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Helicone

Helicone is an open-source observability platform for LLM users. It helps companies monitor usage, latency, and costs for AI models like GPT-3, enabling optimization of AI applications and reduction of OpenAI bills. Helicone provides key insights into spend, performance, and usage patterns.

For agents: Open-source LLM observability platform and AI gateway for monitoring usage, latency and costs of AI model calls, with docs, OpenAPI specs and self-hosting.

llm observabilityai gatewayopenai cost trackingprompt managementopen source

Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-22T18:08:01.216Z. Cached copy · Source on helicone.ai

# Helicone

> Helicone is an open-source observability platform for LLM users. It helps companies monitor usage, latency, and costs for AI models like GPT-3, enabling optimization of AI applications and reduction of OpenAI bills. Helicone provides key insights into spend, performance, and usage patterns.

Helicone offers tools for developers to monitor, analyze, and optimize their use of large language models (LLMs). Key features include:
- Usage and cost tracking across multiple AI models
- Latency monitoring and performance optimization
- Request caching and model-swapping capabilities
- Custom property tracking for detailed analytics
- Integration with popular AI frameworks and platforms

Helicone is designed to be easily integrated into existing AI workflows, with support for self-hosted deployments and cloud-based solutions.

## Docs
- [Quick Start Guide](https://docs.helicone.ai/getting-started/quick-start): Introduction to setting up and using Helicone
- [Gateway Integration](https://docs.helicone.ai/getting-started/integration-method/gateway): Guide to integrating Helicone as a proxy for AI model requests
- [Custom Properties](https://docs.helicone.ai/features/advanced-usage/custom-properties): Advanced usage for tracking custom metrics and properties
- [Self-Hosted Deployment](https://docs.helicone.ai/getting-started/self-deploy): Instructions for deploying Helicone on your own infrastructure
- [Authentication](https://docs.helicone.ai/helicone-headers/helicone-auth): Details on authenticating requests with Helicone

## Examples
- [First AI App with Helicone](https://www.helicone.ai/blog/first-ai-app-with-helicone): Tutorial on building an AI app with Helicone integration
- [Product Hunt Launch Automation](https://www.helicone.ai/blog/product-hunt-automate): Case study on using Helicone for automating a product launch
- [Helicone vs Competitors](https://www.helicone.ai/blog/portkey-vs-helicone): Comparison of Helicone with other LLM observability tools

## Optional
- [GitHub Repository](https://github.com/Helicone/helicone): Source code and open-source contributions
- [Y Combinator Profile](https://www.ycombinator.com/companies/helicone): Information about Helicone's participation in Y Combinator
- [Company Blog](https://www.helicone.ai/blog): Latest updates, tutorials, and insights from the Helicone team
- [API Reference](https://docs.helicone.ai/getting-started/quick-start): Detailed API documentation for advanced integrations

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Claim my listing on Agent Web Map for helicone.ai:
1. POST https://agentwebmap.com/v1/sites/helicone.ai/claims and keep claim_id and claim_secret private.
2. Publish the proof: add the line "AgentWebMap ownership: <token>" (token from step 1) to https://helicone.ai/llms.txt, or use the DNS, meta-tag or well-known method the response describes.
3. POST https://agentwebmap.com/v1/sites/helicone.ai/verify with {"claim_id": "...", "claim_secret": "..."}.
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MCP equivalent: tools begin_ownership_claim, then verify_domain, at https://agentwebmap.com/mcp. Docs: https://agentwebmap.com/docs#verify

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