Claude Code, Cursor, Copilot, Codex, or internal agents are moving from suggestions into PRs and CI/CD.
For platform teams scaling AI coding
See what AI-assisted engineering can trigger before it reaches release.
Clyra follows AI-assisted delivery paths through repositories, CI/CD, credentials, approvals, and release actions. See which paths can write, publish, or deploy, which controls are supported by evidence, and what still needs verification.
Start with one workflow or 10 recent AI-assisted PRs
Local/private scan; no raw source retained by default
Findings and evidence delivered in 10 business days
Where the boundary appears
A normal PR can also change the job that publishes, deploys, or runs with standing credentials.
AI tool
PR
release.yml
NPM_TOKEN
npm publish
release approval unresolved
Clyra separates what is detected from what is declared, externally verified, or still unresolved.
Where the work starts
Use Clyra inside a rollout, AppSec, release, or audit review already underway.
The first assessment does not require a new governance program. It answers a concrete control or evidence question for one workflow.
A workflow can change CI jobs, call tools, use credentials, publish, deploy, or reach production.
A security questionnaire, SOC 2 review, or ITGC review asks how AI-assisted changes are controlled.
The team needs to reconstruct what changed, which authority was available, who approved it, and what ran.
What Clyra checks
Approved tools do not show what the delivery path can trigger.
Clyra follows one AI-assisted delivery path through the repository, CI/CD, credentials, approvals, and release action. Existing controls count when evidence supports them; anything else stays unresolved.
What you receive
One workflow. Three usable outputs.
Start with selected repositories, workflows, or recent AI-assisted PRs. Clyra prioritizes consequential paths, then follows one path deeply enough for platform, security, and trust teams to share a decision-ready record.
Prioritized workflow map
Ranks paths in the selected scope, then follows the chosen path through jobs, tools, credentials, targets, approvals, and release actions.
Output: ranked paths + reachable actions
Control coverage
Shows which repository rules, reviewers, CI/CD gates, and approvals are supported by evidence and which remain unresolved.
Output: prioritized control decision
Review-ready record
Collects the owner, changed files, authority, approval, validation, outcome evidence, and unresolved items in one shareable artifact.
Output: Agent Action BOM + evidence packet
Who uses the finding
One workflow map, four practical decisions.
The same finding gives each team the evidence it needs without forcing a new governance program or replacing existing controls.
Can this AI-assisted change trigger a credentialed job or release action, and what proves the right control applies?
Platform and DevEx
Expand AI coding while seeing where CI/CD, credential, or release reach needs a narrow guardrail.
Engineering leadership
Decide where agents can do more and focus review time on changes that can affect real systems.
AppSec and security
Verify whether repository, identity, CI/CD, and approval controls cover the complete workflow.
Risk, audit, and customer trust
Answer review questions with a traceable record of authority, approval, validation, and unresolved evidence.
Trust and scope
Your controls stay in place. Clyra tests whether they cover the workflow.
GitHub, GitLab, CI/CD, IAM, secrets, and approval systems remain the control points. Clyra connects their evidence around one workflow. See how the coverage differs.
Your AI policy may require review. Clyra checks whether the available evidence verifies that requirement on paths that can write, use credentials, publish, or deploy.
Existing controls count
Repository rules, CODEOWNERS, CI/CD gates, environment approvals, identity controls, and security tools are recognized when evidence supports them.
Unknown is not missing
Each control is marked detected, declared, externally verified, not applicable, or unresolved. Static visibility is not overstated as proof.
Consequential paths first
Source-only and low-impact work stays separate from changes that can run jobs, use credentials, call tools, publish, deploy, or affect production.
Private by default
Local or private scanning comes first. Raw source is not retained unless explicitly agreed; the deliverable is a redacted map and evidence record.
Honest coverage limits
Static analysis can show reachable paths. Runtime outcomes, final approvals, and cloud/IAM depth require evidence from connected systems.
Fixed first engagement
Start with one workflow or 10 recent AI-assisted PRs. The goal is a decision-ready finding, not a platform replacement project.
Useful before a call
Start with a real finding.
Review the deliverable, trace a simulated release path, or use the checklist in an AI rollout or AppSec conversation.
Sample finding
Redacted workflow assessment
See the path, reachable credential, existing control evidence, unresolved item, and next check.
Interactive lab Trace a release pathBuild a simulated AI-assisted change through CI/CD, credentials, approval, and release.
Review checklist Check one AI coding workflowReview workflow files, jobs, tools, credentials, approvals, and evidence without slowing every PR.
Field notes Research behind ClyraTechnical notes on AI-assisted delivery, control coverage, authority, and evidence.
FAQ
What teams usually ask before the first assessment.
Practical answers for platform, engineering, security, release, and trust reviewers.
What does Clyra assess?
Clyra reviews AI-assisted delivery paths across repositories, CI/CD, credentials, approvals, and release actions. It prioritizes paths that can write, use credentials, publish, or deploy, then shows which controls are supported by evidence and what remains unresolved on one selected path.
Does Clyra replace GitHub, CI/CD, IAM, or security tools?
No. Those systems remain the control points. Clyra connects their evidence around one workflow so the team can verify whether the change-to-release path is covered.
Will this slow developers down?
It should not. Normal development stays fast. Review focuses on changes that can alter workflows, use credentials, call tools, publish, deploy, or affect production.
Can an AI-assisted change reach CI/CD secrets?
Sometimes indirectly. The agent may not read a secret directly, but an AI-assisted PR can change a workflow, package script, tool config, agent instruction, or release path that later runs with CI/CD secrets or release credentials.
What does the team receive?
A workflow reach map, credential and release-path analysis, existing control coverage, unresolved evidence, a prioritized next step, and a review-ready Agent Action BOM and evidence packet.
What can a static scan prove?
It can show reachable code and configuration paths. Runtime outcomes, final approvals, and cloud/IAM details require connected-system evidence, so Clyra marks those items unresolved until verified.
Does unresolved mean a control is missing?
No. Unresolved means the available evidence does not yet verify that the control exists or applies to that path.
Can Clyra prove a change was AI-generated?
Only when reliable provenance exists. Otherwise, Clyra describes the workflow as AI-assisted or agent-accessible and does not claim authorship.
How does the first engagement start?
Select one consequential workflow or 10 recent AI-assisted PRs. Agree on local or private access, then receive the assessment in 10 business days after scope and access are confirmed.
10-business-day assessment
Map one AI-assisted delivery workflow.
Use the assessment for an AI rollout, AppSec review, release review, audit request, or customer assurance question. Typical delivery is 10 business days after scope and access are confirmed.
Bring
one consequential workflow or 10 recent AI-assisted PRs near CI/CD, tools, credentials, or release
Get
reachable jobs and actions, credential reach, control coverage, unresolved evidence, and a prioritized next step