Operating AI™ / Governance

Enterprise-grade controls. Built in from day one.

Every deployment ships with SOC 2 infrastructure, complete audit logging, and a governance framework designed to satisfy your legal, compliance, and risk teams.

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SOC 2 Type IIGDPRHIPAACCPAISO 27001 AlignedAES-256 EncryptionTLS 1.3Zero Data Training

Framework

Six pillars of AI governance

Security & Compliance

SOC 2 Type II certified infrastructure
End-to-end encryption (AES-256 at rest, TLS 1.3 in transit)
GDPR and CCPA compliance
HIPAA Business Associate Agreement available
ISO 27001 alignment
Annual third-party penetration testing

Access Control

Role-based access control (RBAC)
Attribute-based access policies
SSO integration (SAML 2.0, OIDC)
Multi-factor authentication enforcement
Privileged access management
Session management and timeout controls

Audit & Monitoring

Immutable audit log for every agent action
Real-time anomaly detection
User activity monitoring
Agent performance and drift monitoring
SLA tracking and alerting
Exportable compliance reports

AI Ethics & Responsibility

Human-in-the-loop for high-stakes decisions
AI output validation and confidence thresholds
Bias monitoring for automated decisions
Transparent model documentation
Escalation path for agent uncertainty
Regular model behavior reviews

Data Governance

Data residency controls by region
Zero data training on your data
Data classification and tagging
Retention policy enforcement
Data lineage tracking
Right-to-deletion support

Operational Oversight

Governance council template
AI change management process
Incident response playbooks
Agent rollback capabilities
Policy enforcement automation
Quarterly governance reviews

Core Principle

Your team stays in control

Every agent is configured with explicit human-in-the-loop gates — decision points where an agent pauses and escalates to a human when stakes are high, confidence is low, or policy requires review.

01Contract approvals above defined dollar thresholds
02Customer communications flagged for sensitivity
03Financial transactions exceeding approval limits
04Hiring decisions requiring manager sign-off
05Compliance exceptions requiring legal review

Agent executes task

The agent processes the workflow automatically within defined parameters.

Threshold check

Every action is evaluated against governance rules configured for your business.

Auto-approve or escalate

Low-risk, high-confidence actions proceed automatically. Others escalate.

Human review and decision

Your team receives a clear summary, context, and decision options.

Audit trail recorded

Every decision — automatic or human — is logged immutably for compliance.

Agent Monitoring

Know what every agent did, and why

An agent that runs unattended is only trustworthy if you can reconstruct its behavior after the fact. Every Operating AI™ deployment ships with monitoring across four dimensions — activity, quality, cost, and drift — surfaced in a single operations view.

Activity

What ran, when, on whose behalf, and against which system of record.

Run volume by agent and workflow
Actions taken vs. actions escalated
Systems touched per run
Immutable per-action audit entry

Quality

Whether the output held up — measured against human review, not self-report.

Human override rate
Confidence score distribution
Correction patterns by workflow
Downstream rework triggered

Cost

What the automation actually costs to run, per workflow and per outcome.

Inference and integration cost per run
Cost per completed workflow
Spend trend by department
Budget threshold alerting

Drift

Whether behavior is changing over time as data, models, or processes move.

Output distribution shift
Escalation rate trend
Source data freshness
Model version change log

When an agent misbehaves

Monitoring is only useful if it is wired to a response. Every agent has a defined failure path: confidence below threshold routes to a human, repeated failures on the same workflow suspend the agent automatically, and any agent can be rolled back to a previous configuration without redeploying the rest of the system. Incidents are recorded against the agent, not just the run, so patterns surface across weeks rather than being lost in a log.

Agent Training

Agents are trained, not installed

An agent inherits your business rules, your tone, your approval thresholds, and your escalation paths. That configuration is built with the team that owns the work — not handed to them. Training runs in both directions: the agent learns your process, and your team learns where the agent’s judgment ends and theirs begins.

Governance training is a standing part of every deployment. Reviewers are taught what a low-confidence escalation looks like, how to correct an agent without breaking its rules, and when to suspend rather than adjust.

Process capture

The team that owns the work walks through it end to end, including the exceptions they handle by instinct.

Rule and threshold config

Approval limits, tone, escalation triggers, and hard stops are set explicitly and signed off by the process owner.

Shadow run

The agent runs alongside the human process without taking action. Output is compared, not trusted.

Supervised operation

The agent acts, but every action is reviewed. Corrections feed back into its configuration.

Reviewer enablement

The people who will approve escalations are trained on what to check and how to correct safely.

Steady state and review

The agent operates within its thresholds, with a scheduled governance review of its behavior and scope.

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Enterprise security that meets your requirements.

Discuss your compliance needs with our governance team.

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