Comparison · reviewed August 7, 2026

AI Gateway HQ vs. Helicone

Prevent and explain policy or budget violations before inference, while minimizing stored model content by default.

  • Pre-dispatch control
  • Operator-ready evidence
  • Prompt storage off by default
Working sandbox capture
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Why teams choose AI Gateway HQ

Choose AI Gateway HQ when the primary question is ‘should this request be allowed, funded, and routed?’ rather than only ‘what happened afterward?’ Helicone is a strong experimentation and observability product; AI Gateway HQ owns the preventive enterprise decision boundary.

The runtime evaluates identity, signed workload context, risk signals, policy, budget, rate, concurrency, route capability, and provider health before decrypting the selected credential or dispatching upstream.

Capability evidence

Compare the operating boundary.

AI Gateway HQ entries describe implemented product behavior. Alternative entries summarize the linked first-party documentation—not anonymous review scores.

Decision areaWhat AI Gateway HQ deliversWhat Helicone documents
Gateway and routing

One OpenAI/Anthropic-compatible endpoint; encrypted multi-account BYOK pools; capability-first priority, weighted, request-cost, health, and request-aware provider-capacity selection; shared quota cooldowns and bounded, reason-coded fallback.

OpenAI-compatible gateway across 100+ providers with managed credits, fallback, caching, and integrated observability.

Spend enforcement

Atomic organization-and-workload reservation before forwarding, strict rate and concurrency enforcement, explicit output caps, and settlement against supported provider-reported usage. Promotional credit cannot fund server-paid model exposure.

Rate limits and cost tracking alongside sessions, prompts, experiments, and request analytics.

Identity and governance

OIDC administration, mandatory MFA, built-in least-privilege roles, virtual workload keys, signed execution context, Observe/Shadow/Enforce policy, and local jailbreak, injection, exfiltration, encoding, and Unicode risk signals.

Team controls and Enterprise SAML; the platform is especially deep in developer-facing LLM observability.

Deployment and evidence

WAF-protected AWS serverless deployment, tenant-bound KMS encryption, signed releases, payload-free request metadata by default, tamper-evident audit exports, and customer-approved time-bounded support access.

Managed service with Enterprise self-hosting options.

Public commercial model

A free BYOK proving tier, then $0.10 per 1,000 successful Flex requests with no percentage markup on inference purchased through customer-owned provider accounts; higher-control plans are scoped by operating requirements.

Hobby is free for 10,000 requests; Pro lists $79/month, Team $799/month, and Enterprise is custom; managed credits state 0% markup.

When to consider Helicone

Consider Helicone when prompt experiments, sessions, and deep developer observability are more important than minimal-data preventive governance.

Comparison method

Facts were reviewed from the linked first-party documentation and pricing pages on August 7, 2026. Public meters are not normalized: requests, logs, credits, infrastructure, and enterprise capacity are different units. Revalidate pricing and capabilities before purchasing.