Arbitex Gateway vs. WitnessAI
WitnessAI is a well-regarded AI security platform — intent-based ML policy, agentic security controls, automated adversarial testing, and network-level AI visibility. These are genuine capabilities for security teams governing AI behavior. The threat model Arbitex addresses is different: once AI requests contain regulated data — PHI, PII, MNPI, CUI — who governs what data crosses the model boundary, what compliance rule applied, and what the audit record proves to a regulator? WitnessAI governs AI behavior. Arbitex governs data content. Regulated enterprises deploying both cover the full governance stack.
Feature Comparison
| Capability | WitnessAI | Arbitex Gateway |
|---|---|---|
| Primary governance model | ✓ Behavioral governance — intent-based ML policy classifies AI requests by inferred intent; AI Firewall enforcement; agentic security for autonomous agents | ✓ Data governance — 3-tier DLP pipeline detects regulated data entities in AI prompts; deterministic compliance policy engine; tamper-proof audit trail |
| Published DLP accuracy metrics | ✕ WitnessAI makes accuracy assertions without stating the validation dataset or measurement date behind them | ✓ Three-tier detection — pattern rules, ML entity recognition, and contextual validation — with per-entity evaluation against a labeled corpus |
| Deterministic compliance policy engine | ~ Intent-based ML policy — probabilistic intent classification; policy enforcement based on inferred behavioral intent rather than deterministic data governance rules | ✓ Deterministic policy chains with flexible combining logic for multi-condition policies, 12 compliance framework bundles (PCI-DSS, HIPAA, GDPR, GLBA, SOX, CCPA, BSA/AML, SEC Reg FD, FERPA, EU AI Act, NIST AI RMF, ISO/IEC 42001) |
| Compliance framework bundles — HIPAA, PCI-DSS, GDPR, GLBA | ~ Query WitnessAI's compliance posture — intent-based ML governance does not produce the same evidence as deterministic data governance policy enforcement against specific compliance frameworks | ✓ 12 pre-built compliance framework bundles at the model boundary — PCI-DSS, HIPAA, GDPR, GLBA, SOX, CCPA, BSA/AML, SEC Reg FD, FERPA, EU AI Act, NIST AI RMF, ISO/IEC 42001 — inline enforcement, no post-processing |
| tamper-proof audit trail for compliance evidence | ~ AI security event logging — query whether WitnessAI produces tamper-evident, tamper-proof governance records of deterministic compliance decisions for regulatory examination | ✓ Cryptographic tamper-proof audit trail on every AI interaction record — model provider, DLP tier result, compliance rule matched, enforcement action — structured for HIPAA BAA, SOC 2, and GDPR DPA examination |
| Hybrid Outpost / air-gap deployment | ~ AI Firewall deployment — query WitnessAI on whether AI traffic inspection occurs inside or outside customer-controlled infrastructure for data-residency requirements | ✓ Hybrid Outpost deploys complete data governance plane inside customer VPC — DLP inspection, policy enforcement, and audit logging within authorized perimeter; AI traffic never transits Arbitex infrastructure |
| Multi-model routing — provider coverage | ✓ AI gateway with multi-provider routing support — query provider coverage for your specific model requirements | ✓ 9+ AI providers with access to 1,000s of models (Azure AI alone exposes 1,000+ models) — single governance policy across the entire provider portfolio |
| Credential breach detection — compromised dataset | ✕ Not in scope — WitnessAI's detection surface is behavioral intent and adversarial patterns, not real-time checking against compromised credential databases | ✓ Every AI interaction checked against a compromised credential dataset in real time — detects leaked API keys, stolen tokens, and compromised credential dataset matches at the model boundary |
| SIEM integration — native connectors | ~ Query WitnessAI's SIEM integration capabilities — verify connector count, native API format support, and whether log format translation middleware is required | ✓ 7 native SIEM connectors: Splunk HEC, Microsoft Sentinel DCR, Elastic Bulk API, Datadog Logs API, Sumo Logic HTTP Source, Chronicle UDM, IBM QRadar Syslog — no log aggregation middleware |
| Agentic AI security — agent authorization controls | ✓ Core capability — agentic security layer governing what autonomous AI agents can do, what tools they can call, what resources they can access; leading-edge investment in this area | ✕ Not in current product scope — Arbitex governs data flowing through AI; agentic authorization controls are WitnessAI's domain; deploy both for full-stack coverage |
| Automated red-teaming | ✓ Continuous adversarial testing — automated red-teaming of AI systems as a core product capability; attacks AI defenses proactively | ✕ Different product category — Arbitex enforces data governance policy at runtime; adversarial AI testing is WitnessAI's domain |
| Network-level AI application discovery | ✓ Network-level native app visibility — surfaces AI usage across the organization without requiring application-layer integration; useful for shadow AI discovery | ✕ Application-layer gateway — requires integration at the AI request path; not a network-level discovery tool |
| Encryption enforcement at startup | ✕ No published documentation on startup-level encryption enforcement — WitnessAI focuses on behavioral governance and intent-based policy; transport encryption posture of the platform is not publicly documented | ✓ Startup validators reject plaintext connections in production — Redis, telemetry, model provider URLs validated at process start; mTLS with CA pinning for Outpost traffic; gateway refuses to start if encryption is misconfigured |
Where Arbitex Gateway Wins
We publish. They assert.
WitnessAI makes accuracy assertions without stating what they were measured against. Arbitex evaluates detection quality per entity type against a labeled corpus rather than reporting a single blended score. Arbitex does not currently publish per-entity accuracy figures either — the evaluation corpus is not yet large enough for those numbers to be meaningful. The honest question for any AI governance vendor, including this one, is not "what is your accuracy number" but "what was it measured on, and when" — and buyers should expect a corpus size and a date with any figure they are shown.
Deterministic compliance — not probabilistic intent
WitnessAI's intent-based ML policy classifies AI requests by inferred behavioral intent. Arbitex's policy engine is deterministic — 12 compliance framework bundles apply explicit rules that evaluate against detected entity types, user attributes, org context, and combining algorithms. For regulated environments where auditors ask "what policy applied, what triggered it, what was the decision" — deterministic is the required architecture. An tamper-proof audit record of a deterministic policy decision is compliance evidence. An ML intent classification is not.
Data inside your perimeter
Arbitex's Hybrid Outpost deploys the complete data governance plane inside your own infrastructure. DLP inspection, policy enforcement, and audit logging happen within your authorized boundary — AI traffic never transits Arbitex-controlled systems. For organizations with ITAR, air-gap, or customer-controlled infrastructure mandates, deployment model determines whether inspection is inside or outside the controlled perimeter. Query any AI governance vendor on where AI traffic inspection occurs.
9+ Providers, 1,000s of Models — one governance policy
Arbitex's routing layer covers 9+ AI providers — Azure AI, OpenAI, Anthropic, Google, Cohere, Mistral, and more. Azure AI alone exposes over 1,000 models. One governance policy covers the entire provider portfolio: same DLP pipeline, same compliance framework enforcement, same audit trail regardless of which model handles the request. As your AI portfolio grows across providers and models, the governance layer scales without reconfiguration.
Credential breach detection at the AI request layer
WitnessAI's detection surface is behavioral intent — what AI users are trying to do. Arbitex checks a different signal: every AI interaction is checked in real time against a compromised credential dataset — leaked API keys, stolen tokens, and compromised credential matches that appear in AI prompts. For organizations with supply chain exposure or insider threat concerns, credential detection at the model boundary is a distinct control outside behavioral intent classification.
SIEM-native without middleware
Arbitex provides 7 native SIEM connectors — Splunk HEC, Microsoft Sentinel DCR, Elastic Bulk API, Datadog Logs API, Sumo Logic HTTP Source, Chronicle Unified Data Model, IBM QRadar Syslog — all delivering tamper-proof audit records in vendor-native API formats. No Syslog relay, no log format translation, no SIEM agent required. Governance events land directly in your SIEM in the format your security operations team already queries.
Complementary — Not Competing
WitnessAI and Arbitex address different threat models in enterprise AI governance. WitnessAI governs AI behavior: intent-based policy prevents misuse, agentic security controls what autonomous agents are authorized to do, and automated red-teaming continuously tests AI defenses. Arbitex governs data content: the multi-layer content inspection pipeline detects regulated entities in legitimate AI prompts, deterministic compliance policy maps detections to enforcement decisions, and tamper-proof audit records prove governance to regulators.
An enterprise deploying autonomous AI agents may need both: WitnessAI's agentic controls to govern what agents are authorized to do, and Arbitex's data governance to ensure that what agents send to models and receive from models is inspected, governed, and logged for compliance. The complete AI governance posture covers both behavioral governance and data governance.
Related Resources
See Arbitex Gateway in action
Published accuracy metrics. Deterministic compliance policy. 12 framework bundles. Hybrid Outpost air-gap deployment. Credential breach detection. 7 native SIEM connectors. WitnessAI governs AI behavior — Arbitex governs the data.