Initial run / every pipeline
Standard QA scan
A fast, pipeline-friendly scan of the change set: common defect patterns, test and lint signals, and high-confidence issues that should block or warn before merge.
Products Phoenix AI Agentic QA
Phoenix AI Agentic QA
Agentic quality analysis that plugs into your build pipelines and deepens over PR, nightly, and monthly cadences.
Contact for scoping
Phoenix is TekZilla's AI agentic QA product. It joins your continuous integration and delivery pipelines so every change is examined with agents that reason about code quality, risk, and regressions. Analysis is multi-level: a fast standard scan on each run, a deeper nightly pass over the day's contributions, and a monthly full-estate sweep for security, integrations, and lasting improvement.
Built for build pipelines
- Add Phoenix as a stage in GitHub Actions, GitLab CI, Jenkins, Azure Pipelines, and similar systems
- Publish agent findings as pull-request comments, annotations, or artifacts your gates already consume
- Configure fail-on-critical and warn-on-debt policies so quality bars stay enforceable without noise
What teams get
- Continuous QA that scales with commit volume instead of review bandwidth alone
- Layered coverage: PR speed, nightly depth, monthly estate-wide security and integration review
- Actionable insights prioritized for remediation, not raw scanner dumps
- Fits alongside TekZilla services when you want human experts to act on Phoenix findings
Multi-level analysis over time
Phoenix does not stop at a single pass. The same agent stack runs at different depths on schedules that match how software actually ships.
Nightly
Deep analysis of the day's work
A deeper agent pass over all work contributed during the day. Cross-file reasoning, regression risk, and patterns that are easy to miss in a single pull request.
Monthly
Full codebase sweep
A full sweep of the entire codebase focused on security and integration points, plus code quality improvement suggestions and actionable insights your team can schedule into the next sprint.
See it in context
Interested in Phoenix AI Agentic QA?
Share your stack and goals. We will scope fit, onboarding, and next steps for your teams.