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  • The Future of Technical Support: Collaboration Between AI and Humans

    In the ever-evolving world of technical support, one question remains constant: how do we provide exceptional service while balancing efficiency and cost? Enter generative AI (gen AI) — a transformative force that has redefined the possibilities for technical support and customer engagement.   As Isaac Sacolick highlights in his recent article  on maximizing business value from gen AI, this technology’s potential extends far beyond simple productivity gains. At Ascendo AI, we couldn’t agree more.  The Future of Technical Support: Collaboration between AI and Humans A New Era of Technical Support: Beyond Chatbots   The days of chatbots that frustrate rather than help are behind us. Today’s AI-powered agents , like those championed by Ascendo AI, are designed not just to respond but to actively collaborate. These AI teammates can analyze complex queries, generate precise responses, and even anticipate future issues, ensuring customers receive timely, tailored support.  As Sacolick notes, call centers and IT service desks are ripe for transformation. AI agents excel at reducing average handling time, boosting resolution rates, and enhancing customer satisfaction. Tools like Salesforce’s AI sales agents and Workday’s recruiter agents demonstrate that AI is no longer a “nice-to-have” but a competitive differentiator. At Ascendo AI, our platform takes this a step further, offering AI teammates that integrate seamlessly with human workflows to maximize efficiency without sacrificing personal touch.  Empowering Human Teams Through Collaboration   One of the most exciting aspects of AI agents is their ability to empower human teams. Rather than replacing support agents, AI teammates work alongside them, analyzing tickets, summarizing trends, and providing actionable insights. This collaboration not only speeds up resolution times but also frees up human agents to focus on higher-value tasks, such as building relationships and tackling nuanced challenges.  Sacolick’s insight into Net Promoter Scores (NPS) and resolution times highlights the tangible benefits of AI-driven support. For example, our AI teammates help organizations track key metrics, enabling continuous improvement. By embedding AI into their processes, companies can enhance both employee satisfaction and customer loyalty—a win-win scenario that drives long-term growth.  The Importance of Data and Context   Data is the backbone of effective AI. Sacolick’s emphasis on aligning data strategies with business objectives resonates deeply with our philosophy at Ascendo AI. By centralizing and enriching customer data, AI teammates can provide more accurate, context-aware responses. This capability is particularly critical in industries like healthcare, finance, and tech, where precision and personalization are paramount.  For instance, Ascendo AI’s AI agents leverage advanced data integration techniques to analyze customer interactions in real time. Whether it’s identifying recurring pain points or offering proactive solutions, these agents ensure no insight goes unnoticed. The result? Happier customers and more empowered support teams.  A Collaborative Future for AI and Humans   At Ascendo AI, we believe the future of technical support is a collaborative one. As Sacolick rightly points out, driving adoption requires more than just deploying technology—it’s about building trust and demonstrating value. That’s why our platform is designed with change management in mind, helping organizations transition smoothly while keeping their teams engaged and informed.  Generative AI’s ability to transform workflows isn’t limited to customer-facing roles. As Sacolick highlights, AI is also making strides in areas like sales and marketing, proving its versatility across departments. By adopting a holistic approach, companies can unlock AI’s full potential, driving innovation and improving outcomes at every level.  Let’s Redefine Support Together   The AI revolution in technical support isn’t just about automation—it’s about creating better experiences for everyone involved. At Ascendo AI, we’re committed to helping businesses harness the power of AI teammates to redefine what’s possible in support. Whether you’re looking to improve resolution rates, enhance customer satisfaction, or empower your team, our platform is here to guide you every step of the way.  As Sacolick’s insights remind us, the key to success lies in collaboration—between AI and humans, between technology and strategy, and ultimately, between organizations and their customers. Let’s build that future together.  Learn More: Rethinking Technical Support with Agentic AI Slow and Steady: Why AI in Technical Support is Poised for Transformation in 2025

  • The Future of Customer Service: Generative AI CRM Copilots

    Customer support  is a battlefield. Between sky-high expectations, complex product ecosystems, and a constant influx of inquiries, support teams are under immense pressure. Without the right tools, these challenges can quickly overwhelm even the most dedicated agents.  Generative AI CRM Copilots The Struggles of the Traditional Support Agent   Information Overload:  Switching between multiple tabs, searching knowledge bases , and manually cross-referencing information is exhausting and time-consuming.  Repetitive Tasks:  Answering the same questions over and over drains morale and prevents agents from focusing on more complex, high-value interactions.  Inconsistent Responses:  Different agents may provide varying answers to similar queries, leading to customer frustration  and confusion.  Limited Personalization:  Without a comprehensive understanding of each customer's history  and preferences, it's difficult to provide truly tailored support.  Slow Resolution Times:  Long wait times and drawn-out issue resolution can damage customer satisfaction  and loyalty.  A Holistic Solution: Empowering Agents for Success   A truly effective solution goes beyond simple automation. It's about empowering your agents and giving your team the insights they need to excel. Here's what a holistic support solution  should offer: Agent Empowerment:  Equipping agents with the tools and knowledge to effectively  troubleshoot and resolve issues, rather than relying on scripted responses.  Collaboration Tools : Providing seamless integration with platforms like Slack or Teams, allowing agents to collaborate with internal experts when needed.  A Holistic Solutions: GenAI CRM Copilots Knowledge Creation: Going beyond simple prompts, the AI tool should help agents understand the underlying issues and contribute to the knowledge base ,  creating  a continuous learning loop.  Real-time Insights: Providing leaders with actionable data on issue trends, customer sentiment , and root causes. This enables proactive decision-making, such as developing targeted training, updating knowledge articles , or even making product  improvements.    Enter the AI Co-Pilot: Your Agent's Superpower   Ascendo.AI is that holistic solution. It's a Generative AI CRM Copilot designed to transform your customer support operations from the ground up. With its deep integration into your existing service CRM , Ascendo.AI :  Empowers Agents:  Gives agents the insights and tools they need to provide exceptional, personalized support.  Improves Productivity:  Automates routine tasks and surfaces relevant information, allowing agents to focus on complex problem-solving  and building customer relationships.  Enhances Efficiency:  Streamlines workflows and facilitates collaboration, reducing resolution times and improving customer satisfaction .  Drives Revenue:  By fostering a culture of continuous improvement and delivering a superior customer experience , Ascendo.AI helps increase customer loyalty and drive repeat business.  Provides Real-Time Insights:  Equips leaders with the data they need to make informed decisions and optimize support operations .    Are You Ready to Revolutionize Your Support?   Don't settle for band-aid solutions that merely mask the underlying challenges. Embrace the power of a truly holistic AI co-pilot and unlock the full potential  of your support team with Ascendo.AI .  Let's build the future of customer support together.   Learn More: Unleashing the Potential of Generative CRM: Redefining Customer Engagement Uncovering Trends and Redefining Success in Customer Support with AI-Powered Precision

  • Go Beyond Knowledge Management To Improve Support Experience

    For large Enterprises, Data Variety trumps volume while looking for insights. More enterprises are inclined to make Big decisions with data. To do this efficiently, applications need to be intelligent. They should have the ability to: Accumulate data Analyze data Act based on data The business processes in Enterprise applications so far have been workflow-based. The data is gathered from the workflow to then be utilized to do reporting. The future of Enterprise applications will be based on Intelligence rather than workflow and Prescriptive rather than reporting Essentially, Intelligence will drive the workflow and Prescriptive actions will be based on predictions. This is where the top-tier AI systems stop. There are many tools coming up in the market branding themselves as AI or expert tools. The Customer support market is especially proliferated with Robotic Process Automation (RPA), Chatbots and automation tools. Companies are at a loss on how to evaluate them and know when to use what. Their focus is on Return On Investment (ROI) and the tools don’t specifically cater to the customer needs. This article highlights how to think beyond buzz words and articulates the differences in technology to enable picking the right solution for your support/service teams. Why Complex Systems Need New Thinking In Customer Support When products are new, come out as the most simple, why do we need to support innovation? Complexity is increasing exponentially, complex systems fail in complex ways, and complex failures need dynamic and adaptive responses. Complex systems contain mixtures of latent issues : A system’s complexity means that it is impossible for it not to contain multiple flaws. Most flaws are insufficient to cause significant issues . They are regarded as minor factors during operations. The flaws change constantly, due to evolving technology and organizational factors, and even as a result of efforts to resolve existing flaws. Complex systems run as broken: Redundancies in the system, and the ongoing expertise and effort of humans, ensure that the system continues to function, sometimes in degraded mode. Issues have multiple causes, not a single root cause . Every single flaw is insufficient to cause a major issue. It is the linking of multiple faults that creates the circumstances required for a significant failure. Innovate Customer Support From Ground Up! The level of complexity has increased not just because products are complex but also the environment and usage are complex. In this ever-increasing complexity, support teams are focused on three main goals: Solve today’s problem Make sure it doesn’t happen again — Reduce customer escalations article talks about aligning customer expectation, empowering front line, prioritize which customers to focus on, communicate Predict problems before they happen Whether it is self-service , community, agent assist, or auto-support, problem prevention and problem elimination are the core. As companies look at ways to do the above, most of them believe incorporating AI will help them. They believe AI to be: Automating repeated tasks. This is called Automation or Robotic Process Automation (RPA) for short. In this method, you program the repeated tasks and let the computer execute them. Rules-based and statistics-based tools are an expansion to traditional Business Intelligence (BI) engines. Machine Learning algorithms that identify anomalies and patterns within data in the enterprise Identify relevance using Natural Language Processing (NLP) Ideally, a tool can be called a true AI tool when it utilizes all of the above along with: Extending NLP to include Content and Intent along with relevance. Extending Machine Learning to provide prescriptive actions. Utilize Tribal knowledge from the users. Tribal Knowledge: Beyond AI in support Intuition helps only when it is in the area of expertise — Originals by Adam Grant Value of data as a function of a number of observations in an ML domain, here machine vision. Each vertical line represents the same complexity of a particular problem. Credit: Nicole Immorlica, Microsoft Research. The key to a successful AI journey incorporates utilizing knowledge intelligence to improve support experience from humans, getting the feedback loop, and incorporating it into learning. AI is good for complex systems and dimensions of data. Feedback procured from humans on prescriptive actions provided by the tool adds to another dimension. At Ascendo, we believe one of the most important dimensions is every interaction the users are having with the tool. These interactions become critical learning opportunities. A learning engine knows what an agent is looking for, what the data suggests as actions, what the agent decides and how the agent interacts with the tool. It has the ability to not just learn from data, not just learn from feedback from its users but also from user interactions . What we have seen is when we include tribal knowledge from interactions, the prescriptive actions are more optimal than just utilizing data. Essentially, we have expanded the dimensions of decision-making. Top 10% of AI tool dimensions: Where AI tools need to be? When someone says AI tool, do ask what do they mean by AI. Following are some leading questions: 1. What role does artificial intelligence play in this tool to help customer support teams? 2. How are relevance and feedback enhancing the Machine Learning dimensions of the tool? 3. Can the tool go beyond these dimensions to identify intent and learn from interactions? Learn more, Knowledge Intelligence in Customer Service Use AI to Drive Service Improvements

  • Ascendo Announces SOC 2 Certification

    The letters SOC stand for Service Organization Control. The certification process involves an audit by a third party to verify that a company is meeting SOC guidelines. Ascendo AI is excited to announce that it has successfully completed a System and Organization Controls (SOC) 2 audit. Ascendo SOC 2 Certification Why do we take SOC 2 seriously? There were 945 data breaches globally in the first half of 2018. That’s 4.5 billion compromised records in just six months! It is more important than ever to take every precaution to keep user data safe. One way that a company can ensure that they keep data safe is by undergoing SOC 2 Certification. Why is SOC 2 Certification Important? SOC 2 Certification is vital because it holds businesses to a standard that protects consumer data. It allows the consumer to have peace of mind knowing that a company is vetted and approved. SOC Certification is essential for companies that store data in the cloud and those that offer SaaS (software as a service) subscriptions. Companies that handle healthcare information fall under patient-protection laws and HIPAA, so having SOC 2 certification and compliance is a good step for them to show they are protecting patients’ information such as when offering medical insurance verification services. SOC 2 Certification is not required, but it is a way of communicating the degree of care a company takes for the consumer. High-profile data breaches are in the news all the time, and it seems more accessible than ever for criminals to compromise private data. Companies should test all web applications and software to ensure they stand up to hacking, DDoS attacks, and any other attempts that compromise customer information. When a company does have a data breach, it lowers public opinion of them, and users can experience identity theft. That could ruin their credit or lose them their retirement savings! It is up to companies who use this data to conduct business to protect their users. A SOC 2 certification can go a long way to building user confidence. SOC 2 Trust Services Criteria To pass the SOC 2 audit process, a third party evaluates a company’s system on five SOC 2 Trust Services Criteria including: Security Availability Processing Integrity Confidentiality Privacy Industry-Standard Accreditation The SOC 2 audit is one of the highest recognized standards of information security compliance in the world. It was developed by the American Institute of CPAs (AICPA) to allow a third-party auditor to validate a service company’s internal controls concerning information security. The SOC 2 Audited Report is the auditor’s opinion on how an organization’s security controls meet the SOC 2 criteria. To obtain our audited SOC 2 Report, a third-party auditor reviewed our internal controls including policies, procedures, and infrastructure regarding data security, firewall configurations, change management, logical access, backup and disaster recovery, security incident response, and other critical areas of our business. Thanks to a company-wide effort at Ascendo, we successfully achieved compliance and received an Auditor’s Report demonstrating that our policies , procedures, and infrastructure meet or exceed the SOC 2 criteria. We believe the relationship with our customers must be built on trust. The successful completion of our SOC 2 Report is one of many ways that we have planned to earn and retain that trust. SOC 2 is just one aspect of our growing security program. We are committed to continually improving our information security program and retaining an annual SOC 2 audit to ensure we keep supporting our customers’ needs. If you are interested to learn more about Ascendo AI, contact us

  • AI Service Agents - Build vs. Buy

    As AI initiatives   become higher priorities and technologies become more accessible, many enterprise organizations consider building solutions   in-house. A variety of questions typically arise when exploring the idea: Will general LLMs (GPT4, BERT, RoBERTa, LLaMA, Megatron) work for our needs?  Can we just apply ChatGPT?  Is GenAI the answer for us?  Can we just use RAG architecture or Vector Embedding Databases?  Are there some use cases that make sense to Build vs. Buy?  Do we have the right expertise? AI Service - Build vs. Buy For service organizations, the build approach is often the best path for simple use cases that require a bit of customization, while complex use cases in service environments with complex products find a faster path to success with the right AI solution partner .  Planning an AI initiative to improve service performance ?   Choosing the right AI technology is critical. Should you adopt ChatGPT  or leverage Ascendo AI ’s Service Co-Pilot, purpose-built for service organizations?  Companies with Technical Support or Complex Services typically require a higher degree of accuracy from AI responses than ChatGPT offers out-of-the-box. Ascendo’s AI has been trained on the service data of the world's largest manufacturers, delivering unmatched accuracy compared to even the best adaptations of generic LLMs. Before attempting to adapt LLMs to fit your needs, consider the high costs, time, integration, and expertise needed for a solution that may still have limitations. Ascendo AI’s platform gives you unmatched AI performance, so you can quickly begin optimizing your service operations.  Ascendo AI Service Co-Pilot Vs. Open Source LLMs   Criteria Ascendo AI Open Source LLMs   Service Domain Expertise Service-focused model , trained on the data of complex and large manufacturers  to understand the language of service.  General-purpose models lack specialized knowledge and features tailored for the service domain.  Continuous change in models also makes it harder to continuously pick and tune the right model for the right use case Personas   Customizes interactions for different user personas (e.g., customers, remote agents, field agents, escalation engineers, managers) to provide relevant responses and actions. Does not natively support persona-specific customizations, making it less effective in targeting different user needs.  Data Integration Seamlessly integrates  with customers’ CRM or data, assets, service records and knowledge base, ensuring that the most relevant and up-to-date information is used.  Lacks native integration capabilities with specific customer systems, leading to potential data silos and outdated information. Additionally, it requires significant integration efforts to utilize company-specific data and may be prone to errors based on outdated or incorrect data assumptions. Data Quality   Utilizes a custom evaluation framework specifically designed for service data . To achieve the highest level of accuracy, we implement advanced and tailored data transformation techniques that align with the unique characteristics of the data. Each stage of the pipeline—from data ingestion and cleaning to transformation, storage, and response generation—is carefully architected and optimized to meet the specific demands of the application and user requirements, ensuring enhanced precision and relevance in the outputs. Is trained on a broad dataset, which might not include specific or detailed data pertinent to your industry and company needs.  AI Guardrails   Private, RAG based application, does not allow for hallucinations control and guardrails.  Prone to hallucinations and inaccuracies. Expert Knowledge Integration   Incorporates tribal knowledge from your service pros directly into the system, ensuring high-quality, accurate responses. Does not allow for easy integration of specific expert knowledge , potentially leading to generic or less informed answ ers.   Use Case Personalization Makes recommendations based on specific machines and customers.  Also, recommendations cater to the engagement area where the use case is initiated from – e.g., slack, teams, email, phone, forms, etc.  Answers do not take asset and customer history into account. Implementation Time Designed for quick deployment and integration with existing systems, Go live in less than 2 weeks.  Longer setup and training period required, increasing time to deploy. User Expertise Designed for service professionals, minimizing the need for extensive training and technical knowledge .  Requires a dedicated engineering team to customize and implement effectively.  Support & Maintenance Offers dedicated support and maintenance services tailored to customer needs.  Does not provide specialized support and maintenance for specific industries, potentially leading to slower issue resolution and will require in-house support and continuous maintenance. Team Enablement   Offers onboarding or enablement support. Does not provide specialized support and maintenance for specific industries, potentially leading to slower issue resolution and will require in-house support and continuous maintenance.  Scalability Scalable architecture is designed to handle the growing needs of service organizations.  Scalability depends on the in-house development team’s capabilities. Cost Transparent pricing  tailored to the needs of service organizations, Set annual pricing.  Cost of customization, usage, implementation, and scaling will vary and may require additional development resources.  Performance Optimized for high performance in service-related tasks, insights, and recommendations based on your data, ensuring fast and accurate responses to handle issues faster. A general-purpose model may lead to slower or less accurate responses for specific service industry tasks, and it varies on how well it's customized and integrated.  Security & Compliance Built-in compliance  with industry standards and regulations.  Custom security measures and compliance need to be implemented by your team. Research & Development   Dedicated teams continually update and integrate the latest AI and GenAI advancements , ensuring cutting-edge solutions tailored for service organizations. Lacks focused, ongoing R&D specific to the service industry, leading to slower adaptation of new technologies and less customized solutions. Interface   End-user interface for model tuning.  Transparent method to share mapping and contexts.  In-depth human augmentation  to incorporate expert knowledge and feedback. OpenAI sandbox experience.  Generally, a black box. Modules   Offers specific modules tailored for different service use cases (e.g., troubleshooting).  Does not offer specific or customizable modules for different use cases. In the realm of AI for service organizations, the choice between building an in-house solution using general LLMs and partnering with a specialized AI provider like Ascendo AI ultimately hinges on factors such as the complexity of your service operations, the level of customization required, and the desired speed to market.   While general LLMs offer a versatile foundation, they often lack the domain-specific expertise, data quality, and tailored features necessary for optimal performance in service environments. Ascendo AI's  Service Co-Pilot,  on the other hand, is specifically designed to address the unique needs of service organizations, providing unmatched accuracy, seamless integration, and a user-friendly experience.   By choosing Ascendo AI , you can accelerate your AI implementation, reduce costs, and ensure that your service operations are equipped with a powerful AI solution that delivers tangible results.   Learn more: The Future of Customer Service: Generative AI CRM Copilots Tips to transition from Self-Assign to Automatic Assignment

  • Data Quality: The Foundation of Efficient, AI-Powered Technical Support

    Data is the lifeblood of today’s technical support operations—especially in AI-driven environments where intelligent agents and AI-powered teammates streamline technical service. However, as Kathleen Hurley, founder of Sage Inc., points out in her recent Forbes  article, " Data Quality and Integrity in the Age of AI ," poor data is not only a common issue but a costly one. At Ascendo AI, we believe that high-quality data is the bedrock of exceptional customer experiences. Here’s our take on how smart AI solutions can help businesses tackle data integrity challenges and turn them into opportunities for support transformation.  Data Quality: The Foundation of Efficient, AI-Powered Technical Support Why Data Quality Matters More Than Ever   Hurley highlights a universal truth: when bad data creeps into decision-making systems, it impacts real people. Imagine an AI agent providing troubleshooting advice based on outdated or incomplete data. The result? Misdirection, increased frustration, and wasted time—the exact opposite of the seamless, personalized support today’s customers expect. Regulatory pressures, like GDPR’s data integrity principles, only add to the urgency.  Our AI Agents thrive on reliable information, transforming technical support by combining automation with human-like reasoning. However, even the smartest AI systems can’t overcome fundamentally flawed data. Investing in data integrity is more than compliance; it’s about empowering AI teammates to make informed, context-aware decisions that improve efficiency and customer trust.  The Two-Sided Approach to Data Cleansing   One of the most valuable insights from Hurley’s article is the importance of a dual-track strategy:  Clean Data Intake for New Information : Implement structured processes that validate data at entry points. This prevents inaccurate information from ever reaching your AI-driven systems.  Gradual Cleanup of Historical Data : Instead of tackling legacy data all at once, segment and funnel clean data into modern systems step-by-step.  At Ascendo AI, our AI teammates are designed to work with both historical and incoming data. We use dynamic data cleansing processes—automated validation routines paired with anomaly detection—to flag potential issues before they escalate. These AI Agents become integral partners in maintaining data hygiene, and supporting human teams by handling repetitive data monitoring tasks.  What Makes Data “Clean” for AI?   Clean data adheres to five key principles: accuracy, completeness, consistency, timeliness, and relevance. Hurley illustrates how older systems often miss the mark, allowing manual data entry errors or incomplete records to persist. When AI-driven technical support systems rely on this flawed data, troubleshooting accuracy plummets.  AI teammates from Ascendo AI are built with data validation and adaptive learning capabilities. They continuously refine their understanding of what constitutes “good” data, learning from patterns and human feedback. This iterative improvement helps keep your data streams in line with evolving quality standards.  AI and Human Collaboration: A Better Path to Data Integrity   Hurley’s article emphasizes the need for user education alongside technological solutions. AI can identify patterns, flag outliers, and enforce validation rules—but human users play a critical role. Employees must understand the importance of clean data practices and how their actions contribute to maintaining integrity.  With AI teammates as collaborators, organizations can achieve sustainable improvements. Our AI Agents don’t replace human ingenuity; they enhance it by handling repetitive validation tasks, freeing human teams to focus on strategic improvements. Empowering users with real-time insights into data quality reinforces better habits and drives long-term efficiency.  The Ascendo AI Advantage: Turning Data Integrity into Competitive Edge   Clean data is the backbone of AI-powered efficiency, and forward-thinking companies recognize this as a strategic investment. By integrating AI Agents that prioritize data integrity, organizations can:  Reduce error rates and avoid costly missteps.  Deliver faster, more accurate technical support.  Strengthen customer trust through personalized, reliable experiences.  Hurley’s article serves as a timely reminder: solving the data integrity puzzle requires both smart technology and informed teams. At Ascendo AI, we’re committed to equipping organizations with AI teammates that transform technical support operations from reactive problem-solving into proactive, data-driven service excellence.  Learn More: Unlocking the Power of Proprietary Data: AI Agents as Game-Changers in Customer Support Navigating the Integration of Large Language Models (LLMs) in Enterprise: A Comprehensive Guide

  • What sets Ascendo Apart?

    Ascendo AI is a copilot for customer support and service teams. Ascendo is a plug-and-play engine with deep self-learning capabilities that help customer-facing teams provide proactive support. Ascendo differentiates by going deeper in understanding the meaning of every customer interaction. Four modules of Ascendo are: Resolve – Automated workflows for Agents including resolutions, debug engine, triage, assign, and categorize. Automated self-service workflows for customers Reveal – Predictive alerts, trends, and patterns for Leaders in real-time to tweak and optimize Prevent – Reduce Escalations and Churn Predict – Spares planning to meet SLA Ascendo AI: Your Service Co-Pilot Ascendo AI is a SaaS software that does AI automation through domain-specific Large Language Models (LLM) built on top of foundational LLM models. It is a true copilot with thousands of automated use cases to provide insights, predicted alerts, actions, and trends. Ascendo also has plug-and-play integration with various data sources. Let us review them in detail: Foundational Models : The Foundation of Ascendo is several foundational Large Language Models (LLMs). These models are advanced AI systems capable of understanding and generating human language. Along with LLMs Ascendo uses Retrieval Augmented Generation (RAG). RAG integrates LLMs like GPT-4 with external vector databases and APIs, thus enabling real-time information retrieval for up-to-date and more accurate responses. These foundational ensemble models are tuned differently for different use cases. Domain-Specific LLM: What sets this Ascendo apart is its specialization in the support and service domain. It goes beyond the general language understanding of foundational LLM models and is fine-tuned for specific industries or domains. This specialization allows the software to deeply comprehend and work within a particular field, making it highly effective for domain-specific tasks. The domain-specific LLM also considers dirty data, and incorrect data and has “smart sizing” built into the tool. This sizing of both structured and unstructured data helps even if historical data is not very reliable. This approach “fixes” historical data right at ingestion for Ascendo models to give much greater accuracy and instant ROI for teams from day 1. True Copilot: Ascendo is a "true copilot." Ascendo acts as a genuine partner in tasks and processes. It doesn't just automate tasks but actively collaborates with human users, offering suggestions, insights, and assistance. It's more than just a tool, an AI engine, or a resolution engine. Ascendo is a valuable ally for support agents, field service technicians, leaders, and end customers. Thousands of Automated Use Cases: Identifying what an expert does and replicating the exact steps for every other user is an invaluable core of Ascendo. Ascendo handles an extensive range of tasks and processes that are done every day within support and service teams. Ascendo is pre-trained to automate thousands of use cases across support and service domains. This extensive automation capability can significantly reduce manual workloads and improve efficiency. Plug and Play Integration: One of Ascendo’s key advantages is its ease of integration with various data sources. It can seamlessly connect with different systems, databases, and data streams, making it adaptable to the specific data environments of individual organizations. This includes systems of record like Jira, CRM, and Knowledge bases as well as systems of engagement like Chat, Slack, Teams, forums, and communities. This "plug-and-play" approach ensures a smooth implementation process within Enterprises. This also helps to onboard new products within days instead of weeks or months. In summary, Ascendo’s differentiation lies in its ability to go beyond general AI capabilities by specializing in support and service domains, serving as a true collaborator, automating a wide range of tasks, and being highly adaptable through seamless data source integration. This makes it a powerful tool for businesses looking to streamline processes and harness the potential of AI within their unique contexts. Learn more Revolutionizing Customer Support with Ascendo AI and SAP Service Cloud Customer Support Software Trends for 2023: Unlocking Growth with Ascendo

  • Transform Field Service with Knowledge First Agentic AI Platform

    In today’s fast-paced business environment, the integration of artificial intelligence (AI) into field service management (FSM) workflows is becoming essential. Ascendo AI’s Knowledge First Agentic AI platform offers a comprehensive solution designed to streamline processes, enhance customer satisfaction, and optimize resource utilization.  Ascendo AI: Knowledge First Agentic AI Platform Seamless Integration with Existing Systems  One of the standout features of Ascendo AI is its ability to seamlessly integrate with existing field service CRM systems. This integration provides a unified view of customer information, service requests, and technician assignments. By reducing data entry errors and enhancing workflow efficiency, organizations gain a holistic perspective on their field service operations.  Empowering Customer Self-Service  Ascendo AI places a strong emphasis on customer empowerment. The platform provides robust self-service options, enabling customers to independently find solutions through FAQs, knowledge base articles, and guided troubleshooting steps. This approach not only reduces the need for human intervention but also significantly boosts customer satisfaction by enabling quicker resolutions.  Intelligent Routing for Efficient Dispatch   At the heart of Ascendo AI’s offering is its intelligent routing engine. This AI-powered tool matches customer requests with the most suitable technicians based on skill sets, location, and availability. By ensuring efficient dispatch and minimizing response times, organizations can optimize resource utilization and enhance service delivery.  Streamlined Game Plan Generation   For dispatch managers, Ascendo AI simplifies the process of creating detailed game plans for technicians. By outlining the necessary steps, parts, and tools required for each task, the platform ensures that technicians are well-prepared and equipped to resolve issues efficiently.  Real-Time Technician Support   Technicians also benefit from Ascendo AI’s real-time support features. The platform provides step-by-step instructions, troubleshooting tips, and access to relevant knowledge articles, empowering technicians to address issues effectively and independently.  Automated Activity Summarization   After each service call, Ascendo AI automatically summarizes technician activities, offering a clear record of the work performed and the issue resolution process. This feature aids in tracking performance, identifying areas for improvement, and generating accurate reports.  Leveraging the Voice of the Customer   Understanding customer feedback is crucial for continuous improvement. Ascendo AI collects and analyzes this feedback to identify common issues and areas that require attention. By leveraging this data, organizations can enhance their service offerings and address customer concerns proactively.  Comprehensive Knowledge Management   Ascendo AI facilitates the creation and management of a centralized knowledge base , ensuring that technicians have access to the latest information and best practices. This fosters a culture of continuous learning, ultimately improving problem-solving capabilities.  Proactive Supply Chain Management In addition to these features, Ascendo AI includes an early warning system that monitors inventory levels and identifies potential shortages or surpluses of spare parts. This proactive approach helps organizations manage their supply chain effectively and avoid disruptions in service delivery.   Key Benefits of Ascendo AI   Improved Efficiency:  Streamlined workflows and automated processes lead to reduced manual effort and enhanced response times.  Enhanced Customer Experience:  Proactive support and personalized recommendations significantly boost customer satisfaction.  Data-Driven Decision Making:  Real-time insights and analytics empower organizations to make informed decisions.  Optimized Resource Allocation:  Intelligent routing and scheduling ensure optimal use of resources.  Continuous Learning:  Machine learning capabilities enable ongoing improvement and adaptation to evolving needs.  In conclusion, Ascendo AI’s Knowledge First Agentic AI platform is transforming the landscape of field service management. By automating tasks and providing intelligent recommendations, it empowers organizations to deliver exceptional customer experiences while optimizing operational efficiency. As AI continues to evolve, solutions like Ascendo AI are paving the way for smarter, more responsive field service operations.  Learn More: The Future of Customer Service: Generative AI CRM Copilots Uncovering Trends and Redefining Success in Customer Support with AI-Powered Precision

  • Embracing AI in Technical Support: Navigating Challenges and Opportunities

    In today's fast-paced digital landscape, artificial intelligence (AI) is reshaping how businesses engage with customers. At Ascendo AI , we recognize the immense potential of AI to enhance technical support while also understanding the challenges that come with it. However, a recent Harvard Business Review article by Ian P. McCarthy, Timothy R. Hannigan, and André Spicer ("The Risks of Botshit")  sheds light on a crucial challenge: botshit .  Botshit , as the article defines, refers to inaccurate or misleading information generated by chatbots. Imagine a customer relying on an AI agent for critical medical advice, only to receive fabricated information. The consequences can be dire. This highlights the importance of responsible AI development and implementation in Technical Support. The Dual Nature of AI in Technical Support   The Dual Nature of AI in Technical Support The rise of generative AI tools like OpenAI's ChatGPT and Google's Bard has brought about significant advancements in customer service capabilities. These tools can provide round-the-clock assistance, streamline operations, and improve response times. However, as highlighted in recent discussions, the inaccuracies that can arise from these systems pose serious risks to businesses. For example, a factual error generated by Bard during its launch led to a notable decline in Alphabet's stock price, demonstrating the potential financial fallout from unverified chatbot responses. Moreover, incidents across various fields—from legal professionals submitting fabricated cases generated by ChatGPT to journalists relying on AI for content—illustrate the pitfalls of uncritically using chatbot outputs. These examples serve as cautionary tales about the importance of accuracy and reliability in customer interactions.  Understanding and Managing Risks To effectively harness AI's capabilities while mitigating its risks, organizations must adopt a strategic framework for managing chatbot-assisted tasks. This involves asking two critical questions: How crucial is the accuracy of a chatbot's response for a specific task? How challenging is it to verify that accuracy?  By answering these questions, businesses can categorize tasks into four quadrants:  Authenticated Tasks : High importance and difficult verification (e.g., legal judgments).  Augmented Tasks : Low importance and difficult verification (e.g., brainstorming).  AI Tasks Quadrant Automated Tasks : High importance and easy verification (e.g., loan assessments).  Autonomous Tasks : Low importance and easy verification (e.g., routine inquiries).  This framework allows organizations to tailor their risk management strategies according to the nature of each task.    The Role of AI Agents and Human Collaboration   At Ascendo AI, we envision a future where AI Agents  work alongside human teammates to enhance technical support efficiency. Our agentic AI platform empowers organizations by providing intelligent assistance that complements human expertise rather than replacing it. This collaborative approach ensures that while AI handles routine inquiries and data processing, human agents remain at the forefront of complex decision-making processes. By developing practice-specific chatbots that utilize advanced technologies like retrieval augmented generation (RAG), businesses can significantly improve the accuracy and reliability of their customer interactions. These specialized tools not only enhance operational efficiency but also foster trust with customers by delivering precise information tailored to their needs.  A Call for Responsible Innovation   As we navigate this exciting landscape of AI-driven transformation in technical support, it is crucial for organizations to embrace these advancements responsibly. By acknowledging the potential risks associated with chatbot technology and implementing robust verification frameworks, businesses can harness the benefits of AI while safeguarding their reputation and customer trust. At Ascendo AI, we invite you to explore how our innovative solutions can revolutionize your technical support strategies. Together, we can leverage AI's strengths while ensuring a reliable and enriching experience for every customer interaction. Let’s embark on this journey towards a smarter future in technical support!  Learn More: Transform Field Service with Knowledge First Agentic AI Platform AI Service Agents - Build vs. Buy

  • Breaking Down Silos: How AI Agents Are Transforming Technical Support

    In today's fast-paced business environment, the integration of artificial intelligence (AI) is not merely a trend; it is a transformative force reshaping how organizations engage with their customers. At Ascendo AI, we understand the challenges posed by siloed departments that can hinder customer support efficiency. Fragmented structures often stifle innovation and impede communication, resulting in a subpar customer experience. However, what if we could leverage these specialized pockets of expertise to create a collaborative powerhouse?  Breaking Down Silos: How AI Agents Are Transforming Technical Support Ricardo Saltz Gulko's recent CMSWire article , "10 Ways to Turn Organizational Silos Into Collaboration Engines," offers a compelling perspective. He argues that silos, when approached strategically, can become centers of excellence. The key lies in harnessing that expertise  through intelligent  collaboration.  The AI Revolution in Technical Support   Recent industry data underscores a critical shift in customer service dynamics, revealing that over 56% of businesses  are already utilizing AI for customer interactions. Projections suggest that by 2025, 95% of these interactions will be driven by AI . This surge highlights a fundamental truth: organizations must adapt to meet heightened customer expectations for speed and personalization.    AI technologies, particularly chatbots and virtual assistants, are at the forefront of this revolution. They enable businesses to provide 24/7 support, ensuring that customers receive timely assistance without the long wait times traditionally associated with human agents. Notably, 82% of customers express a preference for interacting with chatbots  over waiting for human representatives, signaling a significant shift towards automation as a means of enhancing customer satisfaction.  Enhancing Efficiency Through Collaboration   While AI can efficiently handle routine inquiries, the human touch remains irreplaceable for complex issues requiring empathy and nuanced understanding. at Ascendo AI. We believe in the power of reliable  AI Agents and AI Teammates to empower  human support teams, fostering a collaborative environment that unlocks the true potential of your organization.  Statistics reveal that 77% of support teams  believe AI has raised expectations for faster response times. By integrating AI as an assistant to human agents, businesses can streamline workflows and reduce the time spent on repetitive tasks. Our AI agents are designed to support technical teams by providing instant access to information and automating routine inquiries, allowing human agents to focus on high-level problem-solving and relationship-building.  Here's how AI can transform your support strategy by bridging the silo gap:  AI Agents as Knowledge Hubs:  Imagine an AI agent that can tap into the deep knowledge of your R&D department, the customer insights of your marketing team, and the technical prowess of your support specialists – all in real time. This creates a nuanced  understanding of customer issues, allowing for faster and more accurate resolutions.  AI Teammates for Seamless Collaboration:  Our AI teammates seamlessly integrate with your existing support infrastructure, acting as a bridge between siloed departments. They can automate repetitive tasks, freeing up human agents to focus on complex issues and personalized interactions. This fosters a collaborative environment where everyone plays a vital role in delivering exceptional customer support.  Shared Accountability, Unified Success:  By leveraging AI to track key performance indicators (KPIs), we move away from departmental goals towards shared objectives. Everyone becomes invested in achieving a common vision, like improving customer satisfaction or reducing resolution times. This fosters a sense of shared accountability and propels your organization towards reliable  success.  AI isn't here to replace human support agents; it's here to empower them.  As a thought leader in the AI-powered customer support arena, Ascendo AI is committed to developing intelligent solutions that empower collaboration, unlock innovation, and deliver reliable results.   Looking Ahead: A Collaborative Future   As we look toward the future, it’s clear that the role of AI in customer service will continue to expand. Our vision at Ascendo AI is to lead this transformation by positioning our platform as a collaborative partner in enhancing technical support efficiency. By investing in advanced AI tools, organizations can prepare for a future where seamless integration between human agents and AI teammates becomes the norm.  In conclusion, embracing AI-driven solutions is not just about keeping pace with technological advancements; it's about reimagining how we interact with customers. At Ascendo AI, we are committed to empowering businesses to harness the full potential of AI in their support strategies. Together, we can create a more efficient, responsive, and personalized customer experience that reflects our shared values of innovation and collaboration.  Ready to break down the silos and revolutionize your support strategy?  Explore how Ascendo AI's AI agents and teammates can transform your customer experience. We invite you to explore our solutions and see how AI can empower your team to achieve new heights of efficiency and customer satisfaction.  Together, let's turn silos into engines of growth!   Learn More: Embracing AI in Technical Support: Navigating Challenges and Opportunities Transform Field Service with Knowledge First Agentic AI Platform

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