Name: Agentic AI in Action: From AI to ROI
Uploaded: 2025-10-22T14:12:04.650Z
Duration: 56 min 8 s
Description: Agentic AI in Action: From AI to ROI

Transcript for "Agentic AI in Action: From AI to ROI": In a world where technology is constantly evolving, one concept is redefining what's possible, agentic automation. Agentic automation is more than just a buzzword. It's a game changer. But with great power comes great responsibility, and the gap between promise and results is vast. What if you could turn AI hype into tangible ROI where every solution is grounded in real world use cases, not marketing promises? Where AI innovation is balanced with governance and trust. Where AI is ready to deliver value from day one. Helping you innovate faster, better, and with bigger impact. SS and C Blue Prism. Our agents mean business. Hello, everyone, and welcome to today's webinar, Genetec AI in action, turning AI into ROI. I'm Natalie Keatley. I'm the VP of product marketing here at SS and C Blue Prism. And today, we're gonna be exploring how to turn the hype around Genetec AI into real enterprise ready results. And we're also going to talk about some of the solutions that we've launched to enable organizations on their AI journey. Because the big question really on everyone's mind is how do we generate a return on the very significant investments that have been made in AI initiatives today. There is no doubt the potential with AI is enormous. Capgemini have predicted that it is going to generate $450,000,000,000 in economic impact by 2028. But despite this hype, many organizations just aren't seeing that value hit their bottom line yet. In fact, MIT recently reported that 95% of Gen AI initiatives are failing to deliver tangible business value to organizations. And that's a very sobering statistic when you think about the amount of time and energy and money that's been poured into AI. We've identified three consistent themes that keep coming up that stop organizations from turning AI investments into ROI. Firstly, we often see agentic AI being approached from a technology lens, that everyone gets excited about the new shiny capabilities. But AI isn't about the technology. It's really about organization change. It enables a very different way to of working, and that impacts every part of the business. But right now, we're seeing an awful lot of hype and confusion, and Gartner are actually predicting that 40% of projects are gonna be canceled due to escalating costs, unclear business value, and inadequate risk controls in the next two years. Secondly, we hear a lot about the governance lag, and the governance lag is really fueled by fear because employees are worried that AI is gonna do their jobs better than they can or replace them altogether, and organizations are worried that they're gonna lose control over the very sensitive data that they hold. Trust in AI agents has dropped from 43% to 27% in the last twelve months according to Capgemini. And that fear is real, and it's impacted by governance because the pace of innovation for most organizations today is outstripping their ability to governance, and that governance lag is eroding the potential value that AI could deliver because it introduces risk. The third area is really the skills gap because AI is completely reshaping the job market. And whether it's about the people who are building the AI or the people who've been displaced or whose skills need to change because of their AI, it's introducing new jobs. It's changing the existing ones faster, and that is bringing about an awful lot of work for organizations in terms of trying to figure out how to retrain their workforce. How many times do you hear organizations say, we're gonna free people up to do higher value work and more strategic work? That's great, but if you don't really know what that work is, it's really, really hard to put programs in place to change that work. So how can you overcome those obstacles? Well, we think we can help organizations turn their AI investments into real results. Firstly, our customer zero program has provided us with real world results, learning, and validation that we think we can use to help other organizations overcome some of those technology and value realization challenges. Secondly, our AI governance platform, which is a direct product from our customer zero program, enables organizations to deploy AI soft safely and responsibly and overcome the governance lag. Thirdly, we're also providing ready to go AI agents that deliver very tangible business outcomes without asking organizations to invest in skills and infrastructure themselves. So over the next few minutes, you're gonna hear from Rob, Adam, and Ben. They're gonna share their expertise and their insights on how to overcome the obstacles of AI adoption. We're gonna talk about the customer zero program, our prebuilt a agent solutions, and our AI governance and chat platform. And then finally, you're gonna hear from Omid, who's gonna give you a sneak peek into what's coming next in the world of AgenTek AI. So with that, I'm gonna introduce Rob Stone, our senior vice president and general manager for intelligent automation and analytics at SS and C. Rob has really been at the forefront of our customer zero program. He's experienced firsthand how AI can push the boundaries of what's possible for us and our customers, and he's helped pivot the automation program from a cost lever to a growth engine for our business. And and he's now actively helping other organizations to achieve the same. So over to you, Rob. Thanks, Natalie. So, you know, who is SS and C to start really as the customer zero for SS and C's Blue Prism automation capabilities? It's a big publicly traded regulated organization that serves demanding financial services and health care customers worldwide. So, you know, SS and C mirrors the Blue Prism customer base pretty well in terms of how sensitive the data is that we process, and how, you know, complex our business is relative to the types of solutions that we provide to our own customer base, in the industry worldwide. So, you know, SS and C acquired Blue Prism about three years ago, and one of the major initiatives from day one was to get it deployed far and wide within SS and C's business. Largely the, largely the BPO and services businesses, because that's where we saw the ability to get the most uplift, right, to automate away some of the frustrating and mundane work that went into processing large amounts of data, to to hit, you know, high frequency deliverables for for our, you know, valued and and highly demanding customer base. So today, we've got, you know, 3,300 digital workers deployed across, you know, a number of different processes all over the world with, many of SS and C's, you know, operational folks and and staff highly trained and certified on the Blue Prism platform. You know, that that's really meaningful. Right? Because that means that we've got, you know, a petri dish, the biggest petri dish in the world to understand how our capability is utilized, take that feedback and and, you know, enhance the platform accordingly, which our, you know, clients of the, Blue Prism platform, you know, really get to take advantage of. So the fact that we have it deployed in real time, in production, doing really high value mission critical work, for for customers, you know, and things that require, a lot of domain expertise, things like trade confirmations and and, you know, global tax accounting and, you know, another, you know, highly, sensitive and regulated, you know, processing. The fact that we've got Blue Prism automation capabilities assisting our high value, high expertise staff, you know, is is really, really valuable for us. You know, the the the story sorta goes that, we deployed all of these digital workers and and, you know, what we were finding was all of the folks that were doing the processing, utilizing the platform were saying, you know, I really, think I could do more if I had AI. Right? And, we were, you know, pretty inclined to provide those tools to our staff in order to, you know, give them all the horsepower they needed from a technology perspective, but we recognized the challenges in in governance and and we understood the risk, as it related to unfettered access to large language models and other AI tools. And and we spent, you know, a lot of time, a lot of thought, a lot of effort, a lot of resources, you know, putting a government governance program in place, which Ben Ben will talk about, from a technology perspective, from a framework perspective, and from an overall kind of, you know, how we were gonna go about allowing a broad set of staff, you know, allowing them the access to large language models that they were asking for. But that was really important because what it did was sped up the innovation curve. Right? And so what Adam, our head of professional services is gonna talk to you about is sorta, you know, what happened next, you know, which is where, you know, AI use cases popped up all over the place within SS and C, which gave gave us a great foundation to go to market, with our agent catalog. Right? So today, we've got, you know, tens of AI agents, you know, across tens and tens and hundreds of processes that are alive within SS and T's secure environment that we're also going to market with. Right? And that doesn't really happen unless you have a really far and wide deployment and program of the Blue Prism platform. So we're really proud of, you know, how we've taken advantage of, you know, the expertise within SS and C, the processing power, and the and the, customer base that we have, to enable the Blue Prism organization to continue to innovate at pace, and that's only speeding up. We're really excited about where we are. We've got AI agents for sale. We've got AI agents deployed internally all over the place and externally, And these are either prebuilt. They're, you know, configurable. And and as Omid will talk to you later, you know, we're really excited about, you know, what what's to come over the next, over the next several months from a development perspective. So so we really appreciate everybody joining this webinar, and and, I'm sure you'll enjoy the content, sort of going forward. Thank you very much for that overview, Rob. I think you summed it up perfectly when you said that our customer zero program has given us the world's largest petri dish for AI innovation and adoption. So next up, I wanna introduce Adam Binder who heads up our global professional services organization here. And Adam's been instrumental in building out our AI agent solutions and services practice. He's gonna take you through a quick overview of our prebuilt AI agent solutions that are aimed at helping to fast track your AI adoption, and he's gonna talk through some of the AI agent services to help build agents on your behalf. Thank you, Adam. Thanks, Natalie. What I wanted to talk to everyone about today is how our SS and C agent services have worked with the AI Innovation Lab to build those customer zero agents that Rob talked about earlier. In doing so, we created an AI framework, used across all of those agents, which leverages our governance and guardrails of the AI gateway. To get into a little bit more detail around that, here's a quick video to introduce our SSMC agent solutions. As a world class financial services and health care solution provider, SS and C sees the initiative in AI agent development with a governance first AI agent building program for in house operations and have now made these AI agents available for customers to purchase. The results have been transformational, unlocking operational efficiency, revenue growth, improved customer satisfaction, and new levels of agility and innovation. Now through SS and C agent solutions, we help our customers fast track AI adoption without the complexity and risks, building autonomous AI agents that are goal oriented, adaptable, collaborative, and trusted in highly regulated settings. We provide AI technologies, proven methodologies, and expertise of financial services and health care to accelerate time to value. Take our credit agreement processing AI agent as an example. Credit agreements often run to hundreds of pages, previously taking skilled employees several hours to review, extract data, and update the loan management system. With SS and C agent solutions, the AI agent sends the agreement to our secure AI large language model. The AI agent poses a series of questions to its AI model, which reads and interprets the complex finance specific legal terms to find the information needed. The AI agent has built in security and governance, including AI evaluation, a double check to assess the quality and accuracy of the information returned before the process proceeds. With a full audit trail and routing exceptions to a human teammate, you can be confident the AI agent will meet regulatory and best practice governance standards. Agreement processing time has reduced by 95%, so downstream collateral management and financial reporting now take place sooner, reducing risk and driving revenue growth. And instead of spending hours on paperwork, employees now focus on customer relationships and identifying more opportunities for innovation. Already proven at scale within SS and C, these AI agents are now available to you, delivering reconciliations, contract and invoice processing, customer communications, and more. With SSNC, you don't face the AI learning curve alone. Our experience, governance, and agent solutions give you a faster, safer path to AI agent adoption. Contact us today to see how SS and C agent solutions can unlock your business's full potential. Within that video, what I wanna call out is the fact that we've made that leap from POC to production. And to be able to do that, what we have to do is understand the governance needed to be put into place in order to do that. I'll get into more about that later, but I wanna dive a little bit deeper and show that to everyone what the credit agreement agent actually feel looks like at work. Let's see how it works. The AI agent waits for new credit agreements to arrive, downloads, and sends them to an agreement processing AI agent to find and extract more than 40 pieces of information. The AI agent reads through agreements, which can be four to 500 pages long to find discrete data like the facility type, global commitment, and contact details, as well as complex information that needs to be derived, like the amortization type that requires the AI agent to identify how much of the principal amount is repaid each year to decide if payments are full or partial interest only or amortized with a balloon payment. All SS and CAI agents use our AI gateway to govern every AI model interaction. This keeps the data and AI model secure and creates an audit trail. Every piece of information extracted passes through SS and C's evaluators to check for semantic correctness and possible hallucinations. If the evaluators detect a risk or parts of a scanned document are not clear, the section is routed to a human along with details of the risk detected page number, and a snippet of the relevant text in the agreement to help resolve the issue quickly. Finally, the agent sends the extracted and checked information to the downstream systems to be actioned. So within there, you saw our AI gateway in use, implementing the guardrails to ensure we've got the safety, of PII information and a lot of other aspects when it comes to pulling, extracting the data from that document. We've also created evaluators within our AI agents and those are used to create enhanced validation steps to ensure what we've extracted is correct based off of what we're looking for within the different document types. After that, you also saw that we provide a comprehensive audit functionality. So we know where within the documents that extracted data comes from and what section within those details. So if we ever need to look that up later from an audit standpoint, we can go back and see where that those details came from. So we offer more than just AI agent products. We offer AI agent solutions and services to be able to help deliver this for our customers. And what you get is you get the help of us implementing those AI agents and getting them from proof of concept within your organization actually into production. And really to be able to do this, we work with our customers understanding what governance changes are needed using our AI framework that we've created based off of those customer zero agents like the one you just saw. And what this allows is we're using our expertise not only in building those agents, but really understanding the workflow orchestration needed to get that done and working with your teams and putting the people process in place to get the governance approvals, the governance awareness with AI agents implemented, which is what's going to ensure that successful deployment into production. All of this is done with our managed services. This allows you to be able to leverage our environments to not only use our governance first mindset, but to ensure your data is safe and secure and not being used to train future LLM models. With those services, we ensure that that AI agent is up and running and we track the performance of that agent. And if we see anything change, we make proactive adjustments if needed. Now with those managed services, it has an all in pricing model. So you get cost predictability. You don't get surprised by how many tokens are needed, how much training effort is needed, what the document volumes might be in the future for this agent. All of that is built into the price that you get. Now we also know that this is new for most of our customers. And so with that managed services, we also include additional time for my managed services team to be able to work with you to make minor changes if we discover that into production or if you need to add additional fields or slight additions to that AI agent, we've got the time built in so that we can modify that AI agent after it is implemented into production. Now our managed services are within our SS and C private cloud environment, but we know not everybody can use that. We have AWS instances as well and if that can't be used and it needs to be within your environment, you can use our SS and C agent solution services to be able to do that as well. You can leverage our expertise to deploy those AI agents in your environment using your LLMs and this has been allowing you to accelerate that adoption of AI while still benefiting from our governance first mindset and the experience that we built implementing those Customer Zero agents within SSMC. Now to help you move forward, we've created in our AI agent catalog. First, you have the customer zero AI agents. This is a list of agents that you heard Rob mentioned earlier that we have running in production today. Now these AI agents are working on real solutions, not simple tasks like timesheet or HR entries. They provide tangible value and are running in a regulated area of our business. We also have our general AI agents. These are a list of agents that have been created based off of our customer needs. We leverage our AI framework, AI gateway and the expertise we built working on our customer zero agents to implement these solutions for our customers. To see more detail about the AI agents within our AI catalog, you can go to our website or you can reach out to us to walk you through those details. Now if those prebuilt AI agents don't meet your needs, we also have our services here to be able to design and build that solution for you. My team is here to be able to help take that complexity out of implementing the AI agent solution within your environment and we can use our governance first approach to be able to build those custom built AI agents for you. So why choose SS and C agent solutions? Well, we've done it already as you heard. We've learned the lessons of what's needed to implement an AI governance council within SS and C. We've created the tools to ensure consistency and governance like the AI gateway. Our AI agents aren't a POC. They're in production today providing real business benefits and value. Like when we worked with our Globops team, we reduced their agreement processing time from three hours to three minutes. That AI agent also processes different types of agreements and amendments as well, feeding those updates into a downstream loan management system. This is about being able to extract the value as well as action that data. And what this does is it creates a competitive advantage within our business. So it's not just about efficiency savings, it's about creating a better business within SSMC and doing this also benefits our customers. We've implemented that same AI agent with the customer, but we've also had to make significant modifications to the number of data fields that needs to be extracted. We were able to accomplish all of that and the agent is still able to maintain its high accuracy as well as be able to complete those agreements within three to five minutes for our customer. Now you want to move quickly and implement AI agents within your environment. So we have those pre built AI agents to be able to do that. We also have the AI agent framework and experience building our agents to help fill that governance and skills gap that a lot of our customers have. We've built the capabilities and took the time to ensure that there was traceability, auditability and accuracy with our evaluators in the AI agents that we create. This is what separates us from first movers that create lists of agents but don't have anything to truly show in production providing value. And now to talk more about our governance and our AI gateway, which is what allowed us to move our AI agents into production has been awesome. Thanks, Adam. Let's start with a mindset shift. The best way to approach AI responsibility is to accept that it's imperfect. Instead of asking, will AI make a mistake, the better question to ask is, when it does, how do we detect it? How do we contain it? How do we correct it? That's the essence of AI governance, operational guardrails that make innovation sustainable. Enterprises without robust governance will not be able to capture the value from AI innovations that their organizations need to stay competitive. Governance shouldn't slow AI down. It should allow organizations to innovate safely and confidently. By centralizing platforms, governance, penetration testing, and security testing, organizations can accelerate AI in a safe and compliant manner. At SS and C, we call this applied innovation, which is the idea that every breakthrough must be built with governance and accountability from day one. And that philosophy is exactly what led us to build the SS and C AI gateway. AI has evolved rapidly with GenAI and Agentic Ai now being adopted across industries and reshaping operations in nearly every enterprise. But while AI is everywhere, scaling it safely, that's the real challenge. Without the right governance, organizations risk regulatory breaches, legal issues, financial loss, and even brand damage for misuse, sensitive data exposure, or unchecked bias. That's where SS and C AI Gateway comes in, a powerful new AI governance solution from SS and C Blue Prism designed to ensure your AI implementation is not only productive but protected. It provides centralized, auditable, and compliant access to generative AI and large language models, helping organizations unlock the value of AI while managing risk every step of the way. With SS and C AI Gateway, you can implement a global governance framework tailored to your organization's needs. Build your own AI solutions with advanced security and data loss prevention baked in, and improve output quality with industry specific retrieval augmented generation systems. Real time guardrails let you monitor AI activity for quality and risk while maintaining full auditability of every interaction. What sets SS and C AI Gateway apart? Enterprise grade protection, like prompt injection detection, PII redaction, and hallucination checks, full end to end auditability for every LLM session, a governance first design with real time risk monitoring and explainability at its core. It's built to meet the toughest standards in the most regulated industries. Whether you're working with large language models or custom AI tools, AI Gateway is model agnostic, so it works across your ecosystem seamlessly. Deploy it on premises in the enterprise grade SS and C private cloud or via AWS wherever your enterprise needs it. SS and C AI chat enables natural language interaction, making AI gateway more intuitive and accessible for users. And with tight integration into Blue Prism automation and orchestration, AI Gateway fits naturally into any AI enhanced business process. AI is changing the game, but only if you can trust it. With SS and C AI Gateway, you can scale AI safely, smartly, and successfully. Speak to SS and C Blue Prism today to see how AI Gateway can accelerate your AI strategy. Here's the real challenge. AI adoption is happening faster than most organizations can govern it. Recent studies show that 68% of employees use unsanctioned free tier AI tools, and fifty seven percent of them admit pasting sensitive company data into these tools. That's not malice. That's just people trying to be productive without access to safe approved options. And, honestly, you can't blame them. There's always a drive to compete and be more efficient and do more with less at every organization. At the same time, 63% of organizations that suffered a breach have either no AI governance policy or are still developing one, and only a third audit for shadow AI usage. It's no surprise then that 97% of companies that experienced an AI related breach lack proper access controls. This is the governance gap that AI Gateway was designed to close. What you're seeing on the screen here is an image that describes a high level, overview of the architecture of the AI gateway. So at the top, you have the ability to kick off AI inference tasks both with digital workers as well as through the SS and C AI, chat interface. Organizations can also code directly to the APIs. They're open API spec APIs that which makes it very easy to adopt and use, AI applications. What we're doing essentially is wrapping the AI inference calls, so the calls to the model where you're sending information to have the model interpret it with both auditing and guardrails on both the input side and the output side. For auditing, our core design philosophy is around the requirements of the EUAI Act. So in Europe, and there's regulation around the world that's coming to make this the fact all around the world. But in Europe specifically right now, if an organization, has decisions that are made or assisted by AI, the consumers that are affected by those decisions have two rights. They have the right to an explanation, and they have the right to an appeal. Both of those rights require very robust observability of your AI systems. You need to be able to track everywhere that AI may have touched that decision making process. So it might be in your, email capture solution. It might be in an ML model to look at, say, an insurance risk weighting. There's a lot of different ways AI can touch a consumer decision. So it's very important that you have observability available to tie all of those different data points together in a single pane of glass view of that decision, which is what we're building with the AI gateway and the AI governance system. For the guardrail side, these are very security focused, and abuse mitigation focus on the input side. So we're doing things like prompt injection detection, jailbreak detection, toxicity, and restricted topics. Anything that you wouldn't want your LLM infrastructure to be used for, is going to be caught and ameliorated before it actually gets into the model. On the output side, we're doing a lot of the same guardrails of auditing. But on the output side, we're also augmenting the output with confidence scores. So we collect log probabilities from each individual token. We aggregate those those together to get a confidence score, which is a measure of appropriateness of the response to the context that the the LLM, the model, was given. So it's a pretty high overview of the SS and C AI gateway. What I want you to take away from this is whether an employee uses AI chat to request insights or digital worker triggers an automated prompt behind the scenes, AI gateway applies the same guardrails across both of those, really, any AI interaction that your organization can have. It's doing policy validation, risk scoring, logging, and confidence scoring all in the background with every interaction. This is how organizations will move from simply experimenting with AI to deploying responsible Adjentic AI, driving innovation and transforming how work gets done, but always within the boundaries of governance and safety that your customers and your employees expect. Now let's see what that looks like in action using one of the most highly regulated and publicly scrutinized processes. This is the SEC 10 k process. So what we're going to do is we're going to load up a 10 k document in our SS and C AI chat system, and we're going to do inference for it. Alright. So now let's take a look at the SS and C AI chat. So what you're looking at here is an enterprise grade version of, say, a chat GPT or anthropic claud that organizations, business users can use to interact with AIs directly in a safe and compliant manner. All of the AI workload for this chat system goes directly through the SS and CIA gateway. The prompts and responses never leave our data center, and this is a safe compliant, interface for any kind of data that SS and C works with. So I'm gonna start it off with asking it to explain the life of a trade from initiation to settlement on the New York Stock Exchange. While this is going, I'm gonna highlight some things that are happening in the background. So the first thing that's happened is that that prompt has been audited. We are running guardrails on the prompt itself, so we're looking for, again, things like toxicity, restricted topics, things of that nature. While the LLM is generating the response, we're actually auditing and logging and rescoring that in real time. And then we don't give the response to the user until the all of the audits and, guardrails have actually been completed. So that's why you see all the text come in at once rather than being typed out like you do with ChatGPT and some of the other systems. So let's give a quick quick whistle stop tour of some of the high level enterprise features here. So first off, you'll see that those confidence scores are surfaced on every single prompt. Every single prompt takes that confidence and presents this to the user. This is color graded, so an organization can choose what thresholds that they're comfortable with. You might have team level thresholds as well, where for your marketing team, you might allow more creativity and less confidence because they're doing more qualitative things versus a support team that's working with your customer service documents and SOPs. You might wanna have a much higher confidence score. You don't want hallucination there. Up at the top, you'll see the context limit. Context limits are important within, large language models because when a model is fed more context than it can process, it will actually start to degrade its response because it can't hold all of the context that's required in at the same time. So what we do is we display to the user how much context they have remaining, and then we actually will force a user to start a new chat if there is an issue, that, is is taking up more context. We also have the ability to manage files as well. So if we had uploaded a file to this, we would see that here. So something I really like is taking technical documents or tech taking technical explanations and making them a little bit less technical. So I'm gonna ask it to explain the same thing shorter, but, like, I'm a five year old, and you'll see the confidence score of this response drops a little bit. We're asking it to be more creative because, obviously, there's probably not a web page out there somewhere that is explaining the life of a trade on the New York Stock Exchange to a five year old. So it's having to be more creative by changing the words and shortening things up and summarizing. So the confidence score dropped, and you'll see my context adjusted a little bit as well. So let's do something a little bit more complicated. So in the same chat thread, I'm going to upload SS and C's 2021 annual report, and I'm going to feed it a much more robust prompt. While this is uploading, the upload actually happens fairly quickly. But what's also happening in the background is rather than just extracting all the text and then feeding all of that text directly into the LLM directly. What we're doing is we're sending it through a real retrieval augmented generation system that will chunk it up into paragraphs. These paragraphs overlap. And by doing the more robust rag processing for this rather than just take taking all the text and throwing it to the LLM, it gives us not only higher quality results, but it also has the ability to give us citations for those results as well. So I'm going to ask the LLM to summarize the document, tell me what kind of document it is, and depending on what kind of document it is and what it's doing, run a specific report. So I'm gonna run this report. While this is running, I'm gonna point out a couple of other features as well. So we have the ability to, toggle on and off web search. So if the LM doesn't have an answer to something in its context, it will actually reach out to the Internet and find the most recent source of that information. But we give users the ability to toggle this off, and it's off by default. The reason why it is off by default is because, we want the primary sources of information to be the context that the user is providing, not the model training data and not what's on the open Internet. The, we have a robust white list of trusted sources that, the search provider can only take from those sources. So that's another way for organizations to sort of control what things are available to the LM. So for us, we have white lists of trusted financial services documents and, and, websites that provide information about financial services. If you're a health care organization, you could limit these things to medical journals and things of that nature. We also have the ability to turn off and on agents. So we have different MCP agents available to the chat as well that organizations can work with. This really allows you to leverage your data in a very real and robust way. We can make an MCP agent for any data source that you have internally, whether it's a custom database, your SAP install, or maybe you have, like, a proprietary trading system that you wanna pull data out of as well and allow your users to interact with that. These MCP agents can not only pull data, but they can also push data as well, and they can perform very complex tasks. And what these are, these are tools for the large language model to get work done with. So this is be this is starting to go beyond just displaying text on a screen. It's actually starting to go and work within your your business systems. So let's review this. So we got a pretty robust summary. It's following the format that I defined for it, and it's answering the question. So it's a 10 k document for SS and C Technologies. It's for the year 2021. The ticker symbol is SS and C, and it produced an executive summary, financial analysis, and then risk assessment. So it's a great feature. The so this what we're looking at today is a thread. Threads can be added into collections. Collections are very powerful tools and are becoming more powerful in the future. So today, they're just a collection of related threads that the user has put together. In the future, each of those threads is gonna be able to have its own system prompt. So So you can give it its own personality, its own marching orders, and then those threads can be tagged by each other. So one thread can tag another thread in its response and say, hey. Take my response and then go do something else. So it allows users to create multistep, very robust workflows all within the comfort of the AI chat system with no code or without even having to open up the workflow tool. So that's the SS and C chat system. Now let's go back to the presentation. As you just saw on the demo, we've fully integrated the AI chat system into the SS and C AI gateway. We're bringing all the power of that centralized governance model and private inference into a desktop experience for our users and for your employees. This is really important because by providing a safe, powerful alternative, organizations can limit shadow AI usage in their organization, which is, again, as I said before, is one of the most poignant security and data privacy risks at every organization today. Now let's talk about what makes the AI gateway truly different. When most vendors talk about governance, they're talking about something bolted on after the fact, a compliance checklist or a monitoring dashboard. Again, most organization or most competitors to the AI gateway system stop in the beginning phases of AI adoption. They're they're going from ideation into into running into production. But once things end get into production, you're not you don't have that that robust monitoring and tracking like you do with the SS and C AI gateway. We've really integrated the AI gateway into the very fabric of everything we do, not only at SS and C with AI, but with Blue Prism and Chorus. It's not just an add on. It's our foundation governing AI from the first prompt to the final output, whether it's a chat request or a digital worker task or an API call. Other solutions might give you visibility, but they don't give you controls. The AI Gateway control is continuous and automated. Every interaction is policy enforced, logged, and risk scored in real time. And when you combine that with AI chat, you get the full picture, a governed, explainable user experience that teams actually want to use. It's productivity with accountability, a single platform that connects compliance, IT, and business users under one governance framework. That integration is what truly sets SS and CE apart. We're not just providing tools. We're providing an ecosystem, one that brings governance, orchestration, automation, and AI together in a single secure environment. It's the same framework we use internally to manage regulated workloads for some of the world's largest financial institutions, insurers, and health care providers. So when we say that AI Gateway is the foundation for enterprise grade, responsible, AgenTic AI, we mean that literally. It's built for real organizations with real demands for security, a need to employ the latest AI related technologies, and a desire to scale safely. By embedding compliance and human oversight into every AI interaction, those same organizations reduce risk, accelerate decisions, and realize measurable ROI. That's how SS and C transform AI into a from a potential liability into a scalable, trusted deliverer of growth. Yeah. I'm gonna pass it back to Natalie. Thanks, Ben. Really appreciate that. So really exciting stuff there that we've just heard from Adam and Ben. And if that wasn't enough, then there's more because I'm absolutely delighted to, introduce Ahmed Hosner Tabah, who is the director of product management. And he's responsible for our automation stack, including our AgenTech capabilities. So it's really with great excitement that I hand over to Omid, who's going to walk through what's coming next in the next few months. Thank you, Omid. Thank you, Natalie, and hello, everyone. So far, we've heard about all the capabilities you need to start leveraging to use AI safely in production, and I would like to walk you through some of our high level strategy in how we intend to take this to the next level. We have a major focus on unifying your experience across different products and components and improving the look and feel so that our end users enjoy their time automating faster and easier. You may have noticed these changes in our next gen platform, such as the introduction of the new automation studio, and there were a ton of more changes coming in the next few iterations. I think by now, you've learned that here at SS and C Blue Prism, we're not interested to just jump on the hype train with experimental features and capabilities. We understand that AI agents, despite being powerful new tools in the automation landscape, need to work in harmony with the rest of your workforce, and that's why we're going to introduce a new lightweight workflow orchestration system that help you define the flow of work between humans, digital workers, AI agents, and your external systems using serverless execution. We're also enabling the capability for you to define and deploy your own AI agents in our new agent builder, unlocking those use cases that require more advanced reasoning and expertise beyond what is delivered by digital workers today. You'll have the option to leverage the AI gateway to safeguard your AI agents with advanced guardrails and monitoring. Your workflows and AI agents won't be effective without the native ability to automate external systems using API automation capabilities, and that is why we're introducing an open ecosystem for you to use hundreds of pre built connectors and the ability for you to create, store, and centrally manage all the custom connectors your organization needs for end to end automations. All of this results in what we're calling an automation fabric. The unification of humans, digital workers, systems, and AI agents in one central command hub. Let's break down how this automation fabric plays a central role in your automation journey. Our central node is the new agentic workflows that acts as a glue holding the logical flow in which your automations are run by digital workers, AI agents, and humans. Through a wide set of pre built connectors, you can integrate your external systems and other SS and C products and connect them to your automation fabric. Unlike the competition, we have paved the way for you to get started with these capabilities as soon as they become available without having necessarily to commit to migrating your entire automation estate in one go. This means that you can use our new agentic workflows and AI agents in harmony with Blue Prism Enterprise version 7.4 and later and next gen digital workers. This was only a quick teaser on what is coming next, and we're excited to bring these new capabilities to you as part of an early access in the 2026. I'll invite you all to tune in on our upcoming roadmap show on November 6 to learn about all the details in our plans and watch these capabilities in action. Thank you. Okay. So re hopefully, you are as excited as we are about some of the things Omid spoke about there in particular, the introduction of an agent builder to enable organizations to build agents themselves and also include those in orchestrated AgenTek workflow. So tons of new stuff that is coming down the line, so please do keep your eyes and ears open for more. And as always, if you want to know exactly what is is new and what's what's coming, and has just been released, please don't hesitate to go to our what's new page because that is kept up to date with some of the latest releases and product introductions, including the ones that you've heard about today and some more to beat. So with that, hopefully, you are you have heard a lot of exciting things today, and you're looking forward to continuing your journey with SS and T. But if we could leave you with three things today, in terms of how we can help. Just remember this. One, we want to help you to deliver proven impact, not just, organizational hype. We want you to leverage governance that helps accelerate your AI programs rather than slowing them down, and we want you to be able to have AI that delivers, not distracts from your core organization transformation. So with SS and C Blue Prism, hopefully, we're not helping you just adopting AI. We're helping you realize the value much faster and much safer and in a way that drives lasting impact for your organization. If your technology partner can't demonstrate to you tangible ROI results, then please stop, avoid the hype, partner with someone who can help. And as Ahmed said, we really look forward to you joining us at our roadmap webinar on the November 6. So looking forward to seeing you all there, and thank you very much for joining today.