OpenText EPE 26.1 adds an AI Usage report that gives release owners aggregated visibility into AI query consumption across supported performance engineering products. That matters when AI-assisted work progresses from individual experimentation into a managed delivery capability with budget, security, and audit implications.
AI usage becomes governable
The new AI Usage page in the Core Performance Engineering Platform provides a consolidated view of AI query consumption. For engineering leaders, this creates a practical control point for understanding where AI assistance is being used and how demand is developing across teams.
This supports better operating decisions, including:
- Establishing accountable owners for AI-enabled performance engineering.
- Monitoring adoption against subscription capacity and budget.
- Identifying teams that need training, guardrails, or workflow review.
- Providing evidence for internal AI governance discussions.
Usage data alone is not governance. Teams still need agreed policies for approved use cases, access controls, data handling, and escalation when generated output affects release decisions.
Faster scripting with better context
Aviator for Scripting in VuGen expands the scripting assistance available to performance engineers. Enhancements include browser-based single sign-on, creation of data files under the work folder, parameter summaries if needed, and context-aware suggestions based on script content and execution state.
The release also improves support for Java protocol error logs and brings AI assistance to the TruClient 2.0 Web JavaScript editor. An upgraded language model is intended to provide more detailed and accurate responses.
For delivery organizations, the value is not simply faster script creation. It is reduced dependence on scarce protocol specialists for routine investigation and setup work. Teams should still require peer review for generated scripts, correlation logic, test data, and workload models; AI suggestions can be useful, but they are not release evidence.
Analysis support preserves investigation context
Aviator for Analysis now supports predefined prompts and can append results to the current conversation without losing context. This helps analysts structure recurring investigation tasks while keeping the discussion tied to the active test result set.
Chat history can also be reopened, pinned, and renamed. These usability changes matter in long-running performance investigations, where teams often need to reconnect findings to a specific release, workload model, or defect decision.
A sensible governance approach is to retain formal performance conclusions in the approved test record or release evidence repository. AI conversations can accelerate analysis, but the accountable engineer should validate findings, document assumptions, and record final recommendations through established controls.
MCP expands controlled workflow automation
The Enterprise Performance Engineering MCP server adds AI-assisted report generation and broader test-asset management actions. Users can create consolidated custom PDF reports by selecting report sections, choosing whether headers are included, and adding related trend reports.
The updated workflows also cover more actions for test sets and test-set folders. This can reduce manual work for teams managing repeated release cycles, especially where performance reporting is standardized across products or portfolios.
Key operational considerations include:
- Restrict MCP access according to role and environment.
- Confirm that test-set changes follow existing approval requirements.
- Define approved report templates for executive and audit audiences.
- Log generated artifacts alongside the test run and release record.
MCP standardizes how AI clients interact with supported workflows, but it does not replace change control. A permission model and clear ownership remain necessary.
Large-report handling improves reliability
Trend reports and HTML report packages are now downloaded in chunked mode. This is a direct improvement for programs that generate large result sets, extended trend histories, or detailed evidence packages.
After download, AI clients can generate standalone HTML reports or custom reports from the original package. This gives teams more flexibility in how performance results are packaged for release managers, application owners, and risk stakeholders.
The workflow impact is meaningful for regulated or high-assurance delivery environments. Teams can standardize artifact retention, reduce failures caused by large downloads, and preserve a consistent evidence trail from execution through release approval.
DevWeb workflow guidance improves
The DevWeb MCP server improves handling for recording, generation, and replay processes, while adding guidance for working with MCP workflows. This should help teams apply AI-assisted support more consistently during script development.
Senior QA and DevOps leaders should treat this as an opportunity to define reusable patterns: which script actions may be AI-assisted, which changes require review, and how generated work is validated before it enters a shared repository.
How Merito helps
Merito helps enterprises introduce EPE 26.1 capabilities without weakening delivery controls. We assess Aviator and MCP readiness, define role-based workflow patterns, establish AI usage governance, and integrate performance evidence into CI/CD and release-management processes.
Our teams can also help standardize report templates, test-asset controls, and validation practices so AI-assisted activity supports faster decisions while keeping accountable engineering review in place.
Merito is an authorized OpenText reseller and services partner. Our OpenText EPE team can scope licensing, sizing, and rollout for 26.1, and our enterprise upgrade services help you plan and validate the upgrade with minimal disruption to release schedules.
