Name: Agentic Agreements: The Next Evolution of Contract Intelligence
Uploaded: 2026-08-13T18:16:24.877Z
Duration: 58 min 44 s
Description: Agentic Agreements: The Next Evolution of Contract Intelligence

Transcript for "Agentic Agreements: The Next Evolution of Contract Intelligence": Welcome, everyone. Thanks so much for joining us for Agenda Agreements, the next evolution of contract intelligence. Really glad that you've joined us today. I hope you're gonna find the next hour really valuable. Couple of housekeeping things to kick things off. We are recording today's webinar. We will make it available on demand after the webinar is concluded with the same length that you use to register. So if there's anyone that you wanna share this with in your organization, I hope you will, then you'll be able to do that easily. We will be talking about some upcoming product enhancements, some road map plans, etcetera because we are a public company. This is our safe harbor slide. Always be aware of that. And with that, let's go ahead and kick things off. I'm gonna invite Tommy Sherman up to the stage and introduce myself as well. My name is Hal Marcus. I'm a principal in product marketing here at Workday. I came over to Workday with the acquisition of Evisort in October 2024. I'm a California lawyer, former general counsel. I've negotiated hundreds of contracts, and I've been in the legal technology space for more years now than I care to count working on, technologies that hopefully have a real impact on how legal interacts with all the other departments of the organization. And that's what got me into AI use cases about fourteen years ago for legal and more recently in the last seven or eight years into agreement technology very specifically. So glad to have Tom Sherman here with me today, a solutions consultant. Tom, I'll leave it to you to say hi and introduce yourself. Thanks, Al. Hi, everybody. My name is Tommy Sherman. I'm out of Workday's Boston office, and I've been here for three years now. And I am definitely a technology nerd. I've been following AI for over a decade. And when I had the opportunity to jump into the Workday CLM team and kind of see where AI was going, I knew I had to get on board that ship. It's a very exciting technology, a very exciting solution, and I'm happy to share it with you. Thanks, Tommy. I look forward to pulling you back on stage in a little bit, but first, everyone's gonna have to listen to me for a while and look through a whole lot of slides. We will get through this quickly though and set up the demo that we really wanna get you to. But wanna lay a little bit of a foundation for all the people that are attending. You know, what is this ultimately all about? And it's this, and this was the the genesis of Evisort, which became, you know, Workday CLM. Contracts are the lifeblood of business. Pretty much everything of real significance that happens in an organization when you buy something, sell something, or hire someone. There's some kind of agreement, some kind of documentation associated with that. Knowing what's in those documents is really critically important. But historically, CLMs had treated those contracts as documents to be signed, documents to get through a workflow process. And as important as that is, there's a lot more to it. Those documents are data and those critical data points, they help you save money. They help you grow revenue. They help you make strategic decisions about just about anything you need to do within an organization. So how do you get to that information? Well, historically, it's been pretty hard. All the different offices have the kinds of contracts that they care about and lots of information in those agreements that they need access to to do their jobs well. Historically, they've had to go through legal to try to find access to it, and legal often can't get to that information. In fact, when we get engaged by legal teams that are looking to change how they operate, quite often the first goal of what they're trying to achieve is, where's my stuff? Where are all these agreements? They're scattered across the organization and not in a centralized intelligent repository. And that was what Evisort from the beginning was designed to resolve. It's an AI native solution to tell you what's in your agreements. So before we kick in, just take one quick moment, think to yourselves because we have people, attending today with a variety of roles, and I'll talk more about that in a minute. But what would you like to know about the contracts that matter to you in how you and your department do what you do? Imagine if you could really know anything about those agreements either in advance or on the fly as that issue arises. So with that in your head, let's launch into what it is that we're doing to really advance that cause. And I wanna do a little more foundational work here because the first thing we need to know is, well, what's going on out in the industry? What is that presignature workflow process? Who owns it? Who owns this the the document post signature as well? This is a really critical question for, organizations where often they have different departments that are working on these things. So we started last year a benchmark survey. Last year, we asked 1,250 professionals, both legal and nonlegal. It was something like four to one, I believe, of nonlegal to legal. So probably a pretty good, you know, balance of what you would see in an organization. We asked them across The US about their contracting processes. We published that as the contract intelligence index report and, got a great response in this last year. So we decided to take this to another level this year. And instead of twelve fifty, we expanded this to nearly 7,000 employees, and we took it global across 10 countries. The whole methodology is spelled out in this document, which we'll make available to you. In fact, I believe we have it already in the docs tab. If you go to the docs tab in Goldcast right now, you'll see a link to this report. Now I'm not gonna spend much time on this, but I wanna call out one key really sort of central statistic that we found really interesting. And it has to do with contract ownership confusion. Where does that process live? Who owns those documents from inception to negotiation to enforcement and all of it? And here's what we found in 2025 when we asked, you know, with a few more words than this. But when we asked pretty straightforwardly who owns the contract? What we got back was 76%, three out of four of the respondents, both legal and nonlegal, they were not far apart, said that either no one or only up to a few people in their organization really have a decent understanding of who owns stores and manages their contracts. And we thought that was pretty striking that such a large percentage say this really is not clear in our organization. And we were curious what would happen firstly a year later because they've had another year to implement AI technology and other tools. And we took a global, like I said, across 10 countries, wanted to see what the response would be. So drum roll, please, a year later, and we're at 77%. So we you can't make this stuff up. I mean, there really was no appreciable difference year to year or going more global. There were some discrepancies among countries, and they were kind of interesting about how they store agreements, what kind of formats they're in, and all of that's in the report. But using this as a foundation, I just wanna lay the the seeds here that as you think about how you work with the contracts and your processes in your organization, think about how the tools that we're gonna talk about here could impact that. We'll give you some thoughts on that front as we go. Alright. Onto the technology. Look. Workday delivers industry leading AI for contracts, and that is because in October 2024, Workday acquired Evisort, which had been founded by some Harvard Law School students and their friend over at MIT about ten years ago when they saw the potential for an AI native solution to bring intelligence to contracts. It It was kind of a pioneering approach because historically, CLMs, again, were much more about that workflow process and much less about what can you do with this repository of contracts that you would now have accumulated and saved. They were somewhat searchable. There was some metadata that tended to be as about as far as it went. So introducing contract intelligence was really meaningful. Now how did we become part of Workday? That's because Workday was a customer. For three years before our acquisition, Workday Legal had been using Evisort for all of their customer contracts to manage this vast volume of customer agreements. And with over 11,000 customers across the globe, that's a pretty big volume of contracts. So, they brought all of those contracts together so they could have intelligent analysis of all those agreements. They achieved quarter after quarter a 37 x return on investment. This was again before we became acquired. This is not, you know, something where we stack the deck. And this ROI was achieved just in terms of cost savings. This is not about the value of having deeper analysis of their contracts, knowing what's in them, being able to make strategic decisions, etcetera. This was just based on every inquiry that came into legal and a fairly conservative estimate of what that would have cost to apply counsel to do that analysis that they no longer needed to do. A year later, Workday Global Procurement did the same. Saw what legal had done and decided to apply it to their spend contracts to all of their supplier agreements. They brought in over a 100,000 agreements into the system, and they achieved a 77 x ROI, again, just in those cost savings, not from, the advanced ability to know what's in those agreements. So anyone that thinks that these are costly and that they don't pay for themselves, they're missing the boat, and we have the evidence to show that. Alright. What exactly is it that this technology does? Well, Workday CLM, which encompasses all of the capabilities of Evisort, does essentially three things. It connects to your contract repositories wherever they are, whatever format these contracts are in across your organization. You it it'll bring many of them in through productized integration where we do a two way sync. So we're always keeping those repositories current with many of these solutions. In some cases, like Salesforce or SAP Ariba might be a one way sync where we're ingesting the contracts, on a onetime and ongoing basis. So that's for customer contracts with Salesforce, you know, for those that are using Ariba, as a procurement solution that is bringing in all the supplier agreements. And then just about anywhere else that you have those agreements, we can bring them in either through an upload process, combination, or, through API. Now when we bring all those contracts in, we're creating an intelligent repository of information. We're turning them into searchable text with our own advanced OCR and AI process. And by combining the AI and the OCR, we can deal with things like bad scans. We can deal with handwriting data that's in tables. No one does that perfectly, but we do it quite well. And we're able to do that because, again, the AI is augmenting what the OCR can actually process. So the goal here is to create a really solid, reliable repository of data. We recognize over 250 contract types. We recognize a 150 languages and can identify what those languages are. It doesn't mean we translate them all. It means we can know what language they are in. We can recognize core status, whether they're signed or unsigned, and analyze about 45 core common terms that we can extract and identify across all of those agreements. And we can do that up to 450,000 contracts a day. High scale, very fast. Now by virtue of having brought all the information in, we can then apply more advanced AI and give you a whole range of analytical tools so that you can know everything about your contracts and the related documents, SOWs, POs, invoices, policy documents, anything that goes along with those agreements and helps explain how they work and what's in them. And that means dashboards, full text search, and, advanced capabilities to ask questions. More on that in a minute. Now we also, over time, have advanced the product and expanded it to include all of those CLM capabilities that I mentioned earlier. This whole idea of everything from inception of a contract, ticketing, the request, intake, populating, making choices about how you initiate the contract, how you negotiate and redline the contract, how you get it signed, and then into storage and then notifications about renewals. Basically, everything for that whole life cycle. That's all in here now as well. Now we sell the product in two ways. If you get Workday CLM, which the vast majority of our customers do, you get all that post signature contract analysis, which includes what we call our contract intelligence agent, a series of agentic skills that are really powerful for knowing what's in your agreements. If you get the full CLM package, you also get the pre signature analysis and those n to n contract workflows that I just mentioned. And as part of that, you get our contract negotiation agent, which is actually our primary topic for today's webinar, and you'll be seeing it shortly. I just wanna call out, though, that if you are using an existing CLM or you have other processes you use for your workflows, and what you're looking for is very quickly, to be able to learn what's in potentially tens or hundreds of thousands agreements that you've accumulated across your organization. That may be in a pre merger or even post merger context. That may be because of a new strategic initiative. It may be because of a regulatory need or something going on in the market like tariff analysis right now is a big one. A few years ago, a lot of it was pandemic analysis. And what are the implications of that? When these projects emerge, we can very quickly implement contract intelligence as a lighter version of our Workday CLM product. And that can be implemented quickly so that you can get that full in-depth analysis. Alright. We're gonna take a quick look at the post signature contract intelligence, and then we're gonna pivot to the real focus for today, which is the presignature contract capabilities. But it's important to understand what you can do with all of your contracts to understand what then you can apply to those presignature agreements. So very quickly, let me call out some of those agentic skills that we think are most impactful. And you'll see this, when Tommy does his demo in a little bit. But we introduced about three years ago into the product something that's now becoming something we're very comfortable with in almost every context. Right? Being able to use a conversational experience to get things done. In our case, that means this Ask AI box that you can bring up at any time in the platform, and it will answer questions across one, all, or any subset of your contracts. Very flexible about what you can apply it to. It's also very flexible about what you can ask it to do. It can do calculations. It can do classifications. It can summarize terms even from different parts of the contract. Quite often it's used for pretty straightforward questions where people just need quick information. So when you do that it'll deliver an answer to you in good clear plain language that is always linked not only to the documents that give you the answer but specifically to the parts of those documents that give you the answer. So following any of those links is a great way to validate anything that appears here. That said, this is already a closed network. It is not going out to the Internet. It is not touching on to any external LLMs that would learn or benefit from this information, and it is not delivering information back that is beyond the scope of what the user can access. So it carefully, follows access controls for the user. No one can circumvent anything with this and find out about, you know, the CEO's stock grants, which would probably also be in your repository just because they ask a question about it. Tightly controlled, very reliable, also uses retrieval augmented generation, which means it validates answers against that data store that I talked about earlier from when we ingested all of your contracts. It won't deliver information about, like, what's enforceable, won't give legal advice, won't look out for industry benchmarks that you might find in an Internet website, which could be highly unreliable. So it creates a very tight, reliable way to have anyone across your organization ask questions. And this doesn't have to stay in legal. And in fact, the way we price and deploy the product makes it very easy to share this across teams. Okay. What about when you have a question that you know is a really good one and you don't wanna have to ask it over and over again? You just wanna know that information and make it a standard data point, just like all the core ones that we extract when we ingest, like counterparties and total contract value and governing law and all those types of things. What if you wanna have, for example, a summary of rebates, volume discounts, early payment discounts, and you want all that information in one sentence, and you want it in plain language, and you want it for every relevant contract. Well, that's what you can do with custom AI models. You can turn any of your questions into your own model that'll do just about anything you wanted to. These are almost like creating your own little agents. You know? These will run continuously. They make nuance judgment calls, and they will create new structured data points for you however you need them. Now sometimes those answers will be things that display beautifully in dashboards like you saw here. Here's another example. How quickly would we need to notify customers of a data breach? Well, here it's extracting how that appears in the contract. And as long as that's a small bit of text or a number of days or something like that, that's gonna display in your dashboards really elegantly in a chart. These dashboards, you can have as many of them in the product as you like. You create them and customize them using check boxes and click and drag. Very simple to use. You can make them as specific as you want them to be, and then you have all this information at your fingertips. But what about the example I gave a moment ago where you wanna know about, like, a rebate, volume discount, early payment discount? You want it all in one quick simple sentence. You wanna have that as a data point for every relevant contract. Well, it's not gonna display very well in a dashboard because that's text. That's gonna display instead in this document display, which is a table display of all of your metadata organized however you would like it to be for all of the contracts that you're looking at in any given moment. This can be exported as a CSV or an XLS file. It can be sent over to just about any other solution that you'd like. So by doing this, you're creating a structured data point that travels with the contract, and then you could take advantage of anywhere. By the way, these custom AI models, you don't have to create them all yourself. We've actually given you a head start. In our model library that we introduced last year, we have over a 120 prebuilt models that do a range of very specific things for certain kinds of agreements in industries. So there's a lot to choose from there. They're pretrained. You can run them as is, or you can refine them further. And that includes doing things like a drop down list. So you can define the options for the agent to determine which category it's gonna put things in. Now how do you create a new model from scratch or configure one? It's actually much easier than you think. You don't have to come to Workday for it. You don't have to come to any of our service providers, although we have dozens of them around the globe. Fantastic network of serve of system implementers and others. But you can actually do this right on your own. You just start with that question that you had, and then it will run it against oh, after you I I'm missing a step here. You first you also do need to say which contracts to apply it to. We're not gonna run a a supplier model against all of your customer contracts, for example, unless you want us to. So you define the scope of the contracts to apply it to by folder, by type, and then it'll run across about 10 of those agreements, give you a sample answer. All you really have to do is say correct or incorrect. And if it's incorrect, populate a box to tell us why. What did we miss here? Why did why did the AI not really give you a good answer here? Based on that, the AI will automatically enhance itself. You don't have to be a prompt engineer. It'll make you a better prompt to get you a better result. So this is how it'll automatically refine these terms. When you're happy with the results you're getting, click publish. That model now is in place and will run across all, relevant contracts on an ongoing basis. One more example of what that looks like in a table display. This is what a customer, can do with preconfigured models that we have in our database, that will pull a lease address, square footage, and combine base rent and how increases work into one data field for all of the relevant contracts. So if you have lots of lease agreements in your organization, this would be the kind of result that you can get from that. Now that information is always at your fingertips, you don't even have to ask for it. Alright. How does this align the business? I'm gonna run through these super fast. I'm not gonna spend time on them. I just want you to see that we have put a lot of thought and work with a lot of customers on how do you bring legal, finance, IT, and procurement, all of which are heavily represented in the folks attending this particular webinar today. And, again, we're so glad that you're with us. But I just wanna call out that, you know, this is for all those different types of contracts. If you're, working for the OCFO, you know, if you're in in finance or in procurement, there's so many contract types, kinds of questions, custom models of interest to you. There are terms that are specifically of interest to you that we can identify for you. And so we've worked with many organizations to get benefits on that. This is an example of a finance leadership dashboard bringing some of those top data points to the floor. We've also integrated again, I'm gonna run very quickly here for time. We've also integrated with the Workday financials, suite so that we are now can bring a contract record and some core data points from those contracts directly into the accounting module. We already have customers using this in early adopter mode and free trials available. So if you are one of those Workday customers, this is something you may want to inquire about. With the Department of the OCIO, the office of the CIO, I should say, anyone involved in IT, obviously a wide range of things that you care about. And we'd be happy to share these thoughts and these slides with you. We've worked with many organizations on those kinds of contracts, and we can provide a dashboard focused on data privacy compliance, for example, that gives you exactly the information you need. If you're in procurement, lots of stuff to talk about here. Spend management is a key focus area for us. And in fact, we're aligned within the organization developmentally with the spend organization. And that's good because we've been integrating with them, and I'll call that out in a moment. We've worked with procurement managers, directors, across many organizations and brought great results for them with visibility into these contracts. Now particularly for procurement, this is of real interest because we have introduced now CLM as an integrated part of a full Workday suite for source to pay right there at the center of it so that you can use the sourcing module, feed that into CLM, and then CLM will feed into ongoing procurement management of all your relationships. And that integration is the first step that we've already introduced. It's the first step toward what we were developing as a supplier contract agent that will let you right within the procurement module have deep visibility into all those contract records for those suppliers. Now I really wanna pivot here to the presignature contracts, and I've gotta turn it over pretty soon to Tommy, make sure he's got plenty of time to give you a good demo. So let me run through this fairly quickly. You've seen all that we can do with post signature agreements. The key then is to learn from that and use that to power your presignature workflows and how you analyze and work with those contracts. So with that in mind, we have introduced a lot of new skills into what we have called for several years now our contract negotiation agent, which has used AI to help power through the negotiation steps of an agreement. Here's the first. Earlier this year, we released not just clause by clause auto redlining, which we've had for several years, but now full document review and redlining all at once. So when a new contract comes in, from a third party in any context, this could be a customer that that's determined to contract on their paper. This can be a service provider. This can be anyone that would provide you an agreement and say, no. We're not gonna work on your template. We wanna start with ours. In those scenarios, you may have a 100 pages to analyze and review, and that means it could be sitting with legal for quite a while. I used to do that kind of work and know firsthand how long that can take. We have now made it possible for you to have all of your guidelines in a playbook in our organiz you know, within within our system and then run that playbook against the contract all at once, identify every area of risk, and give it a risk severity level based on the guidelines you've given us so that it will tell you where you have missing language that you need, language that is not compliant in the organization or in the agreement rather. And it will automatically suggest red lines, not whole swapping of clauses, but targeted red lines to, bring in the contract into compliance. Now I won't take more time to talk about this because I wanna let Tommy show it to you. But this is full document review in red line. But I wanna call out now is the next question we often get is great. How do we get a playbook into your system? Maybe we have one and it's a really long word file. Maybe we don't have one at all. Maybe we have one, but we really need 25 because our different contract types have their own playbooks. They're very specific, and we can't apply that. You know, we can't create all these narrow playbooks for all these different use cases. Well, I'm happy to announce there that we are already in early adopter mode and soon to fully release an AI playbook builder. Upload a contract, upload a notes file, and we will turn that into a full fledged playbook within our system. You can certainly make changes on and then bless it before you put it into action, but this is a way to almost automatically create all the custom playbooks that you need for your different kinds of agreements. It's a great way to standardize how you negotiate these terms. It's also a great way to onboard people. So when you have one person who knows this, you know, these kinds of agreements really well and what the company will and won't accept and what the what the fallback positions would be, This is a great way to make that standard across anyone new coming in to help with those contract negotiations. Now one last piece of this. We will, over time, be able to deliver more and more analytics and insights back to you about what is the value you're getting from that and how can you improve those playbooks as you go. I'm gonna leave it to Tommy to talk a little bit more about that and what's coming. But all of this is happening with our contract negotiation agent. So just to sum up, full document review and redlining, the playbook builder that makes that easier and more powerful feeds that the process, and then ongoing analytics and insights to help you maintain those playbooks and this process as effectively as possible. Keep optimizing it as you go. I'm about to turn it over to Tommy for the demo. A couple of quick call outs before I do. If you're interested in what I've just been covering and what Tommy's about to demo, then I think you're gonna be very interested in some of the other developments that are coming very soon with our platform. So stay tuned. Keep an eye open, and we will keep, you know, notifying you. We'll send you emails, about upcoming webinars. But in the near future, we're gonna show you how we're bringing Majentech AI beyond intelligence and negotiation and to the entire life cycle of the contract. Couple of other quick things to call out in resources. Again, if you're finding this valuable today, I think you probably find very valuable a podcast that I cohost with one of my colleagues, where we interview people doing really powerful things with legal AI and with contract intelligence and negotiation tools. The latest on agents, etcetera. These are customers. These are practitioners. These are company founders. So monthly, we do these interviews, and we think you'd find it really useful. It's called Meaning of the Minds, the Legal AI podcast. Hope you join us. We have another webinar coming up on September 17 that you probably will find very interesting if you are involved in Source To Pay, and I know many of you in this, audience today are. So you might wanna grab a quick, glimpse of that QC code. I'll give you a second on it and pre register for that webinar. I think you're gonna find it really useful. Alright. With that, let me hand it over to Tommy, and let's get you live into, Evisort and Workday CLM to see what I've been talking about. Thanks, Adam. Appreciate it. Great job. Alright. By the way, while Tommy is pulling up the other screen, I do just wanna call out, that I've seen some of you put questions into the q and a box. I'm gonna now try to focus on those, answer some in writing. We'll answer more, live at the end of the webinar. Please keep them coming. Go to that q and a box. Enter all the questions you like. We welcome it. Thanks. Alright, everybody. Here we are. We are in product. I'm looking at our documents tab, I have been feverishly is the first part, of the. contract intelligence piece. that glad we got so many questions, with. and thanks are all. our, contracts that have now been brought. into a single try. to pick out a few that I think can give you a metaphor to more, people. I would, you all found it's individual answers useful. you think of your closet, Let's talk? about a few of these. your shirts, One of them, your pants, hey. We always love when we get this, question. is pricing. But over time, it gets to be a mess. When people ask about see, a lot too. that's always good. I are mention mess. Folder earlier today what they used, to be, they've changed over time. no per user fees. imagine you can share the solution, wanted an outfit, dashboards, you just said, to your closet, all of that, like, get me business casual as many people across the organization for you'd summer. like. And it's like, that. triggered someone to say, well, what is. it based they are? right that's front very you. good question. So the, the are trying to do the same thing with contracts and with our contract the number. of documents. AI has read all these documents. fee It on how broad of a deployment that doing. into it's a 100,000. contracts versus, 5,000 contracts, when I go to a dashboard, a certain, I can see all scale the. more that you bring in, I can search within model, those contracts think, because it makes it possible. for organizations can apply filters. like Workday did back in the day real world scenario. to start say California use case and one kind of agreement break breach then over, time expand you have to go check your contracts kinds of see if they contain only pay for what. they need at the time. Fine. Let's go to much everything you saw today, governing law it, is California. fully included. Our AI functionality is mostly included in that basic a look at our services. agreements A couple of exceptions, top left quadrant, here, custom let's take a look. at breach notice. When you create those custom listed as promptly you run them, not are using then Workday days. flex credits for that. Down below, here are those couple of more advanced need. things that will enter with some incremental fees, digging through folders of what you saw can find the things or digging that subscription and. hoping somebody cataloged was helpful. for you, I see Intelligence question that just popped up. to those contracts in a few seconds. Are you oh, I love this one. Are you having to review the details that I can share, with some of my it from here. members? You can see. all the different. pieces of metadata these on a rolling basis. that our AI webinars extracted. multiple times a month. over 40 fact, different have. one coming up. Oh, I think, you're you're sharing create lot there. It's alright. too, just by explaining to the AI what you're looking for. are you are you trying to share the slide to the different shows the link? within the document. that's not what we're seeing. Yeah. Don't worry about also. We'll open this contract if you wanna that we showed earlier, verify. and in fact, it is in the documents tab. You'll see a link to our next here you can see an example of the OCR. 17 where we're gonna walk through pages, source to, pay solutions, handwriting, and then we have another. one coming up on October 8 that I can't give you a link for right here, we. can see the data that was. pulled out, and I can click on a magnifying just. those few. will highlight for doing. So now I can least two webinars that the AI month related extraction this. correct. But thanks so much for that, and you will be able to share do is be able to get your data the link you got originally, easily. the the link you take a look at another feature. here called can share. that link for sure on demand view large, language others in your org. at this point. Let's see. You can ask question large, language model it. possible to override requirements are there for a breach generated this document? field, AI is now reading it. It's going to give, us an answer. you know, answer? Now even better than, you, a that there's something the AI got wrong, a Gemini, the AI will certainly the answer, on occasion we, give you the answer perfect. and we give you if you see an extraction you can a. generated answer and you, think it is not quite right, AI, has been trained, specifically on contracts and reinforced. by legal must be permissioned make sure that do so so that we don't have just every, user making changes hallucinated the fly. answer, as, I see very often in those general. There. is a there's means example, to do q and a termination you go. for breach. Here's our bookmark, and now I can. human verify it. There was one here that, Let's not sure I gave the greatest at a different. example not sure I fully understood contract. intelligence. And it had to do with how does the AI dashboard things. and find think this may be getting into an area a client, of supplier. management that I'm not well enough first in. If an agreement is written with language for all locations, Now when I pop up Ask AI, it can ask a question of my search results. location? And here I've preloaded an answer here. How does it know that something is eligible? I'm really And sure asked fully understanding that, and, unfortunately, identified can't do it MSA a communication all amendments to for Cross. Creek. But I'll table that shows, clauses that have changed what what the prevailing terms are. agent can do table, goes beyond for each. clause, It can interpret information the original MSA the contract. for language, how each amendment changed so and at the end the the day, what the right way, terms. you know, it This is a hugely answer back telling you, only know, a few this is. ago. And then when you system like, Evisoric you can turn that into a custom AI model. if you like so that you it's not just a one off question. You have Couple, of other things the team might, you have look here, now as a structured dashboards. data point. For example, we can see upcoming that's helpful. expirations. I wanna underscore that because so often, renewal notice dates. we just know your renewal. types. We know your upcoming expiration believe. they know what's going on in the space, these into, that seem fairly well informed to your inbox. say, well, Here's, it's alert. really about what, all your, contracts extraction. that are expiring in the next ninety days or one eighty think. broader than that. can stay on top of those renewals. been doing extractions for, nine, one of our early. clients, paid for, Workday we're at the point where data can be it because they were able to identify interpretation contracts text. they no longer think about an expiration terminate that. is not expressly stated in the four corners of the contract, but that can more dashboard you know, you here. This, is procurement contracts. knowing the effective the procurement team and you have a remit language save the business money. and how We come down here, work we can see some extracted. data like early payment are the, kinds of things that it price now, do. So I I'd volume you, to think in those terms about, etc. a detailed question, if I have. a remit, again, to I misunderstood a million dollars, I I apologize. next year, I think it's can come here and say, something, more specific me all my. contracts that are over a million a question about legal invoices. the next twelve months. We are not now, specifically, I know where I can save the most with legal invoices. out of the gate. But that's not to say that you can't bring in old world, legal invoices have been emailing the system calling somebody your say, retainer. Do you even know what we're signed with for and, when this renewal is coming it? can be valuable I need interpreting save money. what's in that can. be proactive. So that's something that's worth experimenting with, and we we'd love to see that attempted. Alright. But, no, we're not a the contract intelligence portion of the system We're se. gonna move into what Hal set up for us, which is agentic I think that I think that's probably pass end of the questions that had popped up. So to help with, this little story here, walk you through it. I'm gonna think are gonna couple valuable here. for I have Barbara Business too specific for. one particular user. And I often see a little bit of tension as we approach the top of the hour, side and the legal side, to Tommy. and it's not on. that. Thanks to everyone, that attended has. this new third you'll attend more of. our webinars needs to get it vetted to your Workday it can be signed, but she doesn't do this very often. for a Workday of that, CLM specialist checks the company intranet. to do a consultation old emails, with you so you can delve into. So issues kinda types out. this guilty email to Laura Legal that, and says, wish. everyone I know you've told me. how to do this before, but I forgot. And Laura Legal is frustrated too because she feels like she just keeps telling everybody the same thing over and over again. This is how you do it, and nobody remembers. And neither of them are wrong. They just need a system that helps keep everybody organized and on the same page. Alright. So let's take a look at that. So we have this contract here. Let me pop it open real quick. Simple services agreement. It's about 10 pages long. It's a lot of content though, and it's all novel content because this is third party paper. For Barber Business to get it get it into the system, how can she do that? Well, one way, she sends it to Laura Legal, and Laura Legal will go to her tickets area of the product, create a new ticket, and choose vendor services agreement and upload it. But the reality is like, for a lot of organizations, there aren't four things to choose from. There might be 40 or there might be 400, and you can't expect Barbara Business to remember all those options, which one she's supposed to use. Because of that, she can go to Ask AI, click on our workflow routing agent, and chat with an AI agent about what her need is, and this will help guide her to the correct workflow for intake. Alright. We've covered a couple of ways to get documents into the system there. One, you can just go click create new ticket and choose the type of agreement it is. The second way is you can use this agent, which will help guide you to the correct intake. Now I've queued this up already. Here's our vendor services agreement. This is what we call an intake form. It's like a q and a about this contract to help route it to the correct people or teams for review. One thing I want to point out here is this is all point and click configurable by you and your administrative team. You have new software developers, you don't have to pay a professional services team, hundreds of thousands of dollars. The reason is because we see that over time, those things get stale and then it never gets updated and people stop using the system. So here we're in our on our vendor services agreement. You can see we have stages for review, sign, and finalize. You can track cycle times. You can see who the contributors are, and we can see who needs to review this contract. It's starting off with legal review. The first instruction, the first task for the legal team is let's review the document using the company playbook and automatic redlining. Let's do that. Now, for Laura Legal, this isn't tipping onerous task. She has a very large playbook. She has lots of things to track. Remember, this agreement is 10 pages long, and she has no idea how it was put together. But instead of having the contract up on one screen and, the playbook up on the other screen and peering through her glasses and trying to figure out where to go, she simply picks the vendor services playbook defined for the company and runs it. So what's happening in the background here while this AI review is running? So this playbook has five different clauses that it checks. And for each clause, we've specified preferred, walk away, and fall back language. The AI then determines for LoRa Legal whether or not the clause is compliant. If it meets or exceeds the requirements, say no issues found. If it does not meet your requirements, then it will give her action needed. Let's take a quick look at an example where it doesn't need a change. Here we're looking at payment terms and it's telling Laurel Eagle, hey, payment terms are sixty days, which is more than our thirty day minimum. We're good to go. No changes needed. Easy. Underneath action needed, it said that this contract doesn't have any information security obligations or requirement these days, and it's going to wholesale insert in the green text here, the company preferred language. Similar for limitation for liability and indemnification. For indemnification, you can see it's doing a surgical red line. It's not only striking some language, but it's inserting some language. It given again, it gives you the reasoning here. So Laura can review it and understand those changes, and then if she's good with them, edit and insert them all at once. And why do we care here? Well, we care because remember where we started. We have Laura Legal, two screens up side by side. She's trying to figure out this 10 page document she's unfamiliar with. And anything that she doesn't meet puts the company at risk. But now, in just a couple minutes here, we've done a full document review with AI, identified problematic clauses, suggested red lines, and now Laura can review and accept those. Now lets you reach your agreeable language faster, gets you the terms you want, all while all while saving time. It's a very exciting feature. Alright. So you might be asking yourself at this point, well, this this looks great. We have had great feedback from it. It's had high adoption, especially these red lines acceptance rates, if that's something that you're thinking about. But what does a playbook actually look like? Let's go ahead and take a look at one. Here's our vendor services playbook that we're just looking at. Underneath, you can see those five clauses we were just talking about. For each of those, there are guidelines. Let's look at the payment terms because this one's relatively simple to understand. At the top, we've told the AI in plain language what to look for. Hey, I'm interested in I need you to go and find the payment terms in this contract. In anything more than thirty days, is it okay? Between fifteen to thirty, I want somebody to review it. And if it's less than fifteen, we don't accept that. Those payment terms are too short. And down below, there are sample wordings of what each of those languages or what that language looks like for each of those cases. And this is the wonderful thing about LLMs, is it's like working with a colleague. You simply explain how it should work, and then the colleague can execute. Now, if I'm chatting with Laura Legal, she might be rolling her eyes at me because she says, have you seen our playbook? Because it is gigantic. This is great, but, like, when am I ever gonna have time to do this? Let's take a look at an example playbook for NexoLink technologies here. This playbook is so big, it has an index at the front or a table of contents. And it has a how to use instructions. It has color coding. And down below for each of our different, clauses, it has sections and it has subsections. And this is where our playbook agent is an exciting new feature. Click create playbook on top right here. You could configure it manually, but who has time for that? Instead, we choose create with AI, and then you can upload different types of files. You can upload this Nexolink document. You could upload an example NDA. That's one of your ones that you typically use. AI reads it, parses it, and turns it into a playbook for you. Now it does take a couple minutes to run, so I've queued it up in another screen here. You can see an example here, software license agreement review, and down below all the guidelines have been created, and I can see what they look like. Let's take a look at one real quick. We took take a look at audit rights. The AI has that high level instruction at the beginning, and then it has example language for that preferred fallback and walk away language. Alright. And what we've seen is a dramatic drop in the amount of time it takes to get up and running. What used to take the legal department or a business user a month or more to create can now be done in half a day. And that lets your team get up and running quickly. Now the next thing that Laurel Eagle might bring up with me is, okay. Well, this is great. It it made it really quickly, but the reality is that our playbook changes all the time. And how do I know what's working and what's not working? And that's where an exciting road map feature comes into play, playbook analytics. Okay. So this is due for the fall, and this is something that Laura Lee will be excited about. It looks at your playbooks and measures things like, what are your most used playbooks? What's your red line acceptance rate for those different clauses? What's your time to signature? Are we bringing that down? What are our most negotiated clauses? And if you look at this little card here, an example here, it's making a suggestion that we soften the limitation of liability fallback, and it's giving us a reason for it. It's saying that, if we change it from twelve months to twenty four months, it seems to be what's most often requested, and we can accept, expect about a third drop in the amount of times we need to negotiate against this. And you can see that underneath the expected impact. And what this lets LoRa Legal do is improve the playbook over time. So we're not setting it up once and then it gets stale and not useful over time. It's something that evolves and grows with your business. Now let's you make more informed decisions. Alright. So last thing, just to recap here as we get in the last few minutes, AI and playbooks, like so what? We want to see you accelerate those contract review times. We want you to see that get your preferred language more often, reduce risky language, drive consistency in your contracts throughout the business. And you we are also adopting a system that's easy to use, gets you up and running fast, and will improve your business over time that will grow with you. Alright. So we saved a few minutes at the end here for questions. I saw the chat. It just, like, completely blew up while I was talking. Is there anything hello? Oh, sorry.