Three layers. One always-on Digital Teammate.
Nogrunt works in a continuous loop - learning your product, generating and running tests, and improving with every sprint. Here is how the three layers connect.
First, Nogrunt learns your product
Nogrunt builds a context model of your application - reading Jira stories, BDD scenarios, GitHub commits and live screen behaviour. Tests built on context reflect how your product works, not just what buttons exist.
- Jira stories, epics and acceptance criteria
- BDD feature files and scenario definitions
- GitHub commits and pull request descriptions
- Live application behaviour via bot observer
Then, it generates, executes and maintains your suite
The Intelligence Engine generates test cases, authors scripts, runs your full suite and heals broken tests after each deployment - continuously, every sprint, without human triggers.
- Generates test cases from requirements
- Authors scripts for web, mobile and API
- Runs the full suite on every CI/CD trigger
- Detects and heals broken tests automatically
Finally, it closes the loop between code and quality
Results surface in your existing tools - Jira tickets updated, Teams channels notified, GitHub PRs decorated with test summaries. Quality becomes a continuous signal, not a gate.
- GitHub, Azure DevOps - triggers on every commit or PR
- Jira - updates tickets with coverage and failures
- Microsoft Teams - real-time summaries and alerts
- CI/CD pipelines - quality gates block failed deploys
Nogrunt fits inside your sprints. Not the other way around.
Nogrunt operates inside your sprints from day one - generating tests in the same sprint the story is written, executing them in the same pipeline the feature ships through, and surfacing failures in the tools your team already uses.
First regression suite authored and running in parallel
Shift left achieved, defects caught before QA
Full team collaboration, 3x productivity increase