For platform, DevEx, AI tooling, release, and trust teams

Map what AI coding workflows can change.

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

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.

01

Action path map

Shows how a request or workflow reaches credentials, actions, targets, approvals, and evidence.

02

Agent Action BOM

Summarizes path, authority, target, approval status, proof coverage, and the next review.

03

Evidence packet

The receipt for high-impact actions: owner, credential source, approval decision, validation, outcome, and open items.

04

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.

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 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 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.

01

Scan delivery artifacts

Clyra reads workflow files, CI jobs, MCP configs, agent instructions, package scripts, credential references, and PR-linked provenance when available.

02

Build the action path map

It connects the workflow to reachable actions, credentials, targets, approvals, and evidence.

03

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

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 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 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.

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