Action-control graph
Shows how a request or workflow reaches credentials, actions, targets, approvals, and evidence.
Clyra Control for AI-assisted engineering
Map what AI coding tools can change.
Agent-assisted work now reaches PRs, CI/CD, credentials, internal tools, and deploy paths. Clyra Control maps the action path so teams know what can run, what needs review, and what proof remains.
Action-control graph → 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 agent autonomy.
Core object
Clyra maps the action path, not just the tool.
An action path connects actor, authority, action, target, approval, and evidence for one workflow. It gives engineering, platform, and security 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 graph, a BOM, and an evidence packet.
Clyra turns one workflow into three reviewable outputs: an action-control graph, an Agent Action BOM, and an evidence packet.
Agent Action BOM
Summarizes path, authority, target, approval status, proof coverage, and the next review.
Evidence packet
The receipt for high-impact actions: owner, credential source, approval decision, validation, outcome, and gaps.
Control boundary
Allow, review, approve, or block decisions for credentialed, tool, deploy, publish, cloud, or destructive actions.
Why teams care
One map for the teams responsible for AI-assisted delivery.
The goal is not to slow normal coding. It is to give each owner the same view of the action path, the authority behind it, and the proof that remains after high-impact work.
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.
Security and trust
Answer customer, audit, or incident questions with evidence instead of tribal knowledge.
System view
Inventory is not control. The graph shows reachability.
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.
Example path: AI-assisted PR -> release workflow change -> NPM_TOKEN -> package publish -> no visible approval/proof
Product view / Action-control graph
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-control graph
It connects the workflow to reachable actions, credentials, targets, approvals, and evidence.
Show decisions and gaps
Approval, policy, owner, and evidence gaps 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
An action-control platform for AI-assisted software delivery. It turns reachable workflow paths into reviewable artifacts.
Clyra Control is not
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.
Existing controls
Clyra does not assume controls are missing. It resolves each path as detected, declared, externally referenced, not applicable, or unresolved based on available evidence.
Not every path is high risk
Clyra separates source-only, non-prod, and low-impact workflows from paths that can write, execute, use credentials, deploy, or affect production.
Source privacy
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.
Coverage limits
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
Short answers for engineering, platform, and security 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 maps what AI-assisted workflows can change across repos, CI/CD, tools, credentials, and deploy paths, then shows what can stay fast and what needs review.
What problem does Clyra Control solve?
Approved-tool lists do not show when AI-assisted work can change workflow files, reach CI/CD secrets, call tools, publish packages, run cloud commands, or trigger release automation.
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 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.
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 approval or proof is missing 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, approval gaps, Agent Action BOM, and evidence packet