Evolving performance analysis with NeoLoad and AI

Analyzing performance test results has long been one of the most complex and time‑consuming aspects of performance engineering. As the volume of testing increases and delivery cycles continue to accelerate, teams face mounting challenges in making sense of vast amounts of data. Tricentis NeoLoad has always aimed to simplify these difficult tasks, helping customers turn performance testing into a faster, more accessible process, and our innovations over the course of this year continue to demonstrate that commitment.

Innovating with AI

With the release of NeoLoad 2025.1 in April, we took the first major step in delivering meaningful AI capabilities with the release of Augmented Analysis. This capability was designed to streamline analyzing results. By automatically interpreting test outcomes, highlighting anomalies through easy to consume intervals, and suggesting likely root causes, Augmented Analysis reduces the manual burden on experts while making insights easier for a broader range of team members to absorb and action on. It ensures that analysis keeps pace with fast delivery cycles and accelerates feedback into development and broader QA teams.

Shortly after, NeoLoad became the first enterprise performance testing solution to deliver a Model Context Protocol (MCP). MCP provides a standardized way for AI systems to interact with tools through natural language. For NeoLoad users, this means being able to run and monitor tests, query results, and generate reports conversationally, without needing deep tool expertise. It also lays the foundation for integrations across other Tricentis MCP-enabled tools like Tosca, qTest, and SeaLights, as well as third-party solutions, making performance intelligence more connected across delivery toolchains.

These capabilities already gave teams a new way to engage with performance results, from quickly requesting summaries to drilling into results across test runs. The release of NeoLoad’s MCP proved the value of conversational access to performance insights, reducing manual effort and accelerating collaboration. But this was only the start …

Expanding the AI innovation

Now, the next wave of MCP capabilities is arriving, and it represents NeoLoad’s continued evolution in how teams can work with performance results. These new tools go even further in enabling users to retrieve more detailed test results, drill into transactions and requests, explore logs and events, and even compare data across runs. Work that might previously have taken hours of manual effort can now be achieved in seconds through a simple natural language request.

One of the most powerful additions is interval‑based analysis. MCP can generate and analyze intervals within a test, breaking execution into phases that highlight how performance changes over time. Teams can quickly identify spikes, degradations, or anomalies within specific windows and understand their impact in context. This capability ties directly to Augmented Analysis, which already generates anomalies and breakdowns automatically. Through MCP, those insights are now even easier to consume, compare, and share, all delivered in plain language and tailored to what each user needs to see.

Equally important, MCP makes reporting effortless. Instead of manually compiling charts, screenshots, and tables, teams can generate clear, stakeholder‑ready reports instantly. These reports surface the key findings from a single test, or multiple tests, and can include things like overall trends, flagged issues, or noteworthy intervals. These reports can then be rapidly generated in a way that is easy for developers, managers, and business stakeholders to understand. What once required hours of manual preparation is now available on demand, improving communication and ensuring performance insights drive action across the organization.

NeoLoad’s introduction of Augmented Analysis and MCP reflects our commitment to delivering meaningful, practical AI capabilities, not hype. These features are designed to simplify complexity, accelerate decision‑making, and make performance insights more actionable across teams. And this is just the start.

As we move through the rest of the year and beyond, expect to see even more advancements in AI‑powered performance testing, ensuring that NeoLoad customers continue to lead the way in implementing modern performance strategies that yield optimized results and enhanced business outcomes.

Want to learn more?

• For more information on the MCP, you can read our previous blog here.
• You can also see it in action on our recent shift-left performance webinar.
• If you want to talk with us to learn more about AI innovation in NeoLoad, schedule a demo today!