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
Know what AI-assisted engineering can change before you delegate more.
Clyra maps one workflow from PRs to CI/CD, credentials, tools, and release paths, then shows what can run alone, what needs review, what needs approval, and what proof is missing.
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 release token.
AI tool
PR
release.yml
NPM_TOKEN
npm publish
Clyra shows the path from assisted work to credentialed action before teams expand what agents can safely do.
Core object
The action path is the control 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.
actor
authority
action
target
approval
evidence
One object for reachability, control, and proof.
What you get
A path map, a BOM, and an evidence packet.
Clyra turns one workflow into three reviewable outputs: an action path map, an Agent Action BOM, and an evidence packet.
Agent Action BOM
Summarizes path, authority, target, approval status, proof coverage, and the run / review / approve / block decision.
Evidence packet
The receipt for high-impact actions: owner, credential source, approval decision, validation, outcome, and open items.
Why teams care
One map for the teams responsible for AI-assisted delivery.
Clyra helps teams decide which AI-assisted workflows can run alone, which need review, which need approval, and which should be blocked.
Shared question: can this workflow write, execute, use credentials, call tools, deploy, or touch production?
Engineering leadership
Keep AI coding adoption moving without losing track of which workflows can change real systems.
Platform and DevEx
Give teams AI speed without creating invisible CI/CD, credential, and release risk.
Release and trust reviewers
Answer customer, audit, or incident questions with evidence instead of tribal knowledge.
System view
Inventory is not control. The path shows reachability.
Clyra shows where normal engineering work gains authority: credential, action, target, approval, and proof. The gap appears when AI-assisted work creates a new authority path before the team can review or approve it.
Example path: AI-assisted PR -> release workflow change -> NPM_TOKEN -> package publish -> no visible approval/proof
Product view / Action path map
Context
Mapped path
Approval / policy boundary
Delegation path
human request
→
agent workflow
→
repo / PR
Authority path
credential
→
reachable action
→
target system
Control path
approval rule
→
policy decision
→
evidence packet
How it works
From delivery artifacts to action decisions.
Scan delivery artifacts
Clyra reads workflow files, CI jobs, MCP configs, agent instructions, package scripts, credential references, and PR-linked provenance when available.
Build the action path map
It connects the workflow to reachable actions, credentials, targets, approvals, and evidence.
Show decisions and coverage
Approval, policy, owner, and evidence coverage become a BOM, evidence packet, and first control boundary.
Trust boundaries
Clear about coverage, privacy, and limits.
Clyra helps teams move from approved-tool lists to action control. Discovery shows reachable paths. Enforcement depends on covered boundaries, policy, and connected systems.
Clyra Control is
A way to map AI-assisted delivery paths and turn reachable workflow authority into reviewable artifacts.
Clyra Control is not
A generic AI inventory, SIEM, IAM, PAM, CNAPP, GRC tool, model gateway, or CI/CD replacement. Clyra shows which delivery paths use those controls to change systems.
Existing controls
Clyra does not assume controls are missing. Each path is resolved as detected, declared, externally referenced, not applicable, or unresolved based on evidence.
Not every path is high risk
Source-only, non-prod, and low-impact workflows are separated from paths that can write, execute, use credentials, deploy, publish, or affect production.
Source privacy
Clyra starts from local or private scanning. Raw source is not retained unless explicitly agreed; the useful output is a redacted graph, BOM, and evidence packet.
Coverage limits
Static discovery can show reachable paths and missing proof. Runtime enforcement, final outcome verification, and cloud/IAM depth depend on connected systems.
FAQ
Short answers for engineering, platform, and trust reviewers.
Practical answers for teams deciding what stays fast, what needs approval, and what evidence should remain after AI-assisted work reaches delivery systems.
What is Clyra Control?
Clyra Control helps teams move from AI tool usage to safe delegation for AI-assisted engineering: what can act, under whose authority, against which system, with what review and proof.
What problem does Clyra Control solve?
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.
Will this slow developers down?
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.
Is this agent monitoring?
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.
Will this require access to source code?
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.
How is Clyra different from secret scanning, IAM, NHI, PAM, or agent gateways?
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
Start with one workflow or 10 recent AI-assisted PRs.
Clyra maps what changed, which authority was reachable, and what control coverage and proof remain before teams expand the pattern.
Bring
one workflow or 10 AI-assisted PRs near CI/CD, tools, credentials, or releases
Get
action path, credential reach, control coverage, Agent Action BOM, and evidence packet