Helicone

What if you could build AI apps with enterprise-grade reliability and observability?

RecommendedHelicone provides an open-source, comprehensive platform for managing and observing LLM-powered applications, ideal for developers and enterprises focused on reliability and cost efficiency.

Helicone is an open-source LLM observability platform and AI Gateway designed to help developers route, debug, and analyze their AI applications. It offers features like smart load balancing, intelligent caching, automatic failover, and rate limiting to ensure reliability and cost efficiency.

Key Features:
  • AI Gateway for routing, caching, and rate limiting
  • LLM Observability & Analytics (cost tracking, sessions, user metrics)
  • Prompt Management with version control and instant deployment
  • Multi-provider support (OpenAI, Anthropic, Google, Azure, etc.)
  • Self-hosting option for complete data sovereignty
Pros
  • AI developers needing to debug and analyze LLM usage
  • Teams requiring robust LLM routing and caching
  • Organizations with strict security and compliance for LLM data
Cons
  • Some integration methods are maintained but no longer actively developed, encouraging use of the AI Gateway.
  • Full benefits require integration with their AI Gateway or SDKs.
  • Pricing for higher tiers can be significant for smaller teams.
Pricing
freemiumFree tier
Starting at:$79/month
Free tier:10,000 free requests, 1 GB storage, 1 seat, 1 organization
Plans
  • Hobby: Free (10,000 requests/mo, 1GB storage, 1 seat)
  • Pro: $79/month (Unlimited seats, alerts & reports, HQL, usage-based pricing)
  • Team: $799/month (Everything in Pro, 5 organizations, SOC-2 & HIPAA, dedicated Slack, usage-based pricing)
  • Enterprise: Contact us (Custom MSA, SAML SSO, on-prem deployment, bulk cloud discounts)
Trial:7-day free trial for Pro and Team plans
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Quick Decision
Try if: You are building AI applications and need robust tools for LLM observability, cost tracking, prompt management, and a flexible AI gateway with multi-provider support.
Skip if: You are looking for a simple, non-technical solution for basic AI tasks or do not require advanced LLM management features.
Not for: Users seeking a simple, no-code AI solution; Individuals not working with LLM APIs directly
Trust Signals
  • Founded


    2025
  • Team Size


    small
Compliance
SOC-2 Type IIHIPAA
Notable Customers
Xpedia AI
Tech Details
Platforms
webapi
Integrations
OpenAIAnthropicAzureLiteLLMAnyscaleTogether AIOpenRouterPostHogGitHub ActionsOpen WebUI
Open Source
Yes
Support
Channels
emaildiscordchat
Company
  • Name


    Helicone, Inc.
  • Location


    San Francisco, CA

Helicone, Inc. aims to revolutionize the developer workflow for LLMs and define the future LLM developer, providing a platform trusted by fast-growing AI companies.

FAQ

What is the Helicone AI Gateway?

The Helicone AI Gateway is an open-source, high-performance proxy that sits between your application and LLM providers. It offers features like smart load balancing, intelligent caching, automatic failover, and rate limiting to manage LLM traffic at scale.

Can I self-host Helicone?

Yes, Helicone offers a self-hosting option that allows you to deploy their observability platform directly within your own infrastructure with a single Docker command. This is ideal for organizations with strict security and compliance requirements.

How does Helicone compare to LangSmith?

Helicone offers more provider flexibility, is open-source, and scales more cost-effectively compared to LangSmith. It provides a more intuitive UI and comprehensive features for prompt management, experiments, and gateway functionalities.

What LLM providers does Helicone support?

Helicone supports a wide range of LLM providers including OpenAI, Anthropic, Azure, Google, Groq, Mistral AI, and many others, with unified API access to over 100 models.

How is Helicone's usage-based pricing calculated?

Helicone's usage-based pricing is calculated based on requests per month, tokens per request, and storage. They offer a pricing calculator to estimate monthly costs.

Use Cases
  • AI developers needing to debug and analyze LLM usage
  • Teams requiring robust LLM routing and caching
  • Organizations with strict security and compliance for LLM data
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