Open-source LLM observability, gateway, and cost analytics platform — proxy your OpenAI, Anthropic, or Bedrock calls through Helicone and get traces, caching, retries, rate limiting, and cost tracking in one line of code.
Open-source LLM observability, gateway, and cost analytics platform — proxy your OpenAI, Anthropic, or Bedrock calls through Helicone and get traces, caching, retries, rate limiting, and cost tracking in one line of code.
Helicone is a developer-first observability layer for LLM applications. The common integration is a one-line change: point your OpenAI or Anthropic client at Helicone's proxy URL and add an API key header. From there, every request is logged with full prompt, response, tokens, cost, latency, cache status, and metadata; a rich UI lets you filter, replay, and diff requests, group by user, session, or feature, and build dashboards. Beyond passive logging, Helicone acts as a gateway with response caching, prompt-template versioning, automatic retries, rate limiting per user/key, key vault, and provider routing (fallback from primary to secondary provider on error). Evaluations and a small experiments product let you compare prompts on saved datasets. Helicone is open source under the Apache 2.0 license and can be self-hosted; the hosted plan has a free tier (100k logs/mo), Pro at $20/user/mo, Team ($200/mo), and Enterprise. For teams that want a lightweight, provider-agnostic way to understand what their LLM app is actually doing in production without ripping out their existing SDK, Helicone is one of the fastest integrations on the market.
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Helicone is the fastest win when a team needs to see LLM requests, latency, users, and cost before investing in a heavier evaluation platform.
AI gateway is a core Helicone capability confirmed from the staged data and fetched vendor copy.
Use Case:
LLM cost monitoring by model, user, endpoint or feature.
request logging is a core Helicone capability confirmed from the staged data and fetched vendor copy.
Use Case:
Debugging bad AI responses using request logs, sessions and prompt history.
sessions/users analytics is a core Helicone capability confirmed from the staged data and fetched vendor copy.
Use Case:
Routing and gateway governance across multiple LLM providers.
prompts and datasets is a core Helicone capability confirmed from the staged data and fetched vendor copy.
Use Case:
LLM cost monitoring by model, user, endpoint or feature.
alerts and reports is a core Helicone capability confirmed from the staged data and fetched vendor copy.
Use Case:
Debugging bad AI responses using request logs, sessions and prompt history.
$0
$20/user/month
$200/month
Custom
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Helicone has expanded session tracking and trace grouping in 2025, added experiment tracking with A/B testing for prompt variations with statistical significance analysis, broadened provider support to include AWS Bedrock, Groq, Together AI, and Fireworks AI, and introduced an AI Gateway product that unifies routing across providers with automatic fallback and key management. The platform also added prompt management with versioning and a template registry where teams can manage production prompts with full version history, an evaluation framework for systematic quality testing using LLM-as-judge scoring and custom evaluation functions, and the ability to create datasets from production logs for fine-tuning or evaluation workflows. Additional improvements include configurable alerting on cost thresholds, error rates, and latency spikes via webhooks, and deeper integrations with LLM frameworks including LangChain, LlamaIndex, CrewAI, and the Vercel AI SDK.
AI observability
An open-source observability and evaluation platform for language-model applications.
AI Observability
LangSmith is LangChain's commercial observability, evaluation and prompt management platform for LLM apps and agents in production.
AI evaluation
Braintrust provides ai evaluation capabilities for teams building and operating AI applications. It supports the MCP ecosystem.
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