Trust: Engineering Reliability and Compliance
Build What Enterprises Depend On
Trust is not optional in enterprise deployment. ITT ARIV applies artificial intelligence with reliability, transparency, and full control, ensuring every decision and data flow remains observable, auditable, and governed within enterprise environments.
Security Overview
Zero Custody Architecture: As part of our AI as a Service approach, we bring the intelligence to the data and never take custody of proprietary information.
Clean Room Execution: Tool execution happens in ephemeral containers; if something looks off, the container is terminated to prevent lateral movement.
Sanitization Layer: All inputs and outputs pass through a layer where named entity recognition models scan for PII and PHI.

Privacy and Compliance
Stateless Inference
Inference by Design
Automated Evidence
GDPR Ready

Responsible AI
Deterministic Guardrails: We wrap probabilistic intelligence in deterministic controls to reduce hallucination impact and prevent unsafe execution.
Action Authority: Agents operate within defined authority boundaries; no agent can exceed its scope without explicit human approval.
Traceable Logic: Every extraction, classification, or recommendation generated through artificial intelligence is traceable back to source sections for audit and compliance, supported by ITT ARIV’s AI consulting services for enterprise governance and deployment.
Data Residency
Client Controlled Keys
We log metadata for observability, but payloads are encrypted with client-controlled keys.
Isolation
The platform can run fully isolated with on-prem LLMs, enabling custom AI solutions while ensuring there is no requirement to send documents outside the customer boundary.
Deployment Assurance
The Lab Foundation: Before a solution reaches you, it has been stress-tested and hardened in our internal Lab to ensure it survives worst-case scenarios.
Shift Left Evaluation: DeepEval runs LLM unit tests before release to ensure accuracy and safety, enabling reliable AI for business deployments from day one.
Continuous Monitoring: Daily regression tests ensure that upstream model changes do not quietly degrade system behavior.

Frequently Asked Questions
Is my data used to train other models?
No. We follow a zero-custody architecture where models come to the data and no external training occurs on customer information.
How do you prevent hallucinations?
Every answer generated by the artificial intelligence AI system is tied to verified source references, and when supporting evidence is unavailable, the agent is designed to return “not found” instead of producing an unsubstantiated response.
What happens when the AI fails?
Reliability comes from observability; we track every reasoning path and tool call, so failures are diagnosable and fixable.