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Unlock the potential of Generative AI Service CRM with Ascendo AI’s seamless Slack integration. Ascendo uses AI to analyze conversations, suggest solutions for agents, and build knowledge bases for better self-service and agent interactions. Discover the future of customer support today! Arm your agents with the help they need when they need it. Knowledge Intelligence Resolve issues as they arise. Know what questions come from customers and how agents are responding. Connect with an existing knowledge base or automatically create new knowledge from conversations. Improve only the knowledge that is required to meet your Self Service and agent quality goals. Derive Trends, Risks, Sentiment, and Patterns Real-time Voice of the Customer Automatically triage, tag, categorize and prioritize issues, solutions, and root causes across all Slack conversations. Get real-time Product Feedback, Knowledge Intelligence, and training information to automate Support Operations. Agent Assist wit hin Slack This integration lets your support agents use Ascendo’s self-learning engine with the/ask Ascendo slash command to get the solutions your customers could be looking for, making it a simple and powerful tool for agents handling customer queries. Run Support Operations on Slack Track and resolve issues that arise on Slack from within the conversations. Decide if you want your customers to get self-service or agents to get help or both from within Slack. Learn and create knowledge automatically from everyday interactions. Get the entire company involved so customer-facing teams are armed with the latest information to help customers. Use Slack for complete Support Operations Install app for Slack READY FOR PROACTIVE SUPPORT? Connect Now First Name Last Name Email Phone Submit Thanks for submitting! Ready for Agents, Customers and Leaders Install Guide A simple no-code method to install the Ascendo application in your Slack workspace.

Explore our field service AI platform at Field Service USA 2025. Learn how AI-enhanced tools boost efficiency and resolution speed. Field Service USA April 22–24, 2025 | JW Marriott Desert Springs Resort & Spa, located at 74-855 Country Club Drive, Palm Desert, CA 92260 Pre-book a 1:1 Executive Meeting With Us Request a meeting We look forward to meeting you at Field Service USA 2025, taking place April 22–24 at the JW Marriott Desert Springs Resort & Spa in Palm Desert, CA. Visit our booth to experience how Ascendo is helping leading field service organizations transform operations with AI-native innovation. Get a live demo of our Field Technician AI Bot — enabling techs with real-time access to manuals, parts directories, and activity history for faster, more accurate resolutions. Learn how advanced context filtering by resolution type and our integration with ServiceNow empowers frontline teams with Generative AI, intent analysis, and sentiment insights. Don’t miss our exclusive sessions featuring EDFR NA’s Chuck Kellen and Melissa Hogan, who will share their success stories with Ascendo in two separate live panels. Book time with our executive team before the event — no sales pitch, just real transformation. Meet Our Speakers Christopher Dickerson Vice President Service Planning & Logistics, Infinera Chuck Kellen Associate Director, Continuous Improvement & Maintenance Digital Product Manager, Asset Optimization, EDFR NA Melissa Hogan Sr. Director, Digital Transformation & Continuous Improvement, Asset Optimization, EDFR NA Trusted by Chris Dickerson VP Service Planning and Logistics Optimized Inventory, Improved SLA We are able to achieve a 95% SLA with hardly any firefighting. We proactively manage and optimize the inventory of 5,000 unique spare parts across 300 depots. Payam Karbassi Global Service Segment Leader MUST HAVE solution for customer support Easy to setup and configure. The game-plan for remote as well as field support prediction results are right-on. Ascendo AI provides excellent support for initial setup and on-going collaboration. We needed an advanced tool to realize labor and material cost savings while maintaining enhanced experience for customers and partners. We are on the path to realize improved benefits across our product portfolio. Kevin Yang Senior Data Scientist Superb models that provides results With Ascendo AI, we are able to enhance patient experience and predict outcomes. The tool also calls out Top trending issues from all of the Voice of the Customer interactions to provide Product Feedback. Ascendo AI helps us to predict patient churn so we can proactively address to improve patient treatment and therapy. Being proactive will enable us to stay as a market leader. Viktor Kehayov VP, Product Engineering SAP FSM Leveraging Enterprise Data: Our SAP FSM with Ascendo AI Our SAP AI-driven FSM solution, alongside partner offering Ascendo AI, is well-equipped for finding reliable solutions using existing data in SAP and other knowledge content. Brenda Guardado Senior Director Customer Success Innovative product offerings and amazing support The Ascendo AI team is extremely pleasant to work with. They are responsive, they show they truly care about your experience with their product, and were quick to iterate on any feedback provided. Ascendo AI has an amazing product offering that integrates well with shared Slack channels and empowers our team to seamlessly support customers effectively and accurately. Cedric Prevost Service Delivery and Infrastructure Leader for Life Care Solution Must have solution finder tool for Field Service Ascendo AI is extremely easy to add new products. We like the design and the easy of use in terms of getting the solutions to customer reported problems. Ascendo ai is helping to support Field engineers doing field and remote support. This is a very useful tool to support new hired field engineer less experience than the others. Alexandra Pham Senior Customer Success Manager Ascendo AI is a must have for CX! Ascendo AI made it so easy to bring Trending issues, Knowledge intelligence, Quality and Voice of the Customer across our support channels. We used Slack as a channel and Ascendo AI helps learn from the interactions. Automatically coming up with Trending issues that we can feed back to the Product team. It is like having Voice of the Customer in our back pockets. Brenda Bernal Vice President AI-Driven Solutions and Knowledge Creation Ascendo AI solves 88% of customer issues immediately and for the rest, guides us by helping to create knowledge. Atad Bronstein Director of Customer Success Transforming Knowledge Dynamics Anjuna’s Product Support team uses Ascendo AI to quickly assimilate knowledge and rapidly resolve new support requests across a variety of customer deployment environments. Our products are highly-technical and always-evolving, and Ascendo AI helped us achieve and even overachieve Support KPIs such as: reducing Time-To-Resolution and increasing the number of Resolution-In-First-Touch. John Heald Global VP, SAP CX SAP and Ascendo AI Partner to Enhance Customer Support Happy to celebrate this news about having Ascendo.ai on our SAP Store. Looking forward to working with them and our great customers, empowering resolution at every point and channel of service. Stacy McQuestion Sr. Logistics Analyst Absolute must for managing customer support SLA Ascendo AI is so easy to get a proactive measure of where we need to stock spare parts to address potential customer demand. We have very stringent and critical SLA requirements and Ascendo AI helps us to take proactive actions. Infinera products are used in mission-critical environments, and it is crucial to provide top-notch customer service while optimizing for cost. Ascendo AI helps us to do just that. Kiet Dam LCS Service VCP & Product Quality Leader Ascendo AI is transforming field service team delivery The tool is very initutive to use and navigate. The tool also constantly improves upon itself as additional data gets uploaded or as users give input. It gives our field team a great gameplan to resolve customer issues based on previous service records. We are trying to improve labor and parts efficiencies along with reducing customer downtime. We have realized labor and material savings year over year. Deovrat Vibhandik Lead Engineer Service Engineering Best Predictor tool for support and troubleshooting for Field Engineers Easy interface that provides the best solution along with guidance on root cause and solution areas. We can also get the best technician to provide guidance on the fix. Ease of troubleshooting and clear gameplan for our field engineers to solve customer issues. We are getting benefits on both labor and material cost. Matt Mitchell Technical Support Principal Engineer From Reactive to Proactive: Ascendo AI Revolutionized Support Ascendo AI has transformed the battleground of technical support, turning what was once a two-week reactive struggle into a one-day proactive plan, ensuring the right solutions (activity and part) are in place before they're needed. Ahmad Azlan Isa Country Senior Engineer Search Resolution Feedback Ascendo AI is helping resolve GE customer devices and systems problems. I appreciate the search engine, which organizes products into distinct groups. Chandrasekar Elongovan Senior Quality Manager Technical Service APAC Deeper insights on the field usage of our equipment We have complex medical devices and we perform varying types of preventative maintenance (PM). Ascendo AI brought out the insights into the cause and effect of such PMs and the trending issues using inference models. These insights are helping us to make proactive steps in the way we provide services. With the recommendation from Ascendo AI we are able to proactively determine PM offerings. James Fitts Director of Service Planning Perfect Solution for Reverse Logistics Spare parts Support Ascendo was Flexible to support our unique business needs. We are able to address our SLA requirements proactively resulting in enhanced Customer Satisfaction and Less Escalation. We are able to predict how much parts we need, where we need it, in time to meet our SLA. With our current Supply Chain Constraints, Planning moves to the forefront of our customer experience. Amitkumar Parihar Customer Success Manager Easy to use and clear prediction results. It is user friendly Easy to connect with CRM data. We can add knowledge enrichment at any point of time. Ascendo AI self learning engine provides best results for customer support team. We introduced new products and also support legacy products, it is so much easier to use Ascendo for new users to ramp up with products. Using Ascendo AI is like Google search for customer support. Amy Waranauskas Service Product Line Manager Easy to use reliable platform with a robust roadmap Ascendo AI has collaboratively worked with us, meeting with us every week to discuss status and collaborate on new ideas. The use case I am involved in is a spares planning application including predictive algorithms. The Ascendo AI application has contributed to significant improvements in SLA compliance for these services. Industry leaders soar with Ascendo.AI It is your turn to elevate with AI agents! What to Expect AI Advisory Lab (Invite-Only) Hear directly from our CCO and real-world customers. The AI Advisory Lab is a closed-door session designed for executives who are curious, cautious, or considering AI. In this invite-only space, we bring together enterprise leaders like EDF to share firsthand how they’ve approached AI transformation. You'll also hear from our Chief Customer Officer — providing strategic insight and front-line perspectives. EDF Panel Spotlights EDF North America’s Chuck Kellen and Melissa Hogan take the stage — separately — to tell their AI story. Chuck Kellen (Associate Director, Continuous Improvement & Maintenance Digital Product Manager, Asset Optimization, EDFR NA) and Melissa Hogan (Sr. Director, Digital Transformation & Continuous Improvement, Asset Optimization, EDFR NA) are two voices you don’t want to miss. In two distinct panels, they’ll share how EDF NA deployed Ascendo.ai to improve frontline responsiveness, optimize cost, and build trust between tech and the field. Melissa is also one of the few senior women leaders in Service today, a powerful and rare perspective on AI, leadership, and workforce empowerment. Nokia Boardroom Join an exclusive, off-floor executive session with Nokia and select Field Service leaders. We’re facilitating a private roundtable between global leaders like Nokia and invited execs considering AI adoption at scale. This isn’t a product pitch, it’s a strategic conversation on how enterprise service organizations are evaluating AI, operationalizing it, and driving success. Booth Demos: AI in Action Real-time, real-world demos of our AI-native platform built for Field Service. Swing by our booth for an interactive experience of how Ascendo.ai helps complex organizations like EDF scale faster. We’ll be showcasing our integration with SAP FSM, delivering fast time-to-value and real automation on day one. Our Messaging: Empowerment > Replacement It’s not about replacing humans. It’s about making them superhuman. Our AI-native platform is designed for automation, frontline empowerment, and cost reduction, with a strong focus on real-world integration. We’re here to differentiate from legacy vendors with a modern, measurable, and people-first approach. Press, PR, and Real Recognition G2’s #1 User-Recommended AI Platform for Field Service and more. We’re not just talking about AI — our users are recommending it. Backed by G2 recognition, strong LinkedIn storytelling, and press coverage tied to real deployments (like EDF), we’re building a brand on results, not just hype. Live Engagement That Goes Deeper Let’s talk live, face-to-face, human-to-human. We’re not sending SDRs. We’re sending our execs, our product leaders, and real customers. Whether it’s a spontaneous chat on the floor or a scheduled 1:1 meeting, we want to understand your challenges and share how others are solving theirs. Awards & Achievements We rely on the power of data, and so can you. All G2 ratings Ascendo is extremely easy to add new products. We like the design and the easy of use in terms of getting the solutions to customer reported problems. Cedric Prevost Service Delivery and Infrastructure Leader for Life Care Solution - Europe & Africa at GE Healthcare Pre-book a 1:1 Executive Meeting With Us Request a meeting

Master customer engagement with Slack! Our webinar unveils expert strategies for onboarding, communities, premium service & more. Learn real-world solutions & actionable tips to skyrocket customer satisfaction. Register now! Harnessing Generative AI with Slack for Knowledge Intelligence April 15, 2025 - 9 AM PST Elevate response times, boost collaboration, and skyrocket customer satisfaction with Slack, the ultimate communication platform for businesses. Join our insightful panel discussion and discover how to leverage Slack as a game-changer for your customer experience. Effective Strategies for Utilizing Slack Gain expert insights on the most impactful ways to integrate Slack into your customer engagement strategy. From Onboarding to Premium Service Explore the diverse applications of Slack, encompassing onboarding support, fostering vibrant customer communities, and managing exclusive premium subscriptions. Real-World Examples & Proven Solutions Hear directly from industry leaders about the challenges they've faced in customer communication and the winning strategies they've implemented using Slack Actionable Tips to Enhance Customer Interactions Take away practical knowledge and actionable steps to immediately improve your customer engagement efforts. What will we cover? Don't miss this opportunity to learn from the best and unlock the full potential of Slack for fostering exceptional customer relationships! AI Agent Assist in Slack Agents have the capability to employ specific slash commands, including /askascendo, /ascendomax, and /onfly, to swiftly retrieve solutions and effectively troubleshoot customer issues utilizing Ascendo within a fraction of a second. Knowledge Creation in Slack Our system empowers agents to contribute solutions to the knowledge base, fostering continuous improvement in knowledge and skills. This commitment to growth ensures an exceptional experience for our esteemed customers, irrespective of the agents' preferences for solutions. Issue Management in Slack As an agent, you have the capability to access and view all the issues consolidated on a single page. This feature allows you to modify the status of the issues as needed and provides a convenient way to swiftly navigate through the various items. We have Powerful demos for enhance the understanding of Slack Use Case If you find the use cases intriguing, you can discover more on our tour page. Learn More Registration Register Now I agree to my contact data being passed to SAP to contact me as a follow-up from my attendance of Lunch and Learn – Enterprise Service Management. Use of your contact data is governed by the SAP’s Privacy Policy. Entering your personal data above and clicking submit constitutes your consent for Ascendo AI to process your special categories of data as described in the Privacy Statement. Yes, I agree to let SAP make my event profile publicly accessible to event attendees and to display the public attributes of my profile on SAP event websites and mobile applications. Do you have any dietary restrictions? * Yes No Will you be joining Online or In Person * Online In Person Country* Department*

We believe in the automation with power of data which helps in Customer Service. After years of optimizing the supply chain, and innovating new products we discovered an efficient way to transform Support processes, to make your customer journey satisfying. ​No more guesswork on what the intent, relevance, sentiment, and context are in every interaction with our knowledge management and Artificial Intelligence based system. "The only way to do great work is to love what you do" We impact Lives and Experiences with Customer Support Agents Our Purpose We have extensive enterprise experience developing and implementing technology & processes to drive transformation and operational efficiencies. We believe in the power of data. After years of optimizing the supply chain, innovating new products, and improving the customer experience for OEMs, we discovered an efficient way to transform Support processes. We can extend the same lean manufacturing principles to deliver Just-In-Time support by turning data into actions and that too without our customers needing to employ complex programming or data scientists. That's why we founded Ascendo. Our team comes to work every day thinking machine learning, breathing data science, listening to the customer-specific business rules, and feeling & striving towards our mission - Transform how our customers deliver support to their end customers. Sign up for free Our Culture We at Ascendo, believe in healthy culture with full dedication to work and fun. We ground to people who work hard, be real, feel proud, and stay humble. While the most talented engineers and leaders are thriving to give the best customer experiences, we treat ourselves with something more. You may not be a perfect match, but our team can shape you to be the best. If this sounds cool to you - then we hope you'll join us! We're looking for people to join the team who are as excited as we are to help build the product that empowers the future of customer support and experiences. Dive into the world of human-machine interactions, empowering the experiences while reducing the effort and time for super complex issues. We look forward to someone who considers the product as his goal and swims through with us in building the best possible product that leverages the latest technologies for good. Learning never stops, and we take care that we are updated. Come join us and make wonders with AI and ML. The team that makes it happen. Our team is comprised of extremely talented designers, developers, managers, marketers, quality analysts, and writers. Below is a list of the folks we have leading the Ascendo Crew. Co-President & Partner Melissa Burton I'm a paragraph. Click here to add your own text and edit me. It’s easy. Just click “Edit Text” or double click me to add your own content and make changes to the font. I’m a great place for you to tell a story and let your users know a little more about you. CFO Vince Taylor I'm a paragraph. Click here to add your own text and edit me. I’m a great place for you to tell a story and let your users know a little more about you. CEO Harold Colby I'm a paragraph. Click here to add your own text and edit me. I’m a great place for you to tell a story and let your users know a little more about you. Director, Legal & Operations Tilly Evans I'm a paragraph. Click here to add your own text and edit me. I’m a great place for you to tell a story and let your users know a little more about you. HR Lead Richard Jones I'm a paragraph. Click here to add your own text and edit me. I’m a great place for you to tell a story and let your users know a little more about you. Project Manager Lucia Behar I'm a paragraph. Click here to add your own text and edit me. I’m a great place for you to tell a story and let your users know a little more about you. Sr. Project Manager Mark T. Wright I'm a paragraph. Click here to add your own text and edit me. I’m a great place for you to tell a story and let your users know a little more about you. Sr. Project Manager George Wood I'm a paragraph. Click here to add your own text and edit me. I’m a great place for you to tell a story and let your users know a little more about you. Lead Superintendent Olivia Clarke I'm a paragraph. Click here to add your own text and edit me. I’m a great place for you to tell a story and let your users know a little more about you. Marketing Manager Nathan Wise I'm a paragraph. Click here to add your own text and edit me. I’m a great place for you to tell a story and let your users know a little more about you. Our Office in Palo Alto Ascendo.ai 228 Hamilton Avenue, Floor 3, Palo Alto, CA 94301 Our Office in Chennai Ascendo.ai 8, Lalitha Nagar First St, Santhome, Mylapore, Chennai, Tamil Nadu 600004 Anandha Kannan Software Engineer "Young and Sensible" Anurag Data Scientist "Self-Driven" Arun Technical Support Engineer "Resilient Achiever" Gokulakrishnan Venkat Front End Engineer "Mr. UI Perfect" John Peter Data Scientist "Pioneering and Decisive" Karpagam Narayanan Co-Founder "Self-Made Woman" Khalisaran Kannan Head of Engineering "Empowered Catalyst" Lhavanyadevi RN QA & Customer Success Support "Supportive 24/7" Ramesh Kumar Sahu CX led Growth Strategist "Our Best Closer" Ramki PitchuIyer Co-Founder "Jack Of All Trades" Naveen Srinivasa Data Scientist "Transforming Insights" Prajeeth Muthukumaran Software Engineer "Front-End Visualiser" Do you have a curiosity to learn? Are you responsible and accountable to deliver what you promised? Are you not afraid to make mistakes? But ready to learn so the same mistake doesn't happen again? If so, you will be a great fit for Ascendo! Explore more Join Our Team We are hiring! Rohit Krishnamoorthy Lead Engineer "Visionary Reader" Randy Chinn Chief Revenue Officer "Revenue Innovation in Action" Vrinda Mathur Data Scientist "Our Great Find" Our Office in Chennai Ascendo.ai 8, Lalitha Nagar First St, Santhome, Mylapore, Chennai, Tamil Nadu 600004

Speaker: Sarah Mckay and Rohit Menon Leaders discuss automation, upskilling and the next era of support. Speaker: Sarah Mckay and Rohit Menon April 9, 2025 Previous Item Next Item Join host Kay in a compelling conversation with customer experience veteran Sarah from Concentrix and tech expert Rohit as they explore the evolving landscape of customer support. From the early days of phone and email support to today’s AI-augmented workflows, this discussion dives deep into how technology is transforming—not replacing—the human element in service roles. Sarah brings over 18 years of frontline leadership in BPO, offering real-world insights into upskilling, team dynamics, and shifting service expectations. Rohit adds a tech-forward lens, breaking down how engineers and AI can collaborate to create smarter, more efficient support systems. The duo also explores how generational shifts—like Gen Z's dislike for phone calls—are reshaping communication norms. Whether you're a CX leader, tech enthusiast, or someone tracking the future of work, this video offers fresh, optimistic perspectives on what it takes to thrive in a rapidly evolving support environment.

Explore how large language models (LLMs) like ChatGPT can be used to improve customer support. Ramki, co-founder and CTO of Ascendo, discusses the limitations of ChatGPT, which include lack of real-time data and factual accuracy. He contrasts this with Ascendo's LLM, which is trained on enterprise-specific data and leverages human feedback for continuous improvement. ChatGPT and the future of Customer Support | Transcription Kay - Welcome to the experience dialogue. In these interactions. We pick a Hot Topic. That doesn't really have a straightforward answer. We then bring in speakers who have been there and seen this but approached it in very different ways. This is a space for healthy disagreements and discussions but in a respectful way. By the nature, of how we have conceived, this, you will see the passionate voice of opinions. Friends having a dialogue and thereby even interrupting each other or finishing each other's sentences. At the end of each dialogue, we want our audience to leave with valuable insights and approaches that you can try at your workplace and continue the discourse on social media channels. A little bit about Ascendo, it is addressing optimization of support to operations within enterprises so that they can serve their customers better. We enable enterprises to optimize workflow for the agents and provide dashboards for insights on risk, churn analysis, and visibility for senior managers. We are revolutionalizing support ops in the same way DevOps and RevOps have transformed other areas of the business. In the last three years, we have created a G2 category and are ranked #1 in user satisfaction. We are very proud to be loved by our users, and now with the topic ChatGPT and the future of customer support. There is excitement on many Tech and business channels on ChatGPT from OpenAI. It had a lot of adoption within the first five days of its getting released. We've been following OpenAI and GPT 3 for some time. We will discuss the technology, explore its impact on customer support experience space, it's possible limitations and opportunities. So join us and bring in your questions to LinkedIn and Slack channels. Now it is a pleasure to introduce the speaker. He is the co-founder and CTO of Ascendo.AI. Ramki comes in with deep data science, and support background.He ran managed services for Oracle Cloud, created a proactive support platform for NetApp's, multimillion-dollar business and is respected for both his mathematical and business thinking and data science. At Ascendo, his mission is to give meaning to each and every customer interaction and elevate the experience of customers and support agents. Welcome, Ramki. Ramki - Thank you Kay, Glad to be here. Kay - So we can start with the basics Ramki. What is actually ChatGPT? Ramki - You know, I create a slide that kind of shows what ChatGPT could be, you know, and I know that it kind of comes from the comic strip but now let's talk about what ChatGPT is. It's essentially a modern variation of a chatbot. We all know and we've been living with chat bots. Typically the chat bots require you to set up the rules, based on a question that the person might ask it basically has rules that match the contents, and the whole thing happens in a coordinated way. The ChatGPT, difference is that instead of only knowing a little bit of whatever it is, for the website that you are on. Essentially, it's kind of a robot ChatGPT knows, just about everything, and it's more articulate than the average human. So it's kind of comes up with- Hey, I've consumed all the internet and I can provide answers in a conversational way. Let's talk about the technicality of it. It's essentially a language model. It's been trained to interact in a conversational way, it's a sibling model to the instructGPT which was trained to follow an instruction on prompt and provide a detailed response. What I mean by that is, essentially it remembers the thread of your dialogue and using the previous questions and answers to inform, what the next responses could be. The answers are essentially derived from the volume of data that got trained on which is what we had on the Internet. So that's kind of the technical answer for it. You can think of it as it understands the conversation, it consumed all of the internet. It knows the history of your dialogue and it can prompt automatically what the next language sentence could be. Kay - So we've been following ChatGPT, GPT3 for quite some time, right? There was GPT 3, and then now ChatGPT, tell me the difference, please. Ramki - Yeah,I said it's a language model, right? So underneath this nothing but it's using the GPT. Its GPT is the Transformer model. What it means is it's predicting what the next words would be based on what it is seeing. The difference is GPT3 uses 175 billion parameters in whereas to instructGPT which is kind of a 1.3 billion parameters. You can look at it as a hundred times fewer and it's still performing quite well because it's the way it got trained but the same time You know, everybody knows that excitement is great but OpenAPI warns, you know, Hey not all the time, the answer may be correct. So you got to be watchful of what you're seeing and you have to inculcate what it is saying and then see in your own form, whether it makes sense or not. Kay - So there are a lot of people who are new to data science, also here Ramki. and when you talk about Transformer model, we are talking about transforming the learning from one to another or transforming the learning. Correct? Would you like to add any other definition for Transformer? Ramki - Transformer was the kind of technical term essentially it was done. You know, you can kind of look at all the words in One Sweep, and the training time is less. So you are essentially looking at the whole sentence or whole information and taking the mass in one set of tokens and understanding the relationship and then you can kind of predict what the next one would be. So it's a combination of doing the training faster and having fewer parameters and doing it with a lot of content and also making some kind of a model that really reinforces the better behavior of which is correct and guarded better. Kay - So a lot of people have interacted with ChatGPT. Right? It's a, you know, they ask a question and they type a piston in and use the content that gives a result and they give feedback and based on how it's trained. So, in a way, it's kind of Google but not Google also. So can you describe a little bit more? Ramki - It's gone, in a way that, we all go to Google and say, hey, I want to know something. Then we go search and we look at the results and we kind of look at them. What makes sense, and put our thoughts into it and make sense out of it, right? The most notable limitation that you're going to find is that this ChatGPT doesn't have access to the Internet. It's basically loaded with the entire content prior to 2021 data-wise. But it can not look at the current image. In fact, OpenAI tells you that. For example, I want to know when my tree train is going to lead, you cannot get it right but you can pretty much ask anything like, Hey, I want to write a poem. I have an issue with this code, does it make sense. Those types of things one can ask and it can be ask it to fix it. In fact, The very first day was out. One of the teammates asked, hey, I want to write a poem on Ascendo and it kind of actually did a pretty decent job. You know. Kay - I would love to see it at the end, so I was playing around with it, and I will share that also in a bit. So, now the adoption of ChatGPT has been pretty exponential, right? So we see millions of people using it. What Are some of the key differences that you would point out in terms of its output? Ramki - Recently, I was listening to several things, one of them being Steven Marsh. He recently, like, even last week, wrote an opinion column in the New York Times in. You also had a podcast before that with the intelligence quiet, a British podcast media. He's been using similar tech for some time. It's not like we just looked at this and said, yeah, you looked at a different variation not opening another company, and then you looked at them as well. He says it in a very succinct way, he says ChatGPT is a great product that he calls, it can provide a filler response by the filler response means it's not junk, it's not a trivia, it leverages on how people are taught to write essays in a structured manner, you know, we have an opening sentence, kind of things like that. The key point that he's bringing up, is the ChatGPT does not have an intention, it's not like an author, you know, I want to, I have a will I want to want to like what when you write an article you're thinking about the point that you want to convey, right? You want to say this, I want to be able to show that to you. I want you to know that, that's not what you're going to be getting. ChatGPT is a kind of a filler, but it gives you a starting point. One can use the starting point and add the rest of the information that are from your Vantage standpoint. We may be entering an era of doing things differently. Like when we started with the internet, right? When the internet came, then Google came, and then, you know, yeah I remember going to some places, where people essentially say, Hey the computer tells me, this is what this must be the truth, kind of thing, so the open source came all of them, right? So that's the same way here. We are going to be entering a different era where you may be asking, and it gives you some responses that use that as a starting point and go from there. Kay- So some could also say that a GPT3 is the base model and ChatGPT is the bot version or the conversational version of using GPT3. That's already indexed and modeled with internet data. As you mentioned, September 2021. Will that be a correct statement? Ramki- It’s kind of you know, Yes and No. I know the GPT is the base, ChatGPT is not using a bot version of GPT3. It's essentially a smaller model, right? It's created by fine-tuning GPT3. In other words leveraging what GPT does it has to offer a mix of its own bot kind to give this whole intelligent conversational experience.Does this make sense. Kay- Yeah, absolutely. So you know, we know RPA came in, right? So that was the first iteration of introducing AI and I Love to equate it to the autonomous driving experience which will also bring up in a sec. So the RPA came in and it became too much rules-based and very cumbersome to maintain, but RPA was very hard and then that got faded away. Then came chatbots, and I remember at one point, we were counting 318 ChatBot companies and they were the chat versions of the RPA, which again was very rule-based and you had to pretty much codify the question and answers and stuff. And they were very well used within the customer service context. So tell me a little bit more about the Bots in the customer service context. Ramki - You know you're right there. A lot of chatbots. In fact people think when we know when you say have a question they always think bot as one of the things but they have a lot of Baggage, you know, companies have tried with limited success to use them, instead, of humans to handle customer service work. There is potential in these bot where you can kind of alleviate the pressure on answering some mundane questions. But the thing is yesterday was like, you know, recently 1700 American sponsored by a company called Ujet whose technology is handling customer contacts. What they saw was very interesting. 72% of the people found Chatbot to be a waste of time that's a very serious thing. You know, the reason is the biggest challenge people want to have is they don't like the feel of having to work with the robot. When I talk to many of our customers you know when they get you to know, yes there is a potential for doing a lot of self-service self answering but the reality is as soon as you give the option to talk to somebody or something, they just click that, you know, that's what people want. The reason is they don't Like to work in a bot-like environment. Kay-They want a answer. Right? Ramki-Exactly. Kay - You know which is like, I'm having an interaction, why can't it be an answer? Why does it have to be a conversation with a machine-like thing which has to be maintained and codified extensively? and on top of it, I don't even want to go in and extend this process ultimately creating a ticket, right? So Yeah, elaborate. Ramki - If you look at the ChatGPT right, on the other hand. It sounds like a human, you know, and it is of one, what you are saying to form the response. It is not pre-coded with a response. It really thinks off what you're saying and that kinda makes the whole discussion and responses more conversational but doesn't make its responses always right. You know, again OpenAI says that. You have to look at the response and make your conclusion. Kay - You also talk about ChatGPT’s initial, audacious claim. So elaborate a little bit more on that. Ramki - I'm going to share one slide on this. You know, it's an interesting lie that you will get a chuck lot of it.In fact, I went and asked this to ChatGPT. Hey, tell me about the customer support kind of thing. So we ask this and first, you can you know, I just put the same response, what I got right on the slide. It first makes a very audacious claim. Hey, it is not capable of making a mistake so that's a big thing but at the same time, it also did admit that it cannot help with real-world tasks. So it's kind of that is essentially what I want the readers to understand. It will appear that it is not making a mistake, it's giving the answers. But at the same time, you have to know that, you know, it may not have the ability at least as of now, to provide customer support or the real-world task, you know, where's my training? What is the issue? Because in a real customer support scenario, things change more normal things that things are going to be relevant now, and it may not have all the answers. So that's where the big difference is, I would see. Kay - There is a question from Shree. He's asking, what is current state of art in ChatGPT integration with KnowledgeGraph enterprise solutions ? continues saying, particularly around Particularly around Explainability for conversational problem solving , in domains that have high compliance bars ( like healthcare or finance )? Ramki - You know you can't just Wing, you know if you look at it right when you and I are having a conversation we're going to use of the knowledge that we have gained and we are going to just tell you and there is no fact-checking. So we got to be conscious of that. So just because you get a response and in fact, the response may look somewhat legit and it doesn't mean that it is right? Especially when there is a complaint kind of a thing as a mod so I would strongly suggest it. In fact, you know about the openAI will in fact concur with this type of thing. You got to, you know, it's giving the answers based on what it had been trained on, but fit is for Real World past and something that you need to do, contact the customers and do contact that particular customer support and get the answers. It's, they're saying, so that's what ChatGPT itself with that, you know it is audacious to say, it will never make a mistake, but it doesn't make a mistake and it also tells you that you have to be at your own. Kay - Yeah, and it's good that the model actually understands its own limitations and claims its limitations, and it's by us too since, you know, I'm just bringing it up because there is the explainability component of it. So absolutely. So, let's now that we talked about Transformer models, we talked about GPT3 and ChatGPT. Tell a little bit about how Ascendo works. Ramki - You know, if you look at Ascendo.AI. At the core it also uses the Transformal model. Well, we essentially developed our model based on the domain expertise that we have, you know, many of our key people come from there, come from customer support or customer service background. So that's a great value because we know how the support model Works. How large companies' technical support organizations should handle even smaller ones as well. And we know the nuances of finding the answer for a customer question and issue. Sometimes, be a simple and elaborately explained to me what it is and what the product test is. Sometimes it is actually an issue. I'm facing, I'm doing this, and I'm facing an issue. What should I do? How can you help me? kind of thing. Our Transformer model essentially looks at the knowledge and the other data point that we have within the company that we are that we have implementing or we are basically providing Ascendo service on top and it's looking at all the content within the company and to evolve, what should be the answer. For example, there may be a new issue blowing, Right? it probably never happened before, but it's coming. There may be new knowledge that got updated. You know, somebody found an answer and the dots or maybe there was a bug that came in, and then somebody answer it, it became a knowledge, all these things are happening as things go by, then maybe these things in some similarity, there are some similarities with ChatGPT because we also use as kind of human feedback to make sure that we can constantly evolve and self-correct self learn, right? That part of it is very similar. We are using actual data and we are also evolving and with actual factual data, not from the entire internet to provide an answer. Kay - Very specific to the Enterprise, very specific to the product, Etc. So the analogy is very similar to the autonomous engine auto driving. Right? So we start with giving the Triggers on predictive actions, escalations impact, risk intended context, and all of that. Then our agents and leaders still make the decision on what they use and when they use it. So in a way, we automate the data aggregation, aspect of humans, maybe I would, I always equate it to what an engineering calculator did for the basic calculations but on an advanced scale so it does help remove the biased. It enhances collaboration, even when people went, whether people are together or remote and it also helps with faster problem-solving. So essentially, we are automating support ops, like, whatever dev-ops and rev-ops are doing. Back to chat GPT.So, the challenges explain a few challenges of ChatGPT, like the media. I kind of alluded to writing. Ramki - One of the biggest issues that we are all going to face. It happened even with the internet, right? When you see something, you may actually believe it. The way we probably get unknowingly got caught by the early days of the Internet, just because something is said multiple times, it appears opinions may drive the truth. The fact-checking asked to be will be on the Forefront. Unknowingly, someone keeps repeating the same thing or, you know, gets Amplified through multiple things. And then information comes on top. People may think that is the truth and it may, you know, actual truth will be hidden, right? That's where we have to be watchful. We have to be careful how these things happen just because it says something so nice and it, you know, feels correct and eloquent. It should not be that, it's always right. And we have to remember but it's a nice way of saying things but it is not the truth to have to do, a fact check. Kay - Yeah, a model is as good as what we feed it in and ChatGPT is fed with internet data and there is a lot of information that needs fact checking whether it is from humans or a machine and it's we at Ascendo we always talk about metrics versus data? Data helps say the story. So from a story standpoint aggregating all of this customer data and bringing out an ability to say, a story is something that models as Ascendo does, But the actual story is told by humans and not by the data itself. So that's where there is this human connection. So Thank you. I think this has been helpful So I was actually asking to ChatGPT to write about holidays in 2022 and it did respond by saying that the day it has stayed only up till September 2021 cannot write about 2022. But you did talk about the poem, it wrote about Ascendo AI, and want to share it, before we end? Ramki - Let me..you know, it's kind of interesting, you know, we basically talked asked it Hey tell me about Ascendo.AI. Like Steven would say it did a pretty decent job, you know, kind of filler information, you can call it. Now you can take it and you can now use this and can just change it the way we want to convey it or whatnot, but here it is, you know, it did a great job. I would say, Kay - I like that so let people read it while we're stopping the Livestream. Thank you very much for tuning in and we want to continue the conversation here on the LinkedIn and slack channel. So, feel free to post your questions and comments. What else can we do to help continue this engagement? Ramki - Thanks. Absolutely. Previous Next

Ascendo AI Privacy Filter ensures personal data protection, applying robust obfuscation techniques while maintaining analytical utility. Privacy Filter Implement robust data obfuscation techniques to safeguard personal identifiable information (PII). This ensures sensitive data remains protected while retaining its utility for analysis and processing. Watch Demo 5/5 Ratings SOC 2 certified No credit card required I I Your CRM’s Built-In Privacy Guardian Sensitive customer data slipping into the wrong view? Ascendo AI’s Privacy Filter Module acts fast: obfuscate emails in leads, anonymize names in tickets, hide credit cards in invoices, and redact IPs in logs—automatically. Compliance simplified, risks minimized, trust maximized. Privacy shouldn’t be a chore. Get started with Ascendo Today Contact Us

Speakers: Mo Mckibbin, Ahmad Shabazz Growth Through Support Dialogue Speakers: Mo Mckibbin, Ahmad Shabazz March 10, 2022 Previous Item Next Item An organization that sees its customer service department as a cost center is ignoring a significant opportunity to increase customer loyalty and lifetime value. Software-as-a-service (SaaS) is taking software that you pay a little bit less in the beginning but regularly. Monthly, yearly, sometimes longer depending on the contract. Customer support and customer success teams are the ones that interact much more closely with the customer after the final sale of the contract. “Service to sale” thinking needs to be cemented in customer support. Customer support is now the primary human touchpoint a brand has with buyers! End customers are trending towards self-service during the buying process. This reduces direct personal interaction with sales. When buyers are not able to fix simple customer service issues with self-service tools, customer support is often the first human contact they have with a brand. That makes interactions with support a critical and strategic advantage in building customer loyalty. Every support interaction is an opportunity for a company to build a more personal relationship with a buyer. At the end of customer service interaction, a happy customer can be showcased in a marketing case study, events, G2, or Trustpilot review. Every unhappy customer can be called out for a follow-up to improve a business process, training, or product improvement. Companies that don’t take a revenue-oriented approach to their customer services teams fail to unlock a lot of sales opportunities. Top Reasons why Customer Support is Revenue Customer retention is far less expensive than customer acquisition. Excellent customer support improves public persona and strengthens the brand. Existing customers are more likely to buy from you than new customers. Your customers stay with you longer. Word-of-mouth marketing is the best kind of marketing. Great customer support opens doors for organic partnerships and opportunities. Providing phenomenal product support results in a reduction of overall problems Support is the Voice of the Customer that improves the product drastically. How AI can enable the pivot for Customer support into Sales Today, AI-based platforms show the current and historical sentiment of the customer based on current and historical interactions. They also show product issues that are open to the customer. All this can be used to gauge when the time is right for a support agent to transition into a sales role. A happy customer, a customer who is thrilled after an issue is resolved, a customer who expresses a WOW moment of using a software feature all of this is factored in. When the agent is ready, the AI platform also suggests cross-sell and up-sell opportunities available for the customer enabling the ease of transition and an ability to pull a salesperson in at any given time. This is especially true for B2B sales, where issues are rarely closed in a single call. So the question is- “Should support leaders advocate customer support as a revenue generator?” Here is where you might agree, or perhaps differ- and this is the conversation that Ascendo AI and Support Driven are trying to facilitate!

Proactive field service with Ascendo AI. Our smartTraining system offers real-time training, measures quality, scores on Voice of the technician to boost agent efficiency & deliver exceptional service. Training Identify potential escalations early, empowering teams to address issues proactively. Watch Demo 5/5 Ratings SOC 2 certified No credit card required I I AI-Based system for proactive escalation management The advantage of using AI is that it can help predict escalation before it becomes a bigger issue. The benefit is for the support team to proactively handle customer expectation and sentiment. By doing this, customers in turn are getting much better support experience and value the product even more. No customer prefer escalation to accomplish their goals and in fact, are happy to be working with the company that has proactive support. The churn becomes a moot point. AI based proactive support reduces or even eliminates escalation while serving as a key vehicle for revenue and customer growth. Do a Root Cause Analysis for Every Escalation As soon as an escalation is contained, it is critical to do a post martum debrief. Root Cause Analysis has to be done for not just issue (validating what Ascendo provides) but also for people and process. People aspects primarily include training. Process is extensive that includes looking at whether the right people are in the right role, analysis of product, workload distribution, team collaboration, departmental involvement and even organizational goals. Train Your Agents When an issue is escalated, customers are already angry and upset. They do expect empathy from all the people talking to them. They also want to make sure their concerns are heard and a clear plan to address them in place. They want to make sure their voice is heard and want to see clarity in communication, understanding about their needs, right resources at the right level involved. They also want to see a realistic plan with expected results and timeline. Tools like Ascendo can help with issue resolution but the human element of empathy and communication has to be in place. Get started with Ascendo Today Contact Us

Ascendo's Field Service AI agents empowers humans to resolve, diagnos, troubleshoot and triage issues; it creates new knowledge and mimics human behavior to convert tribal knowledge into unstructured data. Augmented Agent Assist agents where they need and when they need. Automatically learn from the expert to make every agent an expert. Sign up for free 5/5 Ratings SOC 2 certified No credit card required I I How We Do? Ascendo is the expert in every agent's back pocket Ascendo’s Core Engine utilizes state of the art NLU techniques to examine sentences based on the textual information and understands the word co-alignment within the text using Lexical Analysis and Syntactic Parsing combined with Word Semantics. In terms of understanding the context, we do not rely only on key-words. Ascendo uses Advanced Transformers and Attention networks to depict the text in the vector space. With the Attention mechanism and Positional Encoding, Ascendo is able to find context for any position within the sentence. Our models are pre trained on multiple customer tickets, cases, reviews and SRs and also get fine tuned based on customer’s datasets. This helps to understand text representations pragmatically, where problems can be linked to new problems in the same space, based on the context's relevance. Learn More Establish Connection Ascendo establishes connection with existing CRM, support data and historical service data, responses, knowledge bases, and bug database are ingested. Transforms information into multidimensional adaptive schema. Semantic Inference of data Ascendo engine organizes data to symptoms - problems - root cause and solution. Automated data pipeline, cleaning, organizing across many types of products is what Ascendo excels at. Recommendation Engine Looks at the dimension of problem context, solution effectiveness, recent solutions, and Provides top solution(s) for the root cause which users select amongst possible options. Symbiotic Man - Machine Built on the symbiotic Man-Machine principles to improve solutions continuously and never stops with the initial learning. Your Expert Agent A smart agent in every interaction and Channel. Resolve issues across any channel. This is a great space to write a long text about your company and your services. You can use this space to go into a little more detail about your company. Talk about your team and what services you provide. Share AI insights for any type of issue. Repeated issue? Simple Query? Complex issue? One-off issue? Stop searching across various applications. No more frantically calling experts or deploying field agents. Know what to ask, when to ask, how to look at customer data and follow recommendations. Tribal Knowledge Conversion. You need a system that learns from experts' every move. You need a system that elevates the efficiency of the entire team. Ascendo is the only platform that can help with individual resolutions as well as share patterns and actions for entire teams to improve. Learn More Sectors Our Focus Areas EXPLORE SECTORS We bring our expertise to multiple construction sectors, developing the industry's future and redefining what is possible, one project at a time. 01 Live Agent Transfer from Customer Self Service to Agent seamlessly across multiple channels so your customers can get help anytime and never have to repeat themselves. 02 One Prediction Manage all your customer interactions across all channels in one place while increasing agent quality. 03 Prioritize Prioritize, assign agents and triage cases automatically. Even know who is an expert for a particular type of issue resolution. Consolidated Consolidate view of every interaction across all channels. Ideal in • Issue Resolution • Triaging Automate Automate repeat processes as never before. Ideal in • Voice of the Customer • Patterns and trends Onboard Increase Customer Experience even as you onboard new agents. Ideal in • Tribal Knowledge • Quality and Efficiency Ready to learn more? Contact Us