What it does
Helicone gives AI application teams an OpenAI-compatible gateway and a request-monitoring dashboard. Route model calls through its gateway or use a provider integration to collect request data, then inspect prompts and responses, group activity into sessions, and review cost and latency. The platform also includes alerts, reports, datasets, and prompt tools. It helps developers find where an LLM workflow is slow, costly, or returning unexpected output; application changes and model fixes remain the team's responsibility.
A useful first pass is to send one non-sensitive development request through Helicone's AI Gateway. The official quickstart uses a familiar OpenAI client with Helicone's gateway URL and API key; after sending the call, the documentation says it should appear in the Requests view. From there, developers can inspect request details and use sessions, user metrics, custom properties, and cost tracking to separate one customer flow or feature from another.
Teams that already have model-provider calls in place can instead choose a documented provider integration, while teams still deciding how to connect providers can use the gateway's unified endpoint and routing features. This makes Helicone useful for diagnosing request behavior and spend without replacing the application code that owns the prompt, retries, or business logic. Alerts and reports help surface changes, but they do not determine whether a response is correct unless the team supplies suitable evaluation signals.
The hosted Hobby plan is free with request and storage limits; higher tiers add collaboration, alerting, query, and retention capabilities, and usage-based charges also apply. Check the live plan terms before sending production traffic because request volume and stored data affect the bill.
Strengths
- The quickstart reuses the OpenAI SDK shape while directing requests through Helicone's gateway.
- Request, session, cost, and latency views help connect an individual model call to application activity.
- The hosted plan comparison publishes request and storage allowances alongside its paid tiers.
Watch out for
- The free hosted tier has request and storage caps, and paid plans add usage-based charges.
- Gateway-based collection requires changing the request endpoint and configuring a Helicone key; provider integrations are a separate setup path.
Best for
- Developers diagnosing slow or costly LLM requests across an AI application.
- Teams that want a unified endpoint and request analytics while building with multiple model providers.
Sources
- Helicone / AI Gateway & LLM Observability (Oct 26, 2026)
- Quickstart - Helicone OSS LLM Observability (Oct 26, 2026)
- Helicone Pricing | Ship Your AI App With Confidence (Oct 26, 2026)