sources, bringing them in, and analyzing them. Let's move into one example folders in here. And we've got a couple of categories in here, right, from either customers or industries. And here, let's imagine we acquired a company. So that's the avatar example, that kind of circular relationship that's only possible in AI. Right? You have a lot of circles. And we see a couple of documents in here. 67 documents in total are in this folder. We see all those PDFs in here, and we see the metadata. Now what we hear from customers all over again as well, it's all nice, but if we really want the classification, the metadata on a document, This means for us either some highly paid lawyers or a bunch of interns gotta sit down, take a look at the documents, and key that in. Right? Whether that's, as Memme told, an Excel spreadsheet or something more advanced. It's really hard to get that out. And you see there are the usual suspects. Right? What's the title? What's the contract type? What are the counterparties? Etcetera. But, of course, you can have way more sophisticated data points getting mined from each and every document in here. Let's take a look at this. Right? You see two sections here. We'll take a look at two of both of them. Got the fields, which just imagine that that's the data, the data points that you want to know about the document. And Evisort delivers 30 plus of those fields out of the box. Really? That's the magic that Abhisar delivers. Right? You got those AI scientists and people there really getting and nailing it down and delivering a high quality of those responses because the last thing that you want is 400,000 documents in twenty four hours with garbage data output. Right? That's why and there are high quality levels around those 30 plus fields. And we see, well, title, counterparties, language, etcetera. But then mixed with that, you got fields and information from operational information, legal information, liability caps, GDPR status, stuff in different languages like, that's closer to my heart. Right? For all our Spanish friends on the call. So you are capable of tailoring those fields and that model towards your needs. And that's why every sort of work we are really a match made in heaven because everyone on the call who is familiar with the core concepts of the Workday platform knows Workday delivers an out of the box object model. You can compare that basically to the out of the box fields within every sort, those 30 plus fields that get pre delivered. But like on the Workday platform where you can also create as many custom objects or calculated fields as you like to really tailor it to your needs, you can create that custom model, that custom AI with an ABBYY sort where you can pull out anything that you want to know and make it a known field and train it there. That's a bit of the theory. Right? Let's let's look at this in practice. How does it look like? Because this is now something that's already in here. Let's go in and do a live upload, basically. How does it work in practice? Go in here. We go in into our folders, and we have our fully scanned contract in here. Of course, you can still attach, metadata the moment you do a manual upload. Remember, that would come in through an integration, through a synchronization. We upload the document. In a matter of seconds, it's gonna tell us it's it's been processed. It's available. All of the metadata has been mined. We go in there. First, we see the the contract over here. It's really what the name says it is. Right? It's a poorly scanned contract. We got manual stuff on top sitting here. I can still mark all of that. Right? So Evisort is leveraging both. It's leveraging the best in class models that are on the market and also their very own trained capacities. So we are able to read the entire contract. That's not a pixel perfect PDF, but it's really a crappy crappy scan in here, and it reads all of that. And on top of that, fields on the right that you see here, the metadata has been really extracted fast, consistently, clean, and reliable. So everything in here is based on the references. I can jump in here, and it's gonna point me towards that. Right? Checked out. It's a twelve month period, so it's a one year renewal term. So I can trust really the results of the eye that it's presenting here to me. It's not something that's been dreamed upwards hallucinating. I can really go back to the respective reference. That's that's the one point. And then we got SKI, which is well, if you upload a a contract to your favorite LLM of choice, whether that's an OpenAI or a cloud model, you can chat with it. Right? We know all of that. But the good well, the challenging thing is you probably shouldn't do that. You don't know where that data is landing, and that's why we have the same comparable capacities sitting within Evisort without, having all the trouble of where does my data end up. Right? So this is your secure environment that sits in a in an isolated space. Everything that's in here doesn't train anything anywhere else in someone else's model. And we can go in here and chat now with the document, do the classic. So, what is this document all about? Please give me a one sentence summary. It's now gonna do the charts. It's gonna check the document. It's generating a response. And just like with the metadata, it's gonna give me a couple of references back to the document. So whenever it's it's coming up with facts and figures, it will link it back to the respective components and pieces within the contract. Now I might now decide, well, this one sentence summary of a document, this is so brilliant. Right? This needs to be part of the entire metadata structure. I want to see that, not only for this contract, I want to see it on all contracts, right, on the tabular cells that we've seen before. I want to have it over there. Now just with a click of a button, I can take this prompt, basically, and make it into a very own model. This is really not about programming or coding or opening up a ticket to get an AI specialist, train it, and then implement it probably a week later into every thought. This is really about the the tech savvy end user driving all of that on their own. Right? You can do that on your own. It gives you a little bit of guidance in here what are the four steps that we're gonna do here. The prompt, the evaluation run, improving it, and then publishing it to every sort to everyone. But it's very straightforward, very easy. It just pulls my prompt. I can now sort it down. Right? Does it need to apply to all documents? And then go ahead and and train it. And in that way, you can really have that that core concept of work there, right, driving change, driving, adaptions on a constant basis across the platform in every sort as well. Right? So it's it's not something rigid, not something that needs to be done by a programmer or a specialist. Right? You can do that on your own. You can adjust it and really make it on your own and really understand what is driving the model and the results behind it. Alright. So that was the, the second pillar, how to mine data out of that after you connect it into Evisort. Of course, you don't just do that on one document. You can do that or you will do that across your entire document basis. And as you go along and add more and more data points, you want to make sense out of them again, extract them, and every sort provides a very easy to understand and highly flexible environment for that. So we are in a dashboard area right now. We have different types of dashboards in here. This is, let's put it plainly, just about documents. Right? So it's looking at basically everything here. There are no filters, but it's giving me a perfect overview of my entire contract base here. So I see what kind of contract types are in here. Do we add a lot of proposals? Do we have agreements, professional services agreements, how many NDAs, etcetera? What's been executed? What are the languages behind that? What's the governing law? So we see that's a little bit of demo data from our US friends. Right? So there's a lot of, US governing law in here. But as I go along and filter down let's go for some English, governing law countries or governing contracts in here. It's a dynamic dashboard. So at the moment I filter something down, the rest of the dashboard adjusts. And if I go to the bottom of it, I can always go back to the respective documents or contracts that sit behind those numbers. I didn't really, have a very easy way of maneuvering around and getting an understanding of that. That, of course, can be governed towards any sort of flavor. Right? Whether that's just to get an understanding of your document base, just like now, or for the respective domains. Right? So Memme is a proud Harvard man, Harvard lawyer, and it's it's been built by lawyers. And a lot of lawyers are leveraging contract intelligence and 100 lifecycle management. But Defaqto, you can give access to any sort of domain in there, and they can pull out information about their respective documents that they need. Right? If you look at someone in in finance for pricing, for example, they want to know about what what's what's in that contract in terms of products, in terms of services. What's the pricing behind those, different components? What are base pricings? What are payment terms? Are the payment terms favorable or not? Maybe if we want to adjust it in the next negotiation or address it right now. And imagine you you are a CFO coming in. You want to get an understanding of who's my profitable customer. You will see that in core Workday or in Adaptive. And then if you see, well, got some unwanted, things going on over here. How do I get out of that contract? You can easily drill in and find ways of of doing really actions, and that broadens that plan, execute, analyze cycle within the Verbit platform. Yeah. And, you know, that's that's so important, Fabian. And we even had a question come in asking about, you know, drilling down from the dashboard this specific contract. And as you said, you know, as you're clicking things in the dashboard, it's then narrowing the world of contracts you're looking at. And as you're doing that, as you show in the bottom, when you scroll down, they have actually a list of all the documents there. So let's say you identify a risky payment term. Right? You can click it and just look at those hundreds of the risky, and then maybe from there, you can also say, hey. Which ones are coming up for the renewal next fiscal year? Come down to five or so quest contracts. And then that list of contracts you have at the bottom, you're able just to kind of click and go into those. You know, in this case, you've narrowed it down from a couple thousand documents down to just three, and you can jump directly into those affected contracts. And so excellent. Yeah. Correct. So that's the performance and flexibility that you got here. Right? And that's really what's at the core of of contract intelligence. Right? The first two pillars, connecting documents and analyzing them, that's contract intelligence. Now we got customers who are then going all the way. Right? Not just getting an understanding and insights of their documents and contract based, but really who want to do the CLM processes and workflows within Evisort. So who is doing what, who is approving what are intake forms, etcetera. And for that, we have our very own workflow area. And this is a ticket based environment. Right? So we are looking at this right now as someone from legal. So we got a lot of stuff going on here, NDAs, vendor services agreements, etcetera. And, those workflows, the way the intake forms look like, that's completely up to you. Right? So we'll see one example right now, very straightforward one. We'll do an NDA. But, it can be anything. Right? Any sort of contractual agreement that you're looking for, you can build that with the workflow builder and really determine what's the layout, what are the rules, what are the conditions, who's gonna prove it, what are the thresholds, etcetera. That can all be incorporated and has the same flexibility that you would expect from any Workday product. So we'll go in and, do an NDA. First, it's well, it's is it on our paper? Is it on the counterparties' paper? Let's keep it easy, and let's say that's from our template. Who's the responsible partner? So we're doing that internally. What's the effective date? Let's be ambitious and say that's effective today. And then we got a couple of prepopulated fields. So you can incorporate different types of field types, drag and drops, lists, yes, no, something that that can trigger a further review, etcetera. At the at the at the bottom, you got, your signatory information prepopulated. I don't know if the joke works in The US as well, but if we say in Germany, a is a good one, everybody needs a I don't know who that makes and The US as well. But that's where I land with the legal folks. Right? Alright. So we we make this ticket. And the moment we create the ticket, every sort of is doing two things. It's checking basically the intake form and determines which way the process is gonna flow now, who's responsible, what kind of things needs to be done in the back, thresholds, who needs to approve. And it's gonna create my NDA, my document. So that's created now. And as it is on our paper and we didn't incorporate any changes in here, it's a pretty straightforward process. Evisort tells me, well, just give it a cursory review and then send it out to the client. So the moment I approve that and confirm it, I can send it out and move it to signature stage. And that's the point where we integrate seamless with the likes of Adobe Signature and DocuSign. And every sort is then gonna patch the signed document, store it, and do the whole analytics thing that we've seen before. Now that's the easy way. Right? We created a standard NDA on our own paper. There is no complex or very little complexity in that. That. Let's take a look at an example that is a little bit more advanced, probably. We do have a vendor services agreement here, and we are looking at it really from the the redlining perspective in here. So we'll take a look at all the tools, and all the bells and whistles that we have available up here. And so first, it's gonna guide me through the tasks here as well, and they are, in this example, a little bit more expensive. Right? We got a legal review that has been triggered. We got a compliance review and a finance review, all routing through the organization, all different people for sure. Right? Evisort can cover quite complex, user and security profiles, so that's not a not a concern. I have my comments in here. Right? So at the moment, you are working in a team with colleagues and you tag someone and say, well, hey, Luca. Take a look at this. Luca is gonna get notification, and you can jump straight to the to the, to the contract. We can always link back to the intake form. Now that's a that's a funny side note that we found or I found at least in German speaking countries is there there is sometimes a huge disconnect to the initial intake form and the actual redlining that you're doing right now. Right? So you gotta pull out a couple of emails and track them, etcetera. So in every sort of course, that's that's quite smooth. I just take a look at the intake form if I'm further down, process and know what the initial request was and and what the current means of work is. And and then, of course, I have, all my document details next to the task. I got the clause. And and that's really I resort looking at the entire contract or entire document and then sorting it by the respective clauses it identifies. So let's take, for example, this indemnification clause here. We didn't take that manually. Evisort did this on on its very own. And then when I go in here, I can check my AI drafting tools. I can say, let's do an automated redlining in here. So, let's take indemnification clause to a library. Can sit in the back of that, so you might have different variations of your indemnification clause. In our scenario, we got four. Basically, you walk away, so nothing's gonna happen after that probably with that draft. But then we got three, different kinds of acceptable or agreeable, clauses in here, preferred, preferred, and fallback. And, of course, as Memme said, you could go in here and just override the entire thing and say, oh, no. We won't accept this clause. Let's take our, clause from the library and just insert it. And then I said, well, reality is more like you. You find a common ground. And, you do some rephrasing and inserting. And that's exactly what what we do next. Right? We we tell the model what to do. It's gonna take a look at our clause library at this specific clause, and it's gonna generate some common ground based on what's in the draft and what's in the library. It comes up with this proposal right now. And we can say, well, let's either exact this or generate more or let's check different versions of that. And that's a nice and easy way of working through that. Clause generator is really about, well, I don't know if I have something either sitting on my library or it's something completely new that needs to be dreamed up, and I instruct the model instruct the LLM to really come up with a new clause and do basically the same with it. So that way you can you can redline. Now we take or we can take that step further. Right? And not just screen that manually, your clauses and your contracts, and then decide whether that's risky or not. You've seen Ask AI before, and that's really about, your language approach of how to deal with contracts. And as we know, are quite powerful. And if we take not just one question but a bunch of questions, that's basically your legal playbook. Right? You have a checklist of questions of risk scores, etcetera, of terms that you want to accept or not. And that's basically text that can be compiled in a question group and, hence, a legal playbook. There are a couple of examples in here. We see that's those questions or aspects and factors, they're all part of that legal playbook. I can now decide, do I want to run the entire playbook or do I want just to run a couple of questions? But the moment I hit this, it's gonna fire up my entire playbook against this particular document, and it's gonna do the exactly the same as you would expect it from the previous examples. Right? It's gonna check the document. It's gonna give me back some references, and then I can decide what to do with it. Do I want to auto redline it? Do I need to, create a new clause, or do I want to pull in just something straight from the library? So and as we, wait for the final results, we got two out of five creditors. You see there is stuff that is either problematic or it's not really up to our, not really up to our rules and guidance. So there is stuff in there that we could now go on and work with it. Alright. So this is this is usually something that really changes the core of the practitioner's, activities in your legal department. And for some, this is maybe exactly what you're looking for, and for some, it might be a little bit of change. Right? And, the good thing is now you can go basically with the flow with an ABBYY sort and either, start with your today's work, ways of work, basically checking all the agreements and contracts that you have already with, the customer. So you can go back to your contract base and analyze it and say, well, I'm looking for a specific clause type, indemnification, and I want that for a specific contract type or a specific counterparty. And then really let, the library do its job. Right? I can sort it by effective sale. For example, what was the last agreed, clause I had with a specific customer on a in a specific contract type, and then pull it out. You can look at the contract. You can look at the exact clauses. It's gonna show that here to me. I can just copy paste that into my redlining process. That's probably pretty close to the traditional way of working. And the more you feel comfortable with the AI giving you recommendations, you can work with things like automated red linings or entire legal playbooks. Now this way, of course, you can speed up the entire legal operations, in your organization. And the good thing is now, Evisort also helps you keep track of that because what we hear sometimes is, well, AI changes a lot, but I can't really quantify it. I can't really measure the benefits of that. And, with that, it's it's probably harder to get into buy in, or additional funding, for initiatives. The good thing is now about this reporting framework with the Evisort, it's not just looking at the insights and all the metadata that you can pull out. It's also looking at the entire workflow area so you can really go and measure the performance of your legal operations. So what is the cycle time before and after, what's ticketing ages, what are bottlenecks, who's holding up processes, then either go in and optimize your workflow, so do changes and twist this over there, or change an entire approach. So if you see some adoption challenges in here, you can drive free the the change aspects of that. And driving the change is also easy in Evisort. Right? You got your entire community. You got your Evisort training academy in here. So it's really it's really easy to drive the change and with Evisort. Alright. So we got the three pillars. We got the the integration, the ingestion of documents. We got the analytics components, basically getting and mining information out from any sort of contracts or documents that you store within Evisort. And we got a glimpse into the acceleration pillar and component of Evisort, basically creating new contracts, creating new documents in there. And as you've seen, each and every pillar is, AI built at its very core. Right? It's not attached on the top. It's really sitting at the core of of Evisort in the Evisort platform. Hence, it's driving those massive results, as Manny described, right, those those gigantic numbers. And not just, in law, but for any kind of domain within an organization that is working with documents. And basically, everyone is working with documents, or contracts in any sort of form. So it can have quite a significant impact on your organization. Alright. Awesome. Do we have any so far? I mean, there's been a lot of questions. A lot of questions have been answered. I mean, I would just say, one, that was an excellent demonstration of capability. But if folks really wanna dive deeper, I would definitely reach out to your account team to get a deeper kind of demonstration just because there's so much meaty capability there. I mean, of everything he showed, it's hard to overstate just how configurable things are, just how you can can really create custom workflows that work in the way that your organizations actually operate, how you can create new models that really help you track the specific information that might only be unique to either your industry or your own company. And, frankly, as you get deeper into the evaluation process of the tools, you know, we do have some, you know, capabilities to even do, you know, a level of kind of, you know, proof of concept where you put your own documents into the, you know, platform if if you're actually kind of at that level of evaluation where I think those dashboards look beautiful, but they always look even more beautiful when it's your own data. You know, once you you actually realize, oh, I actually thought that we had all of our governing laws in just these two regions. But after doing that statistical analysis and putting, you know, a few thousand documents in, I'm realizing that we have more contracts maybe, you know, with a governing law in France than we expected. And maybe, you know, as we're building out our playbooks moving forward, you know, we should take that into account, how things are actually going. And so thank you so much for that demonstration, Fabian. You know, we only have a few minutes left here. As we're closing out, well, one, if you like AI and you like contracts and you like my voice, I do host the podcast on AI and contracts. We release, episodes, every month. And so if you're interested in, listening to the meeting of the minds, podcast that I host alongside Hal Marcus, a former general counsel who, you know, works here at Evisort as well. Please do use the QR code on the screen to subscribe to subscribe to us either on YouTube or Apple Music or Spotify. We bring in thought leaders, academics, you know, folks from procurement, from legal, from HR, from across the spectrum. So many folks deal with contracts and have interest in leveraging AI to drive things forward. And so, you know, please do, you know, sign up for that if you have, interest. And then also, you know, if you're based in Europe, the biggest Workday party of the year is coming, you know, to the continent, just next month. And so on November, in Barcelona, Spain will be EMEA Rising, where there's gonna be several sessions talking about contract intelligence, contract life cycle management, you know, capabilities, that are coming up and exciting on the road map capabilities that are existing that we maybe didn't have time to dive into today. And so if you are going if you are interested in attending or learning more and seeing maybe if even folks from your team, can attend that session, in that event, please do use the QR code here. We just had the rising event in, you know, The United States. It was really, really incredible. You know, even if you think you know what's going on at Workday, chances are you don't. We've made some very exciting acquisitions even beyond Evisort, like Paradox, like Sana, like FlowWise, which is really changing the kind of AI and agentic AI landscape of capabilities within Workday. And so, really highly do suggest that you at least find out more about this exciting event in Barcelona either by, you know, scanning the QR code or just reaching out to your respective, you know, account teams to learn some more information about it. And then I hope that you can also join us next time. I mean, you know, we do so many different kind of looking forward with Workday sessions and webinars where we dive into different capabilities, you know, throughout, the Workday ecosystem. October 21, we have one that's the road map to intelligent financial planning, talking about Flix's journey to better business partnering with Workday adaptive planning. If you follow this QR code, you're gonna see the full gamut of different kinds of sessions that we have upcoming, and there's so much to learn about the Workday technology, ecosystem. But for the last couple minutes, we do wanna open up time for any additional question that know our team off stage has been doing a great job of answering folks' questions as they have arise throughout today's session, but did want to leave the last couple minutes here just in case folks have any last questions, you know, before we go. And so don't be shy. Feel free to go to the q and a. And if it's a big question that you're thinking, may may, Fabian, there's no way you guys have enough time to answer this massive question that I have. You know, our account teams are always open and happy to, you know, be reached out to and point you in the right directions, you know, whether it is you have questions about Workday contract life cycle management, about Workday contract intelligence, about something maybe in between the two, whether or not you need one or the other based off your existing technology landscape. Or, you know you know, we can, of course, reach out to our account team to if you have questions about any other part of the suite of Workday technologies or even our partner suite of technologies because there's so many different kind of, capabilities available, you know, through the, Workday marketplace as well. And so I'm seeing no new questions coming in, which is hopefully a testament to the comprehensive nature of today's conversation. I see actually answering a question. We're currently using WSS as a contract repository. How could we alter to this solution? That's an incredibly important question. Thank you for asking that. And so, actually, on a pretty near term road map, we're actually looking to, you know, connect those two kinds of systems, and so and create kind of a comprehensive experience between, WSS as well as, you know, Workday contract life cycle management. And so I'd say that, you know, I'm, early next year, definitely watch this space. Of course, we're still within the first year of the acquisition of, Evisort, and so that connection point has not been fully built out, but it is something that is coming, quite soon. And so I'd say reach out to the account team, for timing and next steps on that. Thank you so much for your time, everyone. Have a great day. Thanks, and bye.