Who owns it—and what may it do?
Make the owner, purpose, approved tools, data, systems, destinations, and prohibited actions visible.
Customer-managed AI worker control plane
Govern the AI workers you build, buy, or deploy. Your governance model. Your risk appetite. Your controls. Operationalized for AI Workers.
Scaled Agents is a customer-managed control plane that connects AI Worker identity, authority, risk, human oversight, runtime decisions, and evidence to the governance practices your enterprise already uses.
The Operating Challenge
AI Workers are gaining operational authority faster than many organizations can govern it.
Scaled Agents turns the questions enterprises already ask into operating controls and evidence while formal governance authority remains with accountable customer owners.
What requires human approval?
Route consequential, unclear, external, or higher-risk decisions to accountable customer reviewers.
Should this action proceed—and can we prove why?
Evaluate the specific request against current policy, context, evidence, and lifecycle state, then preserve the decision path for independent review.
Executive Perspectives
Give each accountable leader a clear governance question.
Scaled Agents should help each enterprise owner reach a clear answer quickly: how to scale AI adoption responsibly, control AI risk, operationalize AI Workers, and prove governance without treating readiness artifacts as formal approvals.
CIO / CTO
Scale AI adoption responsibly with an operating record for ownership, approved scope, lifecycle status, and review-ready evidence.
View Product OverviewCISO
Control AI risk by making authority, data boundaries, tool use, escalation paths, and pause conditions visible before higher-risk action.
View Security ArchitectureCAIO
Operationalize AI Workers through consistent intake, Passport records, Toll Gates, Human Review, Stamps, and lifecycle visibility.
Create a Scaled AgentCRO / GRC
Prove governance with source-linked records, evidence trails, owner decisions, framework-aware readiness views, and review boundaries.
View Framework ReadinessAudit
Inspect what was reviewed, what remains blocked, what evidence exists, and which accountable owner must decide before reliance.
View Oversight ControlsLegal / Compliance
See where policy, privacy, contractual, and regulatory review must shape scope, conditions, evidence, and accountable decisions.
Open Governance ProofGo Deeper
Use the homepage for orientation. Use dedicated pages for depth.
The homepage now routes deeper Passport, oversight, shared responsibility, training, and resource detail to dedicated pages so buyers can move from orientation to the right review path without rereading the full operating model.
Passport record
Inspect the governed operating record, risk map, ownership, approved scope, and evidence posture for an AI worker.
Open Passport Record Open Passport StudioOversight and responsibility
Review executive reporting and the shared responsibility model before treating readiness artifacts as owner decisions.
Open Executive Oversight Open Shared ResponsibilityTraining and resources
Use public training paths and resource templates for education, review preparation, and governed implementation planning.
Open Training Catalog Open Public ResourcesOne Operating Model
Identity → Authority → Control → Action → Evidence
This is the simple model underneath the Scaled Agents architecture. It connects who the AI Worker is to what it may do, which conditions apply, whether a specific action may proceed now, and the evidence needed to reconstruct the decision.
Who is this AI Worker? Who owns it?
What may it do? Under whose authority?
What conditions must be satisfied?
Should this specific action proceed now?
Can we reconstruct and defend the decision?
Passport
Identity, ownership, purpose, scope, and standing authority.
Toll Gates
Required controls, evidence, and conditions.
Human Review
Accountable judgment where policy or risk requires it.
Entry Clearance
Short-lived authority for the specific action.
Clearance Desk
Controlled execution against the authorized action.
Clearance Stamp & Evidence Trail
What was authorized, what occurred, and the resulting evidence.
Explore the model
Overview covers the full image. Tabs 1-3 explain the numbered image areas. Advisor is the next step.
Public view
Overview
Scaled Agents gives teams a governed operating model for AI workers: who owns them, what they may do, what needs review, and what evidence supports the current status in a customer-hosted or customer-managed platform posture.
Named ownershipEvery AI worker should have a visible owner, purpose, scope, and lifecycle state before teams rely on it.
Review before relianceHigher-risk work can pause, route, or escalate through approval paths and evidence checks before consequential use.
Lifecycle visibilityMonitoring, evidence refresh, ownership changes, remediation, suspension, revocation, and retirement stay visible.
Review boundaryThis section explains the operating model. It does not represent legal advice, a compliance conclusion, security authorization, or approval for production use.
Licensed platform foundation
What Scaled Agents Provides
Step 1 in the image separates what Scaled Agents provides into licensed platform capabilities and bounded support resources. The platform creates reusable governance records; readiness, training, and advisory resources help teams design, configure, and roll out the customer-managed operating model.
Licensed platform capabilities
- Agent Passport captures AI worker identity, purpose, owner, risk, systems, scope, and review posture.
- Agent Registry keeps inventory, status, ownership, and lifecycle visibility organized.
- Stamps record reviewed events, evidence updates, review milestones, and lifecycle signals.
- Tolls define control gates where evidence, approval, or escalation may be required.
Support resources
- Readiness resources clarify the AI worker opportunity, business outcome, and review boundary.
- Operating-model guidance maps workflows, owners, reviewers, and control checkpoints.
- Governance templates help customers configure review paths, evidence expectations, and escalation rules.
- Workflow and agent design guidance shapes the governed work pattern before launch planning.
- Enablement and training prepare customer teams to operate the model with human accountability.
Image messageA structured foundation for enterprise agents starts with visible records, repeatable services, and clear ownership before scaling AI worker use.
Connected workflow
How They Work Together
Step 2 in the image shows the operating sequence from intake through improvement. Each row creates or updates governance context so the AI worker is visible before it moves closer to use.
01Use case intakeRequest and business context
02Agent Passport createdIdentity, purpose, owner, risk, systems
03Agent Registry updatedInventory, status, ownership
04Review evidenceSecurity, data, legal, business approval
05Control gates appliedDesign, access, launch, monitoring, renewal
06Launch and monitoringUsage, cost, performance, oversight
07Feedback and improvementUpdates, retraining, lifecycle decisions
DiscoverStart with the use case and business context before defining a governed AI worker.
Design, register, review, gateCreate the Passport, update the Registry, review evidence, and apply Tolls before higher-risk movement.
Launch, monitor, improve, renew or retireKeep usage, cost, performance, oversight, updates, retraining, and lifecycle decisions visible.
Business operating layer
How It Operates in the Business
Step 3 in the image shows the business operating model: a centralized foundation connected to human-governed agent operations, then applied close to the work across business functions.
Centralized foundationIdentity, governance, security, data boundaries, standards, and auditability create the common operating base.
Human-governed agent operationsOwners, approvers, reviewers, and domain teams keep AI worker activity accountable to the business context.
Procurementclose to vendor and tool decisions
Financeclose to cost and value context
Operationsclose to process execution
Legalclose to review boundaries
Customer Serviceclose to service handoffs
Riskclose to controls and escalation
Image messageCentralize the foundation. Scale the agents. Keep humans in control.
Advisor entry point
Readiness Advisor Overview
Use the Readiness Advisor to understand where an AI worker idea fits, what review may be needed, and what next step is appropriate before relying on a draft blueprint or recommendation.
Shape the ideaStart from a plain-language AI worker concept and clarify purpose, audience, workflow, ownership, and trust boundaries.
Surface review needsIdentify likely risk, data, approval, evidence, monitoring, and escalation considerations for human review.
Choose the next stepMove toward a guided intake, self-service form, readiness conversation, or deeper advisor page.
Public-safe useThe Advisor is a planning aid. It can help prepare intake context and next-step recommendations, but it does not approve an AI worker, authorize production use, or replace required human review.
The components connect enterprise governance to bounded action-time decisions without replacing accountable customer authority.
Your Governance. Made Operational.
Apply the governance you already have at the point where AI Workers act.
Scaled Agents does not replace your governance model. It provides the control-plane layer for applying your policies, standards, risk appetite, identities, approval authorities, and evidence requirements to the AI Workers you build, buy, or deploy.
Governance readiness explains what should be true. Observability explains what happened. The control plane connects both to the action-time decision.
Your enterprise governance
Policies, risk appetite, IAM, security, GRC, privacy, legal, data governance, architecture, procurement, and approval authorities remain customer-owned.
Identity and authority
Passport records make ownership, purpose, standing scope, approved boundaries, review posture, and missing inputs visible.
Controls and action-time decisions
Toll Gates, Human Review, Entry Clearance, and the Clearance Desk connect required conditions to the specific action request.
Your AI workforce and evidence
Built, purchased, SaaS, cloud, application, and agent-to-agent workflows remain customer-controlled while Clearance Stamps and the Evidence Trail support reconstruction.
Authority Changes
An AI Worker’s authority is contextual, bounded, and able to change.
Changes in identity, policy, risk, context, evidence, or lifecycle state can change what an AI Worker is permitted to do. Passport standing is not unrestricted runtime authority.
Admitted → Under Review
Establish the owner, purpose, standing scope, reviewers, and required evidence, then reassess when material conditions change.
Allow | Deny | Escalate
Evaluate each consequential request against current authority, controls, evidence, and required human judgment.
Pause → Suspended → Revoked
Make containment and loss-of-authority paths explicit when evidence, policy, identity, context, or operating conditions drift.
Expired or renewed
Do not treat standing records as permanent permission. Require current review and evidence before authority continues.
Public boundaryThis is planning and readiness language. It does not claim automated ROI measurement, live budget enforcement, regulatory approval, compliance conclusion, security authorization, audit opinion, or production authorization.
Govern AI agents as workers
Identity, scope, owners, lifecycle state, and evidence.
Control consequential action
Authority, runtime checks, approval validity, and evidence trails before higher-risk movement.
Standardize AI operations
Intake, onboarding, lifecycle management, training, and reusable governance patterns.
Evidence of Control
Can you prove the organization was in control?
Request → Authority → Control → Decision → Execution → Evidence. A log can prove that an action occurred. Scaled Agents helps preserve the evidence needed to determine whether it should have occurred.
1. Decision checks before action
Use these checks when an AI worker is about to touch tools, move data, send external communication, trigger cost, or support production-adjacent workflow.
Standing authority
Use the Passport to define purpose, owner, trigger rights, approved scope, prohibited actions, validity window, and review posture before relying on the worker.
Action-time check
Use runtime authorization to test the specific request against scope, approvals, evidence, data boundary, and target action.
Human decision path
When the request is sensitive, unclear, external, or higher risk, route it to accountable human review instead of letting it proceed automatically.
Replay-safe evidence
Preserve non-secret decision facts, Stamps, and evidence records so lineage can be reconstructed without rerunning the action.
Handoff continuity
Carry scope, state baseline, owner, approval status, and rollback context across agents, workflows, reviewers, and systems.
Fail-closed ruleIf owner, scope, approval, evidence, or current authority cannot be proven, the safer operating posture is to pause, block, require evidence, or escalate for human review.
Worked Example
One AI worker, one missing proof point, one visible stop.
A Procurement Intake AI Worker is asked to draft a supplier update. Its Passport shows the owner and approved purpose, but the requested destination is outside the approved tool boundary and the evidence record for external communication is missing. The Toll Gate blocks the action, creates an evidence item, and routes the request to Human Review instead of letting the worker send the update.
PassportOwner and purpose foundProcurement Operations owns the worker; draft supplier updates are in scope.
Toll GateEvidence gap detectedExternal-send evidence and destination approval are not present for this request.
DecisionBlocked, not sentThe action pauses because current authority cannot be proven.
Evidence TrailHuman review createdA review item and Stamp preserve why the request was blocked and what proof is needed next.
2. Records that support the decision path
These records explain where the worker came from, what review has happened, what authority exists, and what evidence should be preserved.
Idea
Start with the business outcome, workflow, affected audience, and trust boundary.
Blueprint
Create a draft planning artifact with role, risk tier, governance controls, reviewers, blockers, and next steps.
Passport
Document owner, purpose, scope, trigger rights, delegated authority, permissions, prohibited actions, evidence, lifecycle state, and review posture.
Toll Gates
Identify where data, tool use, cost, autonomy, external communication, or consequential action needs review before the decision window closes.
Human Review
Route unclear, sensitive, externally exposed, or higher-risk decisions to accountable reviewers who can change whether work proceeds.
Runtime Permit
Represent short-lived scoped authority for one proposed action when current purpose, evidence, scope, and approval context are present.
Action Broker
Evaluate whether the requested action should allow, deny, block, escalate, or require more evidence.
Evidence Trail
Use Stamps and evidence records to preserve review events, decision lineage, lifecycle changes, outcome validation, and rollback or correction context.
Review boundaryBlueprints, Passports, Toll Gates, Stamps, Runtime Permits, Action Broker decisions, and evidence trails are governance records and review aids. They are not legal conclusions, compliance approvals, security authorizations, production approvals, audit opinions, formal attestations, or formal decisions.
Platform Operating Model
Govern, operate, and measure enterprise agent workforces.
Scaled Agents™ is not an AI security point tool, compliance-only product, agent directory, MCP tool, cloud platform, managed service provider, or model-provider wrapper. It is a licensed, customer-hosted or customer-managed, provider-agnostic governance and operations platform for governing AI agents before they act across tools, data, systems, and workflows.
Trust signalGovernance and evidence-readiness planning for regulated and high-trust AI environments, including CMMC and FedRAMP-aware conversations without certification, authorization, or compliance claims.
Security, identity, model providers, SaaS tools, GCP, AWS, Azure, Cloudflare, APIs, workflow systems, and MCP-compatible patterns are customer-selected connected systems or execution environments around the platform. Scaled Agents supports governed connection planning through approved connectors and helps customers govern agents around those connections through identity, ownership, policy, evidence, runtime review, and lifecycle controls.
Passport
Governed identity, human owner, purpose, scope, permissions, lifecycle state, evidence, and review posture.
Toll Gates
Review and runtime gates for data, tools, cost, autonomy, external communication, and consequential action.
Stamps
Evidence markers for approvals, denials, actions, exceptions, lifecycle events, remediation, and outcomes.
Runtime Permit
Scoped, short-lived authority planning for a specific AI worker action when context and evidence support review.
Action Broker
Controlled action-path concept between AI workers and enterprise systems, using Passport, Toll, Policy, evidence, and review state.
Human Review
Accountable review workflow for approval, denial, escalation, exception, remediation, pause, or lifecycle decision.
Policy
Configurable decision logic and control rules for review, authorization, required evidence, and escalation paths.
Lifecycle Analytics
Visibility into status, risk, renewal, value, monitoring expectations, exceptions, incidents, and review-ready evidence context.
Board & Executive Oversight
Portfolio visibility into agent inventory, Passport coverage, risk exposure, value estimates, evidence completeness, incidents, exceptions, and scale or retire decisions.
Connector Hub and MCP-compatible patterns belong around this operating layer as governed destinations or integration patterns. Scaled Agents should remain provider-agnostic and should not imply live connector governance or MCP server operation unless implementation evidence and approval exist.
Board & Executive Oversight
AI governance should not only reduce risk. It should prove value.
Scaled Agents helps organizations connect every registered agent to ownership, oversight, evidence, risk exposure, policy exceptions, incidents, lifecycle state, and measurable business value.
Board Oversight Dashboard
Summarize registered agents, high-risk agents, pending reviews, expired evidence, human approval coverage, exceptions, material incidents, and regulatory readiness posture.
AI Risk Appetite
Define acceptable use cases, human-owned decisions, data classes, systems, escalation triggers, and pause, review, redesign, or retirement conditions.
Governance Economics
Use estimated, modeled, and risk-adjusted language to connect agent value, governance cost, cost avoidance, incident exposure, evidence confidence, and control coverage.
Review boundaryBoard views, readiness mappings, scorecards, value estimates, Passports, Stamps, and evidence summaries support governance preparation and oversight. They are not legal advice, formal compliance findings, audit opinions, security authorizations, production approvals, or financial assurance results.
Scaled Agents Passport
One governed operating record for AI workers.
The Passport connects identity, ownership, approved scope, review evidence, Toll Gates, lifecycle posture, and report views into one reviewable operating record for AI workers.
It helps define the approved purpose and intended outcome early enough for Toll Gates, Runtime Permits, Human Review, and Monitoring to evaluate whether the worker remains purpose-aligned before higher-risk work moves forward.
It gives teams a structured starting point for enterprise AI operations without treating a draft record, score, or readiness view as production authorization, legal approval, compliance conclusion, security approval, or an audit opinion.
Solutions Preview
Govern the path from idea to action.
Scaled Agents™ organizes the governance problems enterprise teams face as AI agents move closer to systems, tools, data, and business workflows: who owns the worker, what it may do, what requires review, what evidence exists, and what happens before consequential action.
Agent intake and assessment
Structured review paths for proposed AI workers, use cases, owners, risk tiers, prerequisites, and readiness evidence.
Toll Gates and Stamps
Governance checkpoints for recording reviewed transitions, access boundaries, evidence updates, exceptions, and activity records.
Portal preview
A preview customer experience for viewing agent status, ownership, risk posture, Passport state, support needs, and review records.
Workforce governance roadmap
Coming-soon placeholders for runtime governance, Passport APIs, CFO and board reporting, multi-agent orchestration, and agent-to-agent control planning.
Governance Assurance
Readiness support for control domains, evidence boundaries, external-review preparation, and human-owned launch or pause decisions.
Governed by people. Powered by agents.
Every AI worker has a human partner. Every action has oversight.
Scaled Agents™ connects AI workers to named human owners for clarity, oversight, and accountability. The structure keeps decisions traceable, boundaries respected, and human judgment in control.
Named human partner
Every AI worker has a human owner responsible for purpose and performance.
Clear oversight
Humans set boundaries, review exceptions, and approve sensitive actions.
Structured hierarchy
AI workers operate inside defined scope, escalation paths, and review routes.
Action visibility
Key decisions and activity records are prepared for review and improvement.
Human oversight and approval includes an Executive Sponsor, AI Program Lead, Revenue and Product Lead, Technology and Operations Lead, Risk and Governance Lead, and Data and Customer Lead. Example AI workers include Intake Agent, Requirements Agent, Marketing Agent, Sales Enablement Agent, Documentation Agent, IT Service Desk Agent, Test Automation Agent, Release Readiness Agent, Security Operations Agent, Audit Support Agent, Assurance Agent, Legal Review Agent, Data Governance Agent, Business Intelligence Agent, Customer Success Agent, and Support Triage Agent. The legend distinguishes Human Role, AI Worker, Approval and Escalation, and Audit Trail responsibilities.
Support Layer
AI-Powered Company Blueprint
Draft planning support for business readiness, AI knowledge worker roles, human review, advisor preparation, and launch-readiness conversations before broader use.
Support boundary. Advisory, blueprint, and training resources support evaluation and implementation of the licensed platform. They are not the core offer and do not replace customer validation, legal review, security review, compliance review, audit review, production approval, or accountable owner decisions.
Training Paths
Training for leaders, builders, reviewers, and AI worker owners.
Most AI training teaches people how to use tools. Scaled Agents™ Training helps teams understand how to govern AI workers.
Scaled Agents™ Training provides role-based learning paths for teams preparing to govern AI workers across intake, design, review, oversight, evidence, escalation, lifecycle management, and timely, meaningful, purpose-aligned outcomes.
Self-paced training manuals are available for public review and readiness planning, with role-based paths for AI worker foundations, governance readiness, train-the-trainer enablement, Passport reviewer basics, and action-time governance. Each path helps teams understand AI worker governance and readiness boundaries without exposing proprietary Scaled Agents methods, scoring logic, internal workflows, or platform implementation details.
Manuals available
Self-paced manuals are ready for review.
Six self-paced manuals are available for public review and readiness planning. They include lessons, exercises, knowledge checks, answer keys, and artifact prompts while keeping training completion separate from production approval, credentialing, or permission to operate.
Training manuals support education, readiness planning, and review preparation only. Completion or participation records, where used, confirm training activity only and do not grant approval, authorization, credential status, or permission to operate an AI worker.
Self-Paced Course Paths
Choose the role-based course path.
Each card below represents a public-facing course direction. Use the catalog for course detail and the Public Resources library for available manual downloads.
Foundation
Foundation for AI Worker Governance
For leaders, sponsors, business teams, and stakeholders who need a shared understanding of governed AI worker readiness.
- AI workers vs. AI tools
- Human accountability
- Ownership and role boundaries
- Readiness and evidence basics
Learner output: AI Worker Governance Role Map
Self-paced course previewBuild
Build Governed AI Workers
For builders, process owners, product teams, workflow designers, and implementation teams preparing AI worker use cases.
- Use case intake
- Workflow decomposition
- Access and authority boundaries
- Draft Agent Passport inputs
Learner output: AI Worker Blueprint
Self-paced course previewReview
Governance & Oversight
For reviewers, approvers, risk teams, compliance teams, security stakeholders, QA reviewers, and governance participants.
- Review responsibilities
- Risk and authority boundaries
- Evidence review
- Exception and escalation handling
Learner output: Governance Review Notes and Evidence Checklist
Self-paced course previewOperate
Specialize & Enable
For AI worker owners, operations teams, enablement leads, administrators, and trainers responsible for adoption and ongoing support.
- Agent owner responsibilities
- Monitoring expectations
- Change triggers
- Train-the-trainer basics
Learner output: Agent Owner Operating Plan
Self-paced course previewTraining completion record boundaries
Scaled Agents is not issuing certificates. Training completion or participation records may be used for internal tracking only. They do not grant AI worker approval, production deployment authority, legal assurance, compliance conclusion, security conclusion, audit approval, implementation approval, credential status, or permission to operate an AI worker.
Governance & Trust
Governance by default. Audit-aware by design.
Scaled Agents™ public materials use careful readiness language. They may describe framework-informed review, human oversight, Zero Trust principles, runtime governance concepts, nonhuman identity planning, cost and usage awareness, evidence mapping, data boundary metadata, pause and containment planning, and public planning templates, but they do not claim legal, regulatory, compliance, security, audit, government, live enforcement, or production use.
Governance Public Resources
Public templates for AI worker readiness and review.
Scaled Agents™ Public Resources provide public templates, planning worksheets, and governance-readiness resources for teams preparing AI worker ownership, evidence, human review, security readiness, and controlled launch conversations.
Readiness templatesPlanning worksheets for AI worker ownership, intended use, review scope, and launch conversations.
Evidence supportCustomer-safe prompts for documenting assumptions, reviewed sources, evidence gaps, and decision context.
Human reviewMaterials that keep approvals, escalation, and accountability with the right human roles.
Who We Are
Human-led, governance-first AI operations.
Scaled Agents™ helps teams prepare AI-supported work for governed operation by clarifying ownership, boundaries, review paths, evidence needs, and human accountability before AI workers move closer to operational use.
AI workers may assist, draft, route, recommend, validate, and execute permitted work inside reviewed boundaries. Humans remain accountable for business, legal, security, compliance, customer, and operational decisions.
Connect with Scaled Agents on LinkedIn
Follow Scaled Agents for public updates, readiness guidance, AI worker governance ideas, and ways to interact with the Scaled Agents community.
Connect on LinkedIn
What this means in practice
Scaled Agents keeps the operating model anchored in human accountability, governed boundaries, and reviewable evidence before AI-supported work moves closer to execution.
- Human judgment stays accountable
- Governance boundaries come first
- Evidence supports operating trust
Forward-Deployed AI operating model
The deeper operating-model explanation lives on its own page, where the comparison, delivery flow, and governance boundaries have room to breathe.
Scaled Agents™ Advisor
Explore governed AI service readiness.
Use the Scaled Agents™ Advisor to explore AI worker governance, readiness questions, service planning, and practical next steps before a formal review.
Forward-Deployed AI
Explore human-led AI delivery patterns.
Use Scaled Agents™ Forward-Deployed AI to explore how business problems, workflow discovery, controls, reusable templates, and approval paths can move governed AI services from concept to controlled execution.
From Policy to Action
AI governance becomes real when policy reaches the point of action.
Start with a controlled readiness conversation about the AI Workers your enterprise builds, buys, or deploys. Clarify ownership, authority, review boundaries, and evidence needs before implementation or consequential use.
Request
Share authorized, high-level planning context about the AI worker, business workflow, governance concern, or service-readiness need.
Scope
Clarify owners, intended use, data sensitivity, approval needs, lifecycle state, and whether the work belongs in platform readiness, service planning, or both.
Review
Identify the evidence, human review points, access boundaries, training needs, and professional-review dependencies before consequential use.
Plan
Prepare a practical next-step path for governance readiness, Passport planning, Toll Gate concepts, training, or AI-powered service support.
Form 1: Consultation Request
Start with a short consultation request.
Scaled Agents™ uses a two-step consultation process: submit a quick request first, then Scaled Agents reviews the request and follows up on the right consultation path.
Step 1: Share high-level, authorized contact details and a short description of what you want to discuss.
Step 2: After Form 1 is received, the page provides the next intake link so you can share additional planning context before the consultation.
Please share only authorized, high-level planning information. Do not include passwords, credentials, API keys, production secrets, regulated data, or confidential third-party material.