Digital Trust Platforms • DT-06

AAIOS — Agentic AI Operating System

The controlled runtime that agentic automation executes on.

Scope

What the engagement covers.

Agents that can act on real systems need an operating layer that decides what they may call, remember, spend and do without asking. AAIOS provides that layer, and the audit ledger that makes agent behaviour reviewable after the fact. It is the runtime underneath every GaaS engagement.

Included capabilities

Agent runtime with sandboxed execution, resource limits and circuit breakers
Tool broker enforcing least-privilege, scoped access to every connected system
Governed memory with scope, retention, redaction and cross-session boundaries
Policy engine defining action classes, approval gates and prohibited operations
Immutable audit ledger of prompts, retrievals, tool calls, decisions and approvals
Model routing and cost governance with per-workflow budgets and rate limits
Evaluation harness for regression testing on every model or prompt change

Outputs and deliverables

AAIOS tenant deployment and configuration
Tool registry with permission and rate-limit model
Policy set covering action classes and approvals
Audit ledger with replay and export capability

Workflow

How it is delivered, step by step.

Each step has an owner, an entry condition and an artefact that has to exist before the next step begins.

01ProvisionTenant, identity integration, environments and network boundaries.

02RegisterTools and data sources with scoped credentials and rate limits.

03PolicyAction classes, approval requirements and prohibited operations.

04RunExecution with logging, cost accounting and automatic circuit breaking.

05AuditReplayable ledger for review, dispute resolution and inspection.

Use cases

Where this is typically applied.

Use case 01

Enterprises consolidating scattered agent pilots onto one runtime

Use case 02

Regulated environments requiring provable human oversight of automation

Use case 03

Organizations granting agents authority over production systems

Delivery model

The operating pattern for Digital Trust Platforms.

The same delivery discipline applies across every capability in this line, so combined engagements stay coherent.

Model

Organization, taxonomy, control library and evidence structure.

Connect

Identity, data sources, telemetry and downstream systems.

Configure

Workflows, policies, thresholds, approvals and reporting packs.

Adopt

Role-based onboarding, migration of existing registers and evidence.

Operate

Run the platform, or hand over to the client team with support.

Integration

SSO, SAML and SCIM for identity, roles and provisioning.
SIEM, ticketing and data platforms for events, issues and reporting.
HSM, PKI and certificate management for the cryptographic modules.
Device management and OT asset systems for the device operating system.

Engagement approach

Modules can be licensed individually, but the value compounds when they share a taxonomy: an AI usage event, a privacy finding and a cryptographic gap all become risk records in the same register with the same evidence and reporting model.

Other capabilities in Digital Trust Platforms.

View the full Digital Trust Platforms line →

DT-01