Action path map
Shows how a request or workflow reaches credentials, actions, targets, approvals, and evidence.
For platform, DevEx, AI tooling, release, and trust teams
Agent-assisted work now reaches PRs, CI/CD, credentials, internal tools, and release paths. Clyra Control maps the action path so teams know what can run, what needs review, and what proof remains.
Action path map → Agent Action BOM → Evidence packet.
The control gap
A normal PR can change code. It can also change the workflow that uses a standing token.
Clyra shows the path from assisted work to credentialed action before teams expand what agents can safely do.
Core object
An action path connects actor, authority, action, target, approval, and evidence for one workflow. It gives engineering and platform teams a concrete object to review, not another AI inventory.
One object for reachability, control, and proof.
What you get
Clyra turns one workflow into three reviewable outputs: an action path map, an Agent Action BOM, and an evidence packet.
Shows how a request or workflow reaches credentials, actions, targets, approvals, and evidence.
Summarizes path, authority, target, approval status, proof coverage, and the next review.
The receipt for high-impact actions: owner, credential source, approval decision, validation, outcome, and open items.
Allow, review, approve, or block decisions for credentialed, tool, deploy, publish, cloud, or destructive actions.
Why teams care
Clyra helps teams decide which AI-assisted workflows can run alone, which need review, which need approval, and which should be blocked.
Keep AI coding adoption moving without losing track of which workflows can change real systems.
Give teams AI speed without creating invisible CI/CD, credential, and release risk.
Answer customer, audit, or incident questions with evidence instead of tribal knowledge.
System view
Clyra shows where normal engineering work becomes authority to change a system: the credential used, the action reachable, the target affected, and the approval or proof that exists. The gap appears when AI-assisted work creates a new authority path before the team can review, approve, or prove it.
Product view / Action path map
How it works
Clyra reads workflow files, CI jobs, MCP configs, agent instructions, package scripts, credential references, and PR-linked provenance when available.
It connects the workflow to reachable actions, credentials, targets, approvals, and evidence.
Approval, policy, owner, and evidence coverage become a BOM, evidence packet, and first control boundary.
Trust boundaries
Clyra helps teams move from approved-tool lists to action control. Discovery shows reachable paths. Enforcement depends on covered boundaries, policy, and connected systems.
An action-control platform for AI-assisted software delivery. It turns reachable workflow paths into reviewable artifacts.
A generic AI inventory, SIEM, IAM, PAM, CNAPP, GRC tool, model gateway, or replacement for your CI/CD controls. Those tools matter; Clyra shows which delivery paths use them to change systems.
Clyra does not assume controls are missing. It resolves each path as detected, declared, externally referenced, not applicable, or unresolved based on available evidence.
Clyra separates source-only, non-prod, and low-impact workflows from paths that can write, execute, use credentials, deploy, or affect production.
Clyra is designed to start from local or private scanning. Raw source is not retained unless explicitly agreed; the useful output is a redacted graph, BOM, and evidence packet.
Static discovery can show reachable paths and proof that is not visible in scanned artifacts. Runtime enforcement, final outcome verification, and cloud/IAM depth depend on the systems connected.
FAQ
Practical answers for teams deciding what stays fast, what needs approval, and what evidence should remain after AI-assisted work reaches delivery systems.
Clyra Control maps what AI-assisted workflows can change across repos, CI/CD, tools, credentials, and release paths, then shows what can stay fast and what needs review.
Approved-tool policies are useful, but they do not show whether the delivery environment actually enforces the boundary. Clyra maps when AI-assisted work can change workflow files, reach CI/CD secrets, call tools, publish packages, run cloud commands, or trigger release automation.
No. Clyra is meant to keep normal coding fast and review only actions that can use credentials, change workflows, call tools, deploy, publish, or affect production.
Not exactly. Monitoring shows what happened after an agent or workflow runs. Clyra maps what the workflow can change before it becomes a control problem: authority, action, target, approval, and proof.
Clyra supports local or private scanning. Raw source is not retained unless agreed; most signals come from workflows, package scripts, tool config, and credential references.
Those tools find secrets, identities, permissions, or runtime decisions. Clyra ties them back to the engineering path: where work came from, what it can affect, and whether approval or proof exists.
Get started
Clyra maps what changed, which authority was reachable, and what control coverage and proof remain before teams expand the pattern.