Enterprise AI Security: Complete Architecture Overview

Enterprise AI adoption is accelerating faster than the security controls meant to govern it. Most organizations now run AI tools across dozens of teams, pulling from multiple model providers — often without a clear picture of which data is moving through which system. The risk is not theoretical. Every unguarded prompt is a potential data exposure. Every unreviewed response is an uncontrolled output from a system your organization is accountable for.

The solution is not a policy document. It is not a single tool that filters bad words or blocks a handful of known-sensitive patterns. What enterprises need is an architecture — one that enforces governance at every layer, on every AI interaction, in real time. Arbitex Gateway was designed as exactly that: a complete, layered security architecture that sits between your organization and every AI model your teams use.

The Six Layers of Enterprise AI Governance

Arbitex is not a point solution. It is a stack — six distinct layers, each handling a specific governance concern. Security leaders often ask: “What does your product do?” The honest answer is that it does all of this, together, in sequence, for every request. That is the architecture. Understanding each layer makes clear why any one of them, alone, is not enough.

1. Routing — Control Where AI Traffic Goes

Before a single token reaches a model, Arbitex decides where it goes. The Gateway supports 9+ model providers plus bring-your-own-endpoint (BYOE), giving teams access to the right model for the right task. Three routing modes — single, compare, and summarize — let organizations match workflows to model capabilities.

But routing is not about load balancing. It is a governance decision. Security and operations teams define which groups can access which providers, under what conditions. A regulated team may be restricted to approved, on-premises models. A product team may be permitted to use external frontier models with inspection enforced. Policy governs every routing choice.

Automatic failover with health monitoring means that availability is maintained without operator intervention — but always within the boundaries policy allows.

2. Protection — Inspect Every Prompt and Response

Once routing is decided, every interaction passes through the protection layer. Arbitex uses a 3-tier DLP pipeline that combines pattern matching, entity recognition, and contextual validation to detect sensitive content before it reaches a model — and again when the model responds.

The pipeline covers 80+ detection categories spanning PII, financial data, medical records, credentials, and infrastructure identifiers. The scope matters: most data loss prevention tools were built for email or file storage. The Arbitex pipeline is purpose-built for conversational AI, where sensitive content appears in fragments, in context, and in ways that simple pattern rules miss.

Response inspection is just as important as prompt inspection. A model that returns a reconstructed SSN or a verbatim excerpt from a confidential document is a data breach — regardless of what went in. The protection layer inspects both directions.

For each detected item, the configured action applies: allow, redact, or block. These are configurable at the policy level, so enforcement matches the sensitivity of the data and the risk tolerance of the team.

3. Policy — Enforce the Rules That Matter

The policy layer is where governance intent becomes enforcement reality. Arbitex’s policy engine uses firewall-style rules — ordered, explicit, auditable — to define what is permitted, what is blocked, and what conditions apply.

For organizations operating in regulated industries, Arbitex ships compliance bundles for 8+ regulatory frameworks including HIPAA, PCI-DSS, SOX, GDPR, and others. These are not checklists. They are policy packs that activate an entire compliance profile with a single configuration switch — enabling the right detection rules, response actions, audit requirements, and reporting outputs for that framework.

Beyond compliance, the policy layer handles content filtering, budget caps, and usage quotas. This is where organizations set the boundaries that apply to every AI interaction: what is allowed to be discussed, how much compute a team or user can consume, and what happens when limits are approached or exceeded.

4. Identity — Know Who Is Using AI

A governance architecture without verified identity is not governance — it is a suggestion. Arbitex integrates with enterprise identity infrastructure through SAML 2.0, SCIM 2.0, and WebAuthn/FIDO2, tying every AI interaction to a known, authenticated user.

OAuth 2.0 machine-to-machine (M2M) flows extend this to automated systems: CI/CD pipelines, service accounts, and AI agents all authenticate through the same identity layer, with the same policy enforcement applied. There is no anonymous traffic. There is no pathway that bypasses identity verification.

Role-based access control with group-level policy assignment means that governance rules follow the person, not the application. A user’s clearance, team membership, and access tier travel with them through every AI interaction — regardless of which tool they are using.

5. Audit — Prove What Happened

Regulated organizations are increasingly asked not just to have AI policies, but to demonstrate that those policies were enforced on specific transactions, for specific users, at specific times. Arbitex’s audit layer is built for exactly this requirement.

Every request generates a tamper-evident audit record, HMAC-chained to the preceding record to make retrospective alteration detectable. Records are formatted in OCSF (Open Cybersecurity Schema Framework) for direct integration with SIEM platforms including Splunk, Microsoft Sentinel, and Elastic.

Compliance evidence packs are auto-generated per framework, giving audit and legal teams the structured documentation they need without manual extraction. The complete decision chain — routing choice, DLP findings, policy evaluation, identity context, and final outcome — is recorded for every request. When a regulator or internal auditor asks what happened, the answer is available.

6. Deployment — Run Where Your Data Lives

For many enterprises, the gateway architecture described above must operate within their own infrastructure, not a third-party SaaS environment. Arbitex supports this through a hybrid Outpost model: the data plane runs in the customer’s VPC, processing all traffic locally, while the control plane is managed by Arbitex.

This means prompts, responses, and sensitive content never leave the customer’s perimeter in Outpost mode. For classified or highly regulated environments, Arbitex supports air-gap deployment — no external connectivity required for data plane operation.

All communication between components uses mutual TLS (mTLS). The architecture is designed so that a network interception between components yields nothing usable. Data residency requirements, sovereignty constraints, and internal security policies are met by deployment model, not by contractual promise.

Why Architecture Matters

Point solutions are abundant. There are tools that filter prompts, tools that log requests, tools that manage model access. Each addresses one layer of the governance problem. None of them address all six simultaneously.

The value of an architecture is in the sequence. When a request arrives at Arbitex Gateway, it passes through identity verification, then routing policy, then DLP inspection, then policy evaluation, then audit recording — before it ever reaches a model. Every layer runs for every request. There are no gaps between tools, no seams where a sensitive interaction can slip through unexamined.

That sequence is the difference between saying “we have an AI policy” and being able to demonstrate “we enforced our AI policy on every AI interaction across every team, and here is the audit trail to prove it.” For organizations accountable to regulators, boards, or customers for how they use AI, that distinction is not a product feature. It is an operational necessity.

Related

• Platform Overview — Full Arbitex Gateway capabilities
• DLP Protection — How the 3-tier DLP pipeline works
• Identity & Access — Enterprise SSO and identity controls
• Compliance Frameworks — Pre-built regulatory bundles
• Zero Trust for AI — Why your gateway controls everything