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Open-source LLM observability and gateway platform offering one-line integration, request logging, prompt management, evals, and a multi-provider proxy.
Open-source LLM observability and gateway platform offering one-line integration, request logging, prompt management, evals, and a multi-provider proxy.
Helicone is an open-source LLM observability platform with one-line proxy integration, prompt versioning, multi-provider gateway, caching, and self-host option under Apache 2.0.
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
$79/month
$799/month
Custom
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We believe in transparent reviews. Here's what Helicone doesn't handle well:
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.
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Pricing and features change often. If anything on this Helicone page is wrong or missing, tell us and include a link to the source. We review every correction.