Customer support is in the midst of a technological revolution, with Generative AI (GenAI) at the forefront to streamline end user experience. Today’s AI agents have evolved far beyond the limited capabilities of their rule-based predecessors. They can respond to nuanced queries, optimize workflows, and provide decision-making assistance—all at scale. As a result, many organizations now rely on AI as their initial support layer, efficiently managing common requests like pesky password resets, automating ticket routing and common troubleshooting while freeing human agents for more complex issues.
But as our reliance on these intelligent assistants grows, a critical question emerges: How do we ensure consistent, accurate, reliable, and high-performing support? The answer lies in comprehensive AI assurance.
The Hidden Complexity of Modern AI Infrastructure Used in Customer Support Scenarios
Modern AI agents, especially those handling customer support, are not monolithic. They rely on two foundational pillars:
- Inference Providers (Foundation Models): These are the "brains" – large language models (LLMs) from hosted providers like OpenAI, Anthropic, or Google that power the agent's understanding, reasoning, and response generation, or from open-weights models available on Hugging Face et al.
- Model Context Protocol (MCP) Servers: These act as the "connective tissue," providing the AI agent with enterprise-specific context, access to internal data sources (like CRM, inventory, knowledge bases), and the ability to trigger actions (like creating a ticket with context, resetting a port or updating firmware ). This includes seamless integration with critical ITSM platforms such as ServiceNow and Jira, enabling automated incident creation, task assignment, and workflow updates directly from AI agent interactions.
Any degradation in these components – be it slow responses from an LLM, inaccurate information from an MCP server, or a connectivity issue to a backend system – can quickly turn a helpful chatbot into a frustrating experience, leading to customer churn and reputational damage. Traditional monitoring tools simply aren't equipped to validate the nuanced performance and contextual accuracy required by these advanced AI systems.
Cisco ThousandEyes: Your AI-driven Assurance Partner
Recognizing this critical need, Cisco ThousandEyes is introducing innovations designed specifically for the agentic AI ecosystem. We provide the deep visibility and assurance enterprises need to confidently scale their AI-powered customer support operations:
- Validating the AI's with AI Test Templates: Our AI Test Templates go far beyond basic uptime checks. They specifically target the developer APIs of your inference providers, using sophisticated prompt engineering to simulate realistic queries. We validate not just availability, but also latency, response times, token efficiency, and crucially, the accuracy and consistency of the AI's responses from multiple global locations. This means you can detect if your chatbot or agent is suddenly providing outdated information or taking too long to respond. You can be proactive, helping ensure your Tier 1 support and operations teams remain intelligent and efficient.
- Assuring enterprise context integrity with MCP Server Monitoring: The MCP server is where your AI agent gets its "business intelligence”. Continuous MCP Server Monitoring helps ensure the integrity of this critical layer. It establishes standards-compliant connections, discovers available resources and tools, and provides real-time alerts for unauthorized changes to tool configurations. This is vital for security and governance, helping ensure your agent only accesses and uses approved tools and resources, which helps prevent missteps or data breaches.
- Empowering your AI agents with the ThousandEyes Public MCP Server*: This server provides a secure scalable gateway for your AI agents enabling support with a set of powerful troubleshooting tools that have access to rich, real-time performance and availability data from ThousandEyes' comprehensive synthetic testing datasets, outages and events. Our public MCP server can be integrated with popular AI assistant interfaces (like Microsoft Copilot, Anthropic's Claude, Google Gemini) and accessed by your internal AI agents or integrated into 3rd party ITSM systems like ServiceNow.
AI in Action: Revolutionizing Customer Support with ThousandEyes
Imagine the impact of this integrated assurance on your operations and customer support workflow:
- Enhancing the Capabilities of Tier 1 AI Chatbots: When a customer reports an issue, your AI chatbot can do more than just ask questions. Drawing on insights from 451 Research, which identifies monitoring (50%), security scanning/testing (49%), and troubleshooting (48%) as the top IT operations tasks leveraging GenAI, the bot can internally interact with the ThousandEyes Public MCP Server. It can ask, "Is our payment gateway API responding slowly from the customer's region?" or "Initiate an on-demand network path test to the CRM server to determine if there's a connectivity issue impacting this customer's account lookup." This allows the bot to self-diagnose, gather real-time performance data, and provide more accurate initial responses or even resolve issues without human intervention.
- Supercharging Higher-Tier (Human) Support: When an issue does require human intervention, your higher-tier support agents can leverage the Cisco AI Assistant within ThousandEyes. Instead of sifting through dashboards, they can simply ask, "Summarize the recent outages affecting our customer portal in North America" or "Explain the latency spikes to our cloud contact center from Europe yesterday." The AI Assistant quickly identifies and summarizes relevant performance data, providing plain-language explanations of complex network metrics. This in-line troubleshooting interface empowers agents to provide faster, more informed resolutions.
- Proactive IT Operations & Engineering Ops: Beyond individual interactions, ThousandEyes' Event Detection capabilities provide IT operations and engineering teams with unparalleled visibility. Real-time alerts are triggered for subtle degradations in AI model performance (e.g., "Anomalous response times detected for our LLM model in APAC") or unauthorized changes to MCP server tool configurations. This proactive alerting allows teams to rapidly troubleshoot and resolve issues – often before customers even notice – helping ensure continuous, high-quality AI service delivery.
The Future of Customer Experience is Assured
The convergence of advanced AI agents, standardized context integration through MCP, and comprehensive monitoring capabilities from ThousandEyes provides customer support with a powerful set of troubleshooting tools. Additionally by ensuring the reliability, accuracy, and security of your AI-powered chatbots, you not only enhance the customer experience but also gain significant competitive advantages through intelligent automation and more efficient operations.
Discover the benefits of AI-powered customer support with ThousandEyes and help assure your agentic AI environment with a free ThousandEyes trial!
* Many of the products and features described herein remain in varying stages of development and will be offered on a when-and-if-available basis. The delivery timeline of these products and features is subject to change at the sole discretion of Cisco, and Cisco will have no liability for delay in the delivery or failure to deliver any of the products or features set forth in this document.