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Helicone is an AI gateway and observability platform that routes, debugs, and analyzes LLM applications for reliable AI products. It supports 100+ models with a single integration and offers monitoring and analytics tools.

Helicone positions itself as an AI gateway and observability platform purpose-built for teams that need to route, debug, and analyze LLM applications at scale. Backed by Y Combinator and trusted by companies like Duolingo, Clay, and Singapore Airlines, it has quickly become a go-to tool for developers who want to manage multiple AI models without getting locked into a single provider. The platform's core value proposition is simplicity: a single SDK that works with over 100 models from OpenAI, Anthropic, Azure, Mistral, and others, allowing teams to switch providers by simply changing the model name in their code.

What sets Helicone apart is its focus on operational reliability. Beyond basic routing, it offers real-time monitoring of rate limits, latency, and error rates, plus alerting when things go wrong. The dashboard provides granular insights into request data, user sessions, and prompt performance, making it easy to spot issues and optimize costs. Features like caching, response logging, and a built-in playground for prompt testing further streamline the development workflow. For teams that need compliance, the Team plan includes SOC-2 and HIPAA support, while Enterprise offers on-prem deployment and SAML SSO.

Pricing is tiered to accommodate different scales. The free Hobby plan gives 10,000 requests and 1 GB storage, ideal for small experiments. The Pro plan at $79/month removes request limits and adds unlimited seats, making it a strong fit for growing teams. The Team plan at $799/month adds multi-org support, dedicated support, and longer retention. Enterprise pricing is custom. All paid plans come with a 7-day free trial, and no credit card is required to start.

Helicone is best suited for AI engineering teams that need to manage multiple model providers, debug production issues quickly, and gain visibility into usage patterns. It's particularly valuable for fast-growing startups and scale-ups that want to avoid vendor lock-in and keep their AI stack flexible. The intermediate complexity means developers comfortable with API integrations will find it straightforward, but non-technical users may need some support.

Overall, Helicone delivers a polished, developer-friendly experience for LLM observability and gateway management. Its strength lies in the combination of broad model support, fast setup, and actionable analytics. While the free tier is limited, the paid plans offer good value for teams that need reliable monitoring and the freedom to switch providers on the fly. If you're building AI products and want to avoid the headache of managing multiple APIs, Helicone is a practical choice worth evaluating.

Features

  • Route, debug, and analyze applications
  • Access every AI model easily
  • Switch providers with no code rewrites
  • Monitor rate limits and alerts
  • Use one SDK for all models
  • Free trial with no credit card
  • One SDK for 100+ models
  • Caching and performance monitoring
  • Analytics and debugging tools

Pricing

Free (Hobby), $79/mo (Pro), $799/mo (Team), Custom (Enterprise)

Pros

  • Intuitive UI and fast setup
  • Cost-effective scaling with usage-based pricing
  • Comprehensive monitoring and analytics for LLM applications

Cons

  • Intermediate complexity may require some technical knowledge
  • Free tier limited to 10,000 requests and 7-day retention

Best For

AI teams and fast-growing companies building reliable AI products

Frequently Asked Questions

Helicone is an AI gateway and observability platform that routes, debugs, and analyzes LLM applications, allowing teams to monitor request data, improve prompt effectiveness, and switch between 100+ models without code rewrites.
Pricing starts with a free Hobby plan offering 10,000 requests and 7-day data retention, then scales to Pro at $79/mo, Team at $799/mo, and custom Enterprise pricing with usage-based options.
It supports over 100 models through a single SDK integration, enabling users to route requests across providers like OpenAI, Anthropic, and others without changing code.
The platform provides detailed request logs, error tracking, and latency analysis, making it easy to identify issues in LLM calls and improve reliability.
The tool has an intuitive UI and fast setup, but intermediate complexity may require some technical knowledge to fully leverage its debugging and routing features.
Common use cases include debugging AI applications, monitoring usage patterns, improving prompt effectiveness, and routing AI requests across multiple providers for cost and performance optimization.
It offers a single integration for 100+ models, usage-based pricing for cost-effective scaling, and comprehensive monitoring and analytics, making it ideal for fast-growing AI teams.
Support includes a knowledge base with guides and tutorials, plus email support for paid plans; Enterprise customers get dedicated support and custom SLAs.
Yes, the Team and Enterprise plans are designed for high-volume usage, with features like rate limit monitoring, alerts, and scalable infrastructure to support growing applications.
The platform includes data encryption, access controls, and compliance options for Enterprise customers, ensuring secure handling of LLM request data.
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