Arbitex Gateway vs. Nightfall AI
Nightfall AI is a cloud-native SaaS DLP platform that detects sensitive data in collaboration tools — Slack, Google Drive, GitHub, Jira — scanning content after it has been committed to those systems. Arbitex Gateway is a compliance-first AI governance platform that enforces policy on every AI model request in real time, before data reaches any model. These are different attack surfaces. Enterprises with mature AI programs need coverage at both. Having Nightfall does not mean your AI model boundary is governed.
Feature Comparison
| Capability | Nightfall AI | Arbitex Gateway |
|---|---|---|
| DLP: AI request path — real-time pre-model enforcement | ✕ Not in scope — Nightfall is not in the AI model request path; scans content after it has been committed to SaaS apps | ✓ Core product purpose — every AI request inspected and governed before reaching any model endpoint |
| DLP: SaaS collaboration apps (Slack, Drive, GitHub) | ✓ Yes — real-time scanning of content in Slack, Google Drive, GitHub, Jira, and Confluence | ✕ Different surface — Arbitex governs the AI model boundary, not the collaboration layer |
| Hybrid deployment — data plane in customer VPC | ✕ SaaS-only — all data routes through Nightfall's cloud; no customer-managed data plane | ✓ Hybrid Outpost — data plane runs inside customer VPC; sensitive data governed within the perimeter |
| Response-side inspection (AI output DLP) | ✕ Not in scope — Nightfall scans existing SaaS content; not positioned for AI response inspection | ✓ Bidirectional — every AI response inspected and governed through the same DLP pipeline |
| Full policy engine — combining algorithms, routing decisions | ✕ Detection policies for SaaS scanning — no combining algorithms, no AI routing, no per-org budget enforcement | ✓ Policy chain engine with combining algorithms (first_applicable, deny_overrides), route decisions, budget caps across 9+ providers |
| Pre-built compliance bundles (12 frameworks) | ✕ No pre-configured compliance bundles for AI governance — no HIPAA, GLBA, or SOX policy enforcement at the AI layer | ✓ 12 compliance frameworks (PCI-DSS, HIPAA, GDPR, GLBA, SOX, CCPA, BSA/AML, SEC Reg FD, FERPA, EU AI Act, NIST AI RMF, ISO/IEC 42001) enforced at the model boundary |
| Tamper-proof audit log | ✕ Not available — audit logs for SaaS scanning activity; no cryptographic chain for AI governance | ✓ Cryptographically chained, immutable audit record of every AI request, enforcement action, and compliance decision |
| SIEM connectors (native) | ✕ Webhook-based alerting; limited native SIEM connectors | ✓ 7 native SIEM connectors — Splunk, Sentinel, QRadar, Cortex XSIAM, Elastic, Datadog, Sumo Logic |
| DLP accuracy transparency — published accuracy metrics | ✕ Detection accuracy not published with per-entity accuracy metrics; customers cannot independently verify performance | ✓ Three-tier detection — pattern rules, ML entity recognition, and contextual validation — with per-entity evaluation against a labeled corpus |
| CredInt — compromised credential detection | ✕ Not available | ✓ Sub-millisecond in-process lookup — no external dependency, no raw credential storage |
| Budget enforcement (dollar-cap + request-cap) | ✕ Not available | ✓ Per-org budget caps and request quotas — block / warn / log_only enforcement actions |
Where Arbitex Gateway Wins
Different attack surfaces — Nightfall and Arbitex are additive
Nightfall covers what employees put into Slack and Google Drive. Arbitex governs what goes to AI models. These are adjacent but distinct enforcement points. Most enterprises that deploy Arbitex already have a collaboration DLP tool — Arbitex is the governance layer at the AI model boundary that existing DLP infrastructure was not designed to cover. When an employee submits PHI in an AI prompt, bypassing Slack and Drive entirely, Nightfall is not in that path.
Full policy engine — not just detection, but routing and enforcement
Nightfall's policy model is built for SaaS scanning: define detection rules, apply them to integrations, receive alerts or remediation. Arbitex's policy chain engine operates on a different surface — making real-time routing decisions across 9+ AI providers, applying combining algorithms to resolve conflicting rules, enforcing per-org budget caps, and governing every prompt and response through a bidirectional enforcement pipeline. DLP is one component; the full governance surface is wider.
Hybrid Outpost — regulated data governed inside your perimeter
Nightfall is SaaS-only. Every request routes through Nightfall's cloud infrastructure. Organizations whose data classification policies restrict regulated data from transiting third-party cloud without controls — HIPAA-covered PHI, GLBA NPI, ITAR-controlled technical data — have no viable deployment path with Nightfall for AI governance. Arbitex Hybrid Outpost runs the data plane inside the customer's own VPC. PHI is inspected and governed within the customer environment before routing to any AI provider.
Compliance bundles that execute at the model boundary
Nightfall has no pre-built compliance bundles for AI governance — no HIPAA minimum necessary enforcement, no GLBA NPI inspection at the AI layer, no SOX data controls applied to AI requests. Arbitex ships 12 compliance frameworks as executable policy bundles. Activate a framework and the correct detectors, enforcement actions, and audit controls are applied automatically against every AI request. Compliance coverage for the collaboration layer and coverage for the AI model boundary are both necessary in a regulated environment.
Govern the AI model boundary
Arbitex Gateway handles the attack surface Nightfall was not designed for — real-time AI request governance, 12 compliance frameworks, hybrid deployment, and tamper-proof audit records.