Helicone

Overview

Helicone is an AI Gateway and LLM Observability platform built for engineering teams that need to route, debug, and analyze AI applications in production. It provides a unified control plane for managing traffic to major large language model providers, including OpenAI, Anthropic, Azure, LiteLLM, Anyscale, Together AI, OpenRouter, and other compatible endpoints. As an LLMOps solution adopted by some of the world's fastest-growing AI companies, Helicone helps organizations move from experimental prototypes to reliable, observable AI systems.

The platform acts as an intermediary layer between applications and LLM APIs, capturing structured telemetry for every request. Its dashboard enables granular inspection of requests, sessions, segments, and users, making it straightforward to trace behavior, debug failures, and understand usage patterns. Helicone also offers HQL (Helicone Query Language), a query capability that lets teams search and analyze request logs for deeper operational and product insights. For teams working on prompt quality, Helicone includes tools for prompt improvement, dataset management, and an interactive playground where model outputs can be tested and compared.

Helicone also focuses on operational reliability by supporting rate limit monitoring and configurable alerts. This helps teams avoid throttling and service degradation, particularly when integrating multiple providers with different rate policies. The gateway-based architecture simplifies provider switching, fallback strategies, and multi-model testing without requiring large changes to application code. For AI-first companies, this combination of routing, monitoring, and analytics reduces the friction of operating LLM applications at scale and provides the visibility needed for continuous optimization.

Developers can start with a 7-day free trial on the cloud platform without providing a credit card. The onboarding process is designed to be developer-friendly, with documentation, integrations, and community support. Once connected, teams can use Helicone as their central observability and gateway layer for LLM workloads. With its recent announcement of joining Mintlify, Helicone continues to evolve its ecosystem for AI application development, positioning itself as a foundational tool in the modern LLM stack.

Core capabilities

AI Gateway & Request Routing

Route LLM calls across multiple providers such as OpenAI, Anthropic, Azure, LiteLLM, Anyscale, Together AI, and OpenRouter through a unified gateway.

LLM Observability & Monitoring

Capture detailed telemetry for every request, including prompts, responses, latency, token usage, and error rates.

Requests Dashboard

Inspect individual requests with full metadata and trace-level views to simplify debugging.

Sessions & Segments

Group related requests into user sessions and analyze behavioral segments for deeper product insights.

Users Analysis

Track per-user usage patterns, costs, and activity to understand adoption and identify outliers.

HQL (Helicone Query Language)

Write custom queries to explore LLM logs and extract actionable intelligence from historical traffic.

Prompt Improvement & Datasets

Curate, version, and manage datasets to support prompt engineering, fine-tuning, and evaluation workflows.

Playground

Interactively test prompts and models with configurable parameters to compare outputs and iterate quickly.

Rate Limit Alerts & Monitoring

Set threshold-based alerts and monitor rate limit consumption to prevent throttling and outages.

Use cases

Production monitoring of LLM API traffic for latency, errors, and cost

Centralized routing and failover across multiple LLM providers

Debugging and tracing individual requests or session-level conversations

Analyzing user behavior and usage patterns through session and user analytics

Running custom HQL queries for deep investigation of request logs

Improving prompt quality with datasets and an interactive playground

Proactive alerting on rate limits and usage thresholds to prevent downtime