Arbitex Gateway vs. Helicone
Helicone is a developer observability platform for LLM usage — logging, cost tracking, prompt management, and caching built for engineering teams that want visibility into their AI stack. Arbitex Gateway is an enterprise AI governance platform that sits in front of every AI provider and enforces policy in real time. Observability tells you what happened. Governance determines what is allowed to happen.
Feature Comparison
| Capability | Helicone | Arbitex Gateway |
|---|---|---|
| Real-time DLP inspection (80+ patterns, ML-based entity recognition) | ✕ Passive logging — Helicone records what was sent to AI providers after the fact; no real-time inspection pipeline, no pattern detectors, no ML-based entity recognition at the model boundary | ✓ 80+ pattern detectors + ML-based entity recognition — dual-method DLP inspects every request and response before any data reaches a model; sensitive content flagged or blocked in real time |
| Pre-built compliance bundles (HIPAA, PCI-DSS, GDPR, SOX, GLBA) | ✕ No compliance bundles — Helicone is designed for engineering observability, not regulatory compliance; no pre-configured framework controls for any compliance requirement | ✓ 12 compliance frameworks enforced as executable policy at the model boundary — activate a framework and the correct detectors, enforcement actions, and audit controls apply automatically |
| Tamper-proof audit logging | ✕ Usage logs and request history — useful for debugging and cost attribution; not a cryptographically chained, tamper-evident record structured for regulatory examination | ✓ tamper-proof audit log — every request, every enforcement decision captured in a cryptographically verifiable, immutable record that survives compliance examination |
| Policy enforcement engine at the model boundary | ✕ No policy enforcement — Helicone observes and logs AI traffic; it does not evaluate requests against policy rules, enforce data handling requirements, or block non-compliant content | ✓ Policy engine enforces rules at the wire — route, block, redact, or flag based on content, user, provider, or compliance framework; enforcement happens before the request reaches the model |
| Hybrid deployment — data stays in your infrastructure | ✕ SaaS-only — AI request logs and prompt content route through Helicone's cloud; no customer-managed data plane or Hybrid Outpost for data sovereignty requirements | ✓ Hybrid Outpost — data plane runs inside your own VPC; AI traffic inspected and governed before it leaves your environment; only policy config and anonymized telemetry reach Arbitex systems |
| Compromised credential detection | ✕ No credential breach detection — AI prompt content is logged but not inspected for known-compromised credentials, leaked API keys, or session tokens in the request stream | ✓ Every request and response checked against a compromised credential dataset in real time — sub-millisecond, in-process; stops credential exfiltration before it reaches any AI provider |
| RS256-signed OAuth tokens with JWKS key discovery | ✕ API key-based access model — no RS256 token signing, no JWKS endpoint for automated key discovery, no kid-based key rotation; shared-secret credential model for integrations | ✓ RS256 asymmetric signing — private key signs, public key verifies via JWKS endpoint at /.well-known/jwks.json; zero-downtime kid-based key rotation; standard JWT library compatibility |
| Enterprise SIEM integration (7 connectors) | ✕ Developer observability exports — useful for engineering dashboards; institutions running Splunk, Sentinel, Elastic, Datadog, Sumo Logic, QRadar, or Cortex XSIAM as SOC infrastructure must build custom integrations | ✓ Native connectors for all 7 SIEM platforms — Splunk, Microsoft Sentinel, Elastic, Datadog, Sumo Logic, IBM QRadar, and Cortex XSIAM; AI governance events flow directly into existing SOC tooling |
Where Arbitex Gateway Wins
Logging after the fact is not governance at the wire
Helicone records what was sent to AI providers. It does not intercept requests before they reach models, inspect content against policy rules, or block non-compliant data from leaving your environment. If a user submits a prompt containing PHI, PCI cardholder data, or MNPI-adjacent content, Helicone logs it — after it has already reached the AI provider. Arbitex Gateway evaluates every request before it reaches any model. Sensitive content is flagged, redacted, or blocked at the wire — not discovered in a log review after the fact. The distinction between observability and governance is the difference between a record of what happened and enforcement of what is allowed to happen.
Compliance bundles that enforce — not dashboards that report
Helicone gives engineering teams visibility into AI usage — cost per provider, request volume, latency, prompt history. This is useful infrastructure for engineering teams. It is not what a compliance officer, CISO, or legal team needs when they are asked to demonstrate that AI model requests were governed under HIPAA, PCI-DSS, GDPR, SOX, or GLBA. Arbitex Gateway ships 12 compliance frameworks as executable policy bundles: activate a framework and the correct detectors, enforcement actions, and audit controls apply to every request and response automatically. Compliance is enforced, not reported on after the fact.
Multi-provider governance — active enforcement, not passive logging
Helicone supports multiple AI providers through its logging proxy — it records requests routed to OpenAI, Anthropic, Google, and others. But logging across providers is not governance across providers. Helicone does not enforce a single policy model across all providers, does not apply compliance controls uniformly regardless of which provider receives the request, and does not produce a tamper-evident audit chain across all AI traffic. Arbitex Gateway governs 9+ providers under one policy engine: one set of rules, one enforcement posture, one tamper-proof audit record — regardless of which AI provider the request is routed to.
The buyer is different — and so is the requirement
Helicone's buyer is the engineering team. Its product solves engineering problems: cost visibility, debugging, caching, prompt management. These are legitimate and useful capabilities for development teams. Arbitex Gateway's buyer is the compliance officer, CISO, or legal team. Its product solves governance problems: enforcing data handling policy at the model boundary, producing evidence-grade audit records for regulatory examination, detecting credential breaches before they reach an AI provider, and giving the enterprise a defensible governance posture for AI at scale. Both products have a legitimate place in an enterprise AI stack — but only one governs it.
Related Resources
Your AI stack needs more than visibility. It needs governance.
Arbitex Gateway sits in front of every AI provider, enforces policy at the model boundary, and produces the tamper-evident audit record that holds up in a compliance examination — across 9+ providers, under one policy engine.