QA & Release Quality

Validate releases faster with the QA team you have.

Built on NVIDIA OpenShell, the open source runtime for AI agents.

Build QA agents on the HyperShell platform to select and run relevant tests, reproduce bugs, investigate failures, and maintain regression suites. Our forward-deployed engineers work with your team to build the initial workflows around your existing CI/CD pipeline and test runners. Your team can then modify those agents and create new ones independently.

Discuss a QA pilot See the platform

Who it helps and the problem

Who this is for

SaaS companies with automated CI/CD pipelines and complex test runners.
Teams where release validation is the constraint, not writing the code.
Products with large dependency graphs and partner integrations that make regression maintenance expensive.
VPs of Engineering and QA leaders responsible for release quality.

The recurring problem

Long end-to-end test runs lead teams to test less often and delay validation. AI-assisted development increases the volume of code, and the same QA team has to keep pace.

Deciding which tests a change actually needs is where the time goes, and it is the first workflow we build.

Example workflow

Where we start

1
Identifying and executing the tests relevant to a code change
2
Automatically reproducing bugs submitted by customers
3
Maintaining regression suites across complex dependencies and integrations
4
Debugging issues and generating PRs to address QA failures

An example workflow

1Pull request opened
2Determine relevant coverage using your agreed rules
3Execute the tests
4Reproduce and investigate failures
5Present the evidence
6Confirmed acceptance

Change-based test selection is built with your team for your codebase and rules. It is not a packaged feature.

First engagement and success measures

The first engagement

We scope an initial workflow around a defined application or service, its existing pipeline and test runners, and your agreed validation requirements.

Our forward-deployed engineers build it with your team, in your environment, then hand over so your engineers can modify it and add new agents.

How we measure success

Primary: elapsed time from PR to confirmed acceptance. We define the starting PR event and the acceptance event with you, rather than substituting PR merge or a CI pass.
Secondary: human investigation effort.
A speed improvement only counts if your agreed coverage and review requirements are still met.

These are the evaluation criteria for a pilot, agreed with you up front. They are not published results.

Test changes require review. Agents do not improve pass rates by weakening assertions or skipping tests.

What we can show and next step

What we can show today

We demonstrate the platform and the implementation approach with current development workflows, JIRA triage, and SBOM assembly. These show how agents are built and governed on HyperShell; they are not QA-specific results.

Open the platform walkthrough

A walkthrough of the HyperShell platform, not a demonstration of completed QA results.

What you get

Platform: Build and expand agents within approved Agent Envelopes on the HyperShell platform, built on OpenShell.
Implementation: Work with our forward-deployed engineers to build the first workflows in your environment, then modify agents and create new ones independently.
Support: Get ongoing support for the underlying platform, including updates and bug fixes.

Discuss a QA pilot.

Discuss a QA pilot