Platform / Security

Security controls for governed industrial AI.

TwinEdge is designed around tenant-scoped access, customer-owned secrets, read-only AI recommendations by default, approval gates before operational action, audit trails, replayable evidence, and deployment boundaries for cloud, edge, hybrid, and no-cloud environments.

Governance control planeRecommendations carry scope, policy state, approval, diff, audit, and replay before operational handoff.BOUNDED EVIDENCEPOLICY GATESAPPROVED OUTPUTSSource contexttags, docs, graphTenant scoperoles and boundsEvidence packtraceable inputsno physical writeback by defaultRedactcredentialsDry-runno writebackEval gatepolicy checksApprovalhuman reviewRecommendationexplainableEAM handoffapproved workAudit replaydiff and traceEVIDENCE AND ACCOUNTABILITY TRAILWhoidentity and roleWhat changeddiff before actionWhy allowedpolicy resultHow replayedsource evidenceBusiness outcomesTrust comes from bounded context, explicit policy gates, human approval, and replayable evidence.Read-onlyfirstSecretsredactedApprovalgatesReplayalways

Identity and roles

Tenant isolation

Data protection

AI action gates

Audit trails

Deployment options

Security review starts with the controls buyers need to evaluate: identity, tenant isolation, data handling, AI action governance, auditability, and deployment boundaries.

Platform in action

Security control model for enterprise review

The control model shows how source context, tenant scope, redaction, evaluation, approval, controlled handoff, audit, and replay govern recommendations before operational execution.

Security proof

Security controls sit inside the operating layer, not beside it.

TwinEdge connects identity, tenant scope, connector boundaries, secrets handling, AI action governance, audit trails, support access, and deployment model review across edge, cloud, hybrid, and no-cloud environments.

Tenant

Scoped access

Operational context is constrained by tenant, role, and deployment boundary.

Secrets

Controlled handling

Connector credentials and source details follow approved customer patterns.

Audit

Reviewable trail

API/MCP calls, approvals, policy checks, and evidence remain visible.

TwinEdge security control boardTwinEdge connects identity, tenant scope, connector boundaries, secrets handling, AI action governance, audit trails, support access, and deployment model review across edge, cloud, hybrid, and no-cloud environments.TwinEdge security control boardControls insideINPUTSUsersIdentity and rolesSourcesConnector boundariesDataTenant contextActionsApproval gatesLogsAudit and replayIdentity, connectors, tenant data, secrets, support paths, and deployment boundariesPRODUCT LAYERIdentityRolesTenantsScopeSecretsProtectAI GatesApproveDeployEdge/cloudAuditReviewOne boundary, every layerOUTCOME DASHBOARDSecurity review readinessProduction access is scoped, approved, logged, and reviewableScope, secrets, approval gates, and audit travel with the data across edge, cloud, hybrid, and no-cloud deployments.

Workflow

Security review path

Enterprise teams can start with the control posture, then review customer-specific evidence through a controlled security process.

Start with control posture

Review the identity and role model, tenant boundaries, deployment options, data protection, AI-action governance, audit trails, and replay approach.

Validate deeper evidence

Approved stakeholders can review questionnaires, architecture diagrams, deployment assumptions, network and connector patterns, secrets-handling evidence, audit examples, and implementation constraints.

Lock production governance

Before go-live, agree on identity integration, tenant scope, connector access, approval paths, logging, retention, support access, and operational handoff.

Capabilities

Security controls at a glance

These are the areas an enterprise security team should be able to triage before requesting customer-specific evidence.

Identity, roles, and least privilege

Map identity sources, tenant membership, roles, permissions, field access, approval scope, and administrator responsibilities before production use.

Tenant isolation

Operational context, graph objects, recommendations, API/MCP access, audit records, and evidence are constrained by tenant, organization, role, and deployment boundary.

Secrets and connector access

Connector credentials, private endpoints, and customer source details are owned through approved customer patterns, redacted where appropriate, and kept out of public material.

Data protection and redaction

Sensitive fields, source details, support bundles, and evidence packages can be masked, scoped, or redacted based on role, deployment, and review requirements.

Read-only first AI governance

Recommendations are staged and explainable by default. Operational execution requires validation, permission checks, human approval, and a recorded change path.

Audit, replay, and accountability

Plans, diffs, approvals, API/MCP calls, policy results, source context, and execution evidence remain reviewable so teams can reconstruct what happened.

Engineering controls

Built around bounded access and accountable action.

TwinEdge security posture focuses on least privilege, customer-controlled data boundaries, explicit approval before operational changes, and evidence that can be reviewed after the fact.

Least-privilege access

Tenant, organization, role, field, and workflow permissions constrain who can view context, request actions, approve changes, and use customer data.

Customer-owned secrets

Connector credentials, endpoint details, and support materials follow approved customer patterns and are redacted from public content.

Read-only first AI

AI recommendations explain, stage, validate, and request approval before they become operational execution or external publication.

Traceable evidence

Actions carry source context, policy results, approvers, diffs, timestamps, and replay paths so teams can review what happened and why.

Outcomes

Security review outcomes

Security review gives buyers enough structure to evaluate risk, choose the review path, and request the evidence they need for production approval.

Security teams

Know which controls to validate, which artifacts to request, and where customer-specific evidence will be reviewed.

IT and OT teams

Confirm deployment model, connectivity assumptions, source access, support boundaries, and integration responsibilities.

Operations leaders

Understand why AI recommendations cannot silently write to operations and how approvals protect field execution.

Procurement and risk teams

Route questionnaires, evidence requests, compliance reviews, and production readiness decisions to the right customer review path.

Connected platform

Customer-only implementation materials

Deeper security evidence belongs in a controlled customer review, not as open internet content.

Security questionnaires, control summaries, compliance evidence, and policy exceptions are handled with approved customer stakeholders.

Deployment diagrams, connector paths, private endpoints, firewall assumptions, and support-access controls are reviewed against the customer environment.

Secrets handling, key ownership, rotation expectations, and redaction behavior are reviewed without publishing secret values or customer-specific source details.

Tenant API/MCP catalogs, customer data tools, test runs, audit feeds, and API keys remain authenticated, permissioned, rate-limited, and role-scoped.

Runbooks, support bundles, source maps, implementation notes, and evidence packs are delivered through customer-controlled access paths.

Production readiness locks identity, permissions, approval gates, logging, retention, support escalation, and operational handoff before go-live.

Evaluate TwinEdge

Review TwinEdge security controls with your team.

Use customer-controlled review paths for questionnaires, evidence, operating diagrams, connector details, support-access controls, audit examples, and production readiness decisions.