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Arc / Assurance

Trust is not a policy document. It is an operating system.

Assurance at Arc Intelligence means actively testing the controls that constrain your AI workforce, before production, and continuously afterwards.

System / AI-Assurance Mode / Continuous Scope / Runtime + Boundary
01 Assurance Disciplines

Six disciplines. One continuous cycle.

Each discipline produces evidence. Evidence is what turns an AI deployment from an act of faith into an operational position you can defend.

01 / ADVERSARIAL TESTING

Adversarial Testing

Simulated indirect prompt injection and boundary attacks against the controls that govern your agents.

  • Injection payloads embedded in documents
  • Tool and permission escalation attempts
  • Boundary evasion scenarios
  • Findings and remediation guidance
02 / DATA PROTECTION

Data Protection

PHI / PII inspection and sanitization before external model transmission where applicable.

  • Sensitive-field detection
  • Redaction and tokenization
  • Transmission boundary rules
  • Retention and handling controls
03 / IDENTITY & ACCESS

Identity & Access

Unique agent identities and role-based permissions, issued and revoked under operational control.

  • Per-agent credentials
  • Role-based scoping
  • Least-privilege review
  • Revocation paths
04 / CONTINUOUS MONITORING

Continuous Monitoring

Live telemetry and operational event logging across the agent environment.

  • Runtime event streams
  • Anomaly and variance detection
  • Exception queue visibility
  • Operational reporting
05 / COMPLIANCE EVIDENCE

Compliance Evidence

Structured records supporting internal governance and regulatory review.

  • Cryptographic logging of controlled actions
  • Decision and escalation records
  • Boundary configuration history
  • Evidence packages for internal review
06 / BOUNDARY ENFORCEMENT

Boundary Enforcement

Machine-enforced controls around sensitive actions and data, applied at execution time.

  • Action-level policy gates
  • Approval requirements
  • Isolation triggers
  • Escalation routing
02 Assurance Cycle

Tested before production. Tested during it.

A control that was validated once, at deployment, is a historical claim. Assurance is only meaningful while the environment is still changing.

01 / MAP

Map

Agent inventory, data pathways, tool access and existing controls.

02 / MODEL

Model

Threat scenarios specific to your workflows and regulatory environment.

03 / TEST

Test

Adversarial execution against boundaries, identity, and inspection.

04 / ENFORCE

Enforce

Findings converted into machine-enforced runtime policy.

05 / EVIDENCE

Evidence

Structured records retained for governance and review.

INDIRECT PROMPT INJECTION / TEST PATH Illustrative
Hostile DocumentEXTERNAL CONTENT InspectionPAYLOAD ANALYSIS Injection FlaggedPOLICY VARIANCE Token IsolatedCONTAINMENT Human ReviewAOC ANALYST SYSTEM / AI-ASSURANCE  ·  MODE / CONTINUOUS  ·  HUMAN ESCALATION / ENABLED
03 Stated Boundaries

What assurance is, and what it is not.

Precision about limits is part of the service. A vendor that claims to eliminate AI risk is describing a product that does not exist.

What we provide

Contracted
  • Infrastructure and secure integration
  • Machine-enforced boundaries around agent actions
  • Adversarial testing of those boundaries
  • Data inspection and sanitization controls
  • Continuous telemetry and monitoring
  • Human exception handling and escalation
  • Structured records supporting governance review

What we do not claim

EXPLICIT
  • Guaranteed AI correctness
  • Guaranteed regulatory compliance
  • Guaranteed prevention of every attack
  • Responsibility for third-party model behaviour
  • Guaranteed downstream business outcomes

Arc Intelligence holds no security certifications at this time and displays none. Certification status will be published when it exists, not before.

Service Positioning

Arc Intelligence provides infrastructure, monitoring, assurance, containment, and managed operational services around enterprise AI systems. Responsibility for business decisions, underlying models, and organizational policies remains with the client unless expressly defined otherwise in contractual agreements.

Next Step

Find out which boundaries your AI workforce is currently missing.