Helicone

What is Helicone?

Helicone is an open-source LLM observability platform and AI gateway that logs, monitors, and optimizes requests across 100+ AI models from a single integration point. It works as a proxy sitting between your application and any LLM provider, capturing every request and response with under 1ms of added latency. Helicone targets engineering teams building production AI applications who need cost tracking, debugging, and performance monitoring without overhauling their existing codebase. Y Combinator-backed (W23) and SOC 2 Type II certified, it supports both cloud-hosted and self-hosted deployment via Docker and Kubernetes.

Key Features

• AI Gateway (Proxy): Route all LLM requests through a single endpoint that supports 24+ providers including OpenAI, Anthropic, Google, Azure, Groq, Together AI, and DeepSeek, with automatic fallbacks when a provider goes down
• One-Line Integration: Switch your base URL to Helicone's gateway and start logging immediately, with no SDK changes needed for OpenAI-compatible providers
• Request Logging and Tracing: Every API call is captured with full input/output, latency, token counts, and cost breakdowns, with multi-step interaction visualization for debugging agent workflows
• Cost Tracking: Break down LLM spend by model, user, feature, or custom property so teams know exactly where their API budget goes
• Prompt Management: Version, test, and roll back prompts from a central dashboard without redeploying application code
• Caching and Rate Limiting: Cache repeated identical requests to cut costs and latency, and set per-user or per-key rate limits to prevent runaway spend
• Custom Dashboards and Alerts: Build dashboards with custom metrics, set up alerts for latency spikes or error rate thresholds, and query logs with HQL (Helicone Query Language)
• Async Logging Mode: For teams that prefer not to route traffic through a proxy, Helicone offers SDK-based async logging that captures the same telemetry without sitting in the request path

Use Cases

• AI startups in production: Teams shipping LLM-powered features use Helicone to monitor costs and latency across multiple providers, catching regressions before users notice
• Agent developers debugging multi-step workflows: Engineers building autonomous agents trace full execution chains to pinpoint where an agent fails or produces unexpected output
• Platform teams managing LLM costs: Engineering leads track per-team and per-feature LLM spend to enforce budgets and identify optimization opportunities across the organization
• Solo developers and indie builders: Individual developers on the free tier log up to 10,000 requests per month to understand usage patterns and keep API costs under control

Strengths and Weaknesses

Strengths:

• Setup is fast. Most teams integrate in under 2 minutes by swapping a base URL, with no application code changes needed for basic logging
• Open-source under Apache 2.0 with 5.5K GitHub stars, so teams can self-host and audit the codebase
• SOC 2 Type II certified and HIPAA compliant, meeting enterprise security requirements out of the box
• The proxy adds under 1ms of computational overhead with global edge deployment, so it does not meaningfully slow down LLM requests
• Active Discord community and responsive support, with enterprise customers getting a dedicated Slack channel

Weaknesses:

• The free Hobby tier is limited to 10,000 requests with only 7 days of data retention and a 10 logs/min ingestion cap, which is tight for anything beyond prototyping
• The jump from free to Pro at $79/month may feel steep for small teams that exceed the free tier but do not yet need the full Pro feature set
• Self-hosting requires managing Docker or Kubernetes infrastructure, which adds operational overhead compared to cloud-only competitors

Pricing

• Hobby (Free): 10,000 requests, 1 GB storage, 7-day data retention, 1 seat, 10 logs/min ingestion rate
• Pro: $79/month, includes everything in Hobby plus unlimited seats, alerts, reports, HQL, 1,000 logs/min ingestion, 1-month data retention, 7-day free trial
• Team: $799/month, includes everything in Pro plus 5 organizations, SOC 2 and HIPAA compliance, dedicated Slack channel, 15,000 logs/min ingestion, 3-month data retention, 7-day free trial
• Enterprise: Custom pricing, includes everything in Team plus custom MSA, SAML SSO, on-prem deployment, bulk cloud discounts, 30,000 logs/min ingestion, unlimited data retention

FAQ

Is Helicone free?

Yes. The Hobby tier is free forever and includes 10,000 requests per month with 7 days of data retention. No credit card is required to sign up.

Is Helicone open source?

Yes. Helicone is open-source under the Apache 2.0 license. The full codebase is on GitHub with 5.5K stars, and teams can self-host using Docker or Kubernetes with production-ready Helm charts.

How does Helicone integrate with my existing LLM setup?

Helicone works as a proxy. You change your LLM provider's base URL to Helicone's gateway endpoint and add an authentication header. For OpenAI-compatible providers, this is a one-line change. Helicone also offers async SDK-based logging for teams that prefer not to route traffic through a proxy.

What LLM providers does Helicone support?

Helicone supports 24+ providers including OpenAI, Anthropic, Google (Gemini and Vertex AI), Azure, Groq, Together AI, Mistral, DeepSeek, Fireworks, OpenRouter, AWS Bedrock, and Cloudflare.

Helicone vs Langfuse: what is the difference?

Both are open-source LLM observability platforms. Helicone focuses on being an AI gateway with proxy-based integration and built-in routing features like caching and rate limiting. Langfuse centers on tracing, evaluation, and prompt management with deeper SDK-based instrumentation. Helicone is faster to set up (URL swap), while Langfuse offers more granular trace-level analysis.

Does Helicone add latency to my LLM requests?

Helicone's proxy is deployed at the edge globally and adds under 1ms of computational overhead. For teams concerned about any added latency, the async logging mode bypasses the proxy entirely.