Test automation and code security
We set up the checks that run each time code changes: a security review on every pull request, automated application tests, and regular performance runs, with reports your team can act on.
A security check on every pull request, automated tests for your applications and performance runs on a schedule, all governed by the harness.
- Pull request checks
- CI workflows
- Scheduled jobs
- Merge protection rules
- Static code analysis
- Dependency scanning
- Secret detection
- Model-assisted code review
- Unit tests
- API tests
- Browser tests
- Model-assisted test generation
The challenge
Software changes faster than people can review it. A pull request may be merged after a quick read, and security flaws, broken behaviour or slow code can reach production before anyone notices. AI-assisted coding raises the volume of change further.
Manual testing and one-off security audits do not keep pace. Tests are written late or not at all, performance is measured only after users complain, and nobody can show an auditor what was checked on a given release or who approved the merge.
What it does
Pull request security review
Every pull request is reviewed for security issues such as unsafe input handling, exposed secrets and risky dependencies, with findings posted back on the request for the author to fix.
Merge gating
Merges can be blocked until security and test checks pass, with clear severity thresholds your team agrees in advance, so a failing check is a decision and never an accident.
Automated test generation
Tests for your application are drafted from its code and behaviour, then reviewed by your engineers, widening coverage without asking the team to write every case by hand.
Automated test runs
Unit, API and browser tests run automatically on each change and on a schedule, so regressions are found within minutes of the change that caused them.
Scheduled performance testing
Load and response-time runs execute at regular intervals against agreed environments, so slow-downs are caught as they appear and not when users report them.
Reports and trend tracking
Security findings, test results and performance numbers are collected into reports and tracked over time, showing whether quality is improving release by release.
How it works
Agree the checks
We review your repositories, release process and risk areas, then agree which checks run, which severities block a merge and which environments are tested.
Wire into delivery
Security review, tests and performance runs are connected to your pull request and build workflow, so they start automatically without extra steps for developers.
Run and report
Each pull request and each scheduled run produces findings and results, posted on the request and collected in a report with the evidence behind every result.
Review and improve
Your team triages findings, accepts or rejects generated tests, and we tune thresholds and coverage using the trend data so the checks stay useful over time.
Under the hood
- Delivery workflow
- Pull request checks
- CI workflows
- Scheduled jobs
- Merge protection rules
- Security review
- Static code analysis
- Dependency scanning
- Secret detection
- Model-assisted code review
- Testing
- Unit tests
- API tests
- Browser tests
- Model-assisted test generation
- Performance and reporting
- Load testing
- Response-time metrics
- JSON results
- HTML and PDF reports
Business outcome
Flaws found before they ship. Security issues are caught on the pull request, while the author still has the context and a fix costs the least, and not after release.
Broader, steadier test coverage. Generated and automated tests cover more of the application and run on every change, so releases depend less on individual memory and manual effort.
Performance regressions caught early. Regular performance runs show when a change makes the application slower, so teams fix it in the same sprint and not during an incident.
Evidence for every release. Reports and trend history show what was checked, what was found and who approved the merge, ready for customers, auditors and leadership.
Where it is used
- A product team wants every pull request security-reviewed, with high-severity findings blocking the merge until fixed.
- An engineering group with thin test coverage generates and automates tests for an existing application before a major release.
- A platform team schedules weekly load runs against a staging environment and tracks response times from release to release.
- A regulated business needs a record of security checks and approvals on every code change to support its audits.
Frequently asked questions
Does the security check replace a human reviewer?
No. It reviews every pull request consistently and flags likely issues, but your engineers still make the call. Findings can be accepted, fixed or waived, and each decision is recorded.
Can it block a merge?
Yes, if you choose. You set which severities block a merge and which only warn. Many teams start in warn-only mode, review the findings, and turn on blocking once the noise is low.
Who reviews the generated tests?
Your engineers do. Tests are proposed as ordinary changes with their own review, so nothing enters the suite unseen, and tests that prove unhelpful can be removed or revised.
Which AI models does it use?
The service is model-agnostic. Review and test generation can run on frontier, open-weight or small open-source models of your choice, routed through the harness under your policies.
See it on your own documents and data
Tell us what you want to automate and we will show you how it runs inside the harness.