Helicone
🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓
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What is Helicone?
Helicone is an open-source AI gateway and LLM observability platform built to help teams route, debug, monitor, and analyze AI applications through one OpenAI-compatible interface. It lets you access 100+ models from providers like OpenAI, Anthropic, Google, Groq, Vertex, and others without rewriting integrations. The platform is positioned as infrastructure for production AI apps, with a focus on reliability, flexibility, and visibility across requests. It is designed for developers, startups, and larger teams that need to manage model usage, costs, latency, and failures in one place.
The gateway layer handles intelligent routing, automatic failover, caching, and rate limits. It also provides complete observability so teams can trace requests, inspect metrics, and understand errors and performance bottlenecks. Helicone presents itself as a single endpoint that sits between your app and model providers, translating requests to the correct provider format and logging the results. The site also emphasizes that it can work with the familiar OpenAI SDK, which lowers adoption friction.
Beyond gateway functionality, Helicone includes LLMOps features such as monitoring, prompts and testing, playground tools, scoring, datasets, webhooks, reports, and analytics. It also supports data retention controls, API access, export, and configurable storage options on higher plans. The pricing page shows it as a platform that scales from hobby usage to enterprise deployments. Its open-source positioning and self-hosting angle make it especially relevant for teams that want control over infrastructure and vendor flexibility.
The product appears best suited for engineering teams building LLM apps that need dependable routing and operational visibility, especially where provider switching, fallback behavior, and cost management matter. It is also a fit for organizations that want observability and experimentation tools in the same workflow as their inference gateway. According to the site, Helicone is used by fast-growing AI companies and offers collaboration, support, and compliance features for more mature teams.
Helicone pricing
Pricing model: Freemium
Helicone offers a Free Hobby plan, a Pro plan at $79 per month with usage-based pricing, a Team plan at $799 per month with usage-based pricing, and an Enterprise plan with custom pricing via sales. The pricing page says you only pay for what you use, and the Pro plan includes a 7-day free trial. The Hobby plan includes 10,000 requests per month, 1 seat, 1 organization, 7 days of retention, and 1 GB storage. Pro includes unlimited seats, 1 organization, 1 month retention, 1 GB free storage plus usage-based expansion, 1,000 logs/min ingestion, and 10 API calls/min. Team includes unlimited seats, 5 organizations, 3 months retention, 15,000 logs/min ingestion, 60 API calls/min, and larger collaboration/support features. Enterprise includes unlimited organizations, forever retention, 30,000 logs/min ingestion, 1,000 API calls/min, and advanced support and compliance items such as HIPAA, SOC 2 Type II, SAML SSO, infoSec reviews, customized MSAs, private Slack channel, dedicated support engineer, and SLAs. The page also lists discounts for startups, nonprofits, open-source companies, and students.
Helicone pros
- Open-source platform
- OpenAI-compatible API
- Access to 100+ models
- Single-line integration
- Intelligent routing
- Automatic failovers
- Built-in caching
- Rate limiting support
- Unified observability
- Cost tracking
- Latency tracking
- Error logging
- Prompt management
- Playground included
- Evals with LLM-as-Judge
- Human annotations support
- Model registry with 500+ models
- Self-hosted option
- Flexible provider switching
- Enterprise compliance options
Helicone cons
- Usage-based pricing on paid plans
- Free plan is limited to one seat
- Hobby plan has only 7-day retention
- Hobby plan has 10,000 requests per month limit
- API access is restricted on lower plans
- Some features are gated to higher tiers
- Enterprise pricing requires contact sales
- Pricing page leaves some FAQ sections visually incomplete
- Advanced compliance features are not on the free plan
- Storage limits still apply on paid tiers
Frequently asked questions about Helicone
What is Helicone used for?
Helicone is used to route, debug, monitor, and analyze LLM applications through a single OpenAI-compatible API. It combines an AI gateway with observability, so teams can send requests to many model providers while collecting metrics, costs, latency, and errors in one place.
How does the AI Gateway work?
The gateway sits between your app and the model provider. You send one request in the OpenAI SDK format, Helicone translates it to the target provider format, routes it, applies features like failover or caching when configured, and logs the result with observability data.
Which models and providers does Helicone support?
The site says Helicone gives access to 100+ models and supports providers including OpenAI, Anthropic, Google, Vertex, Groq, and others. It also includes a model registry that advertises 500+ models for comparing costs, context windows, and providers.
Do I need to rewrite my integration to use Helicone?
No. Helicone says its gateway is OpenAI-compatible, so you can use the familiar OpenAI SDK and keep the integration pattern you already know. The site also says the gateway can work without new dependencies or rewriting integrations.
What observability features does Helicone include?
Helicone includes request tracing, monitoring, cost tracking, latency tracking, quality analysis, error capture, user analytics, custom properties, alerts, and reports. The platform is built to help teams see what their LLM app is doing in production and identify bottlenecks quickly.
What gateway controls are available?
The site highlights caching, rate limits, intelligent routing, and automatic fallbacks. These features are meant to improve reliability and performance when using multiple providers or when a preferred model becomes unavailable.
Does Helicone support prompt testing and evaluation?
Yes. The pricing page lists prompts and testing features such as a playground, prompts, scores, datasets, webhooks, and evals with LLM-as-Judge and human annotations. These tools are aimed at experimentation and quality review for LLM workflows.
What are the main plan differences?
The Hobby plan is free and limited, while Pro and Team add more retention, ingestion, API access, and collaboration capacity. Team expands organizations and throughput further, and Enterprise adds the highest limits plus compliance, SLAs, and dedicated support options.
Is Helicone only for startups?
No. The site positions Helicone for a range of users, from hobby projects and startups to enterprise teams. The pricing page specifically includes startup discounts, nonprofit discounts, open-source company credits, and student access.
Can Helicone be self-hosted?
Yes. The site describes Helicone as open-source and says the AI Gateway is ready to deploy in your own infrastructure. That makes it suitable for teams that want more control over hosting and provider management.