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Analyze performance and user feedback from your application in production to detect anomalies, address issues, and drive continuous improvement.
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Compute integrity and performance metrics across your data to detect LLM failures in production.
Capture user feedback to track performance and user experience across your LLM apps.
Create your own queries to monitor the performance of specific components in your RAG or agent pipelines.
Save custom charts to your team workspace for quick access to insights that matter to you the most.
Slice and dice your data across segments and get detailed insights into application performance.
Log application data synchronously and asynchronously, depending on your specific needs. No proxy required.
LLMs often lead to unexpected failures in production. HoneyHive allows you to monitor your LLM apps with quantitative rigor and get actionable insights to continuously improve your app.
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Log LLM application data with just a few lines of code
Enrich logs with user feedback, metadata, and user properties
Query logs and save custom charts in your team dashboard
LLM apps fail due to issues in either the prompt, model, or your data retrieval pipeline. With full visibility into the entire chain of events, you can quickly pinpoint errors and iterate with confidence.
Debug chains, agents, tools and RAG pipelines
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Root cause errors with AI-assisted RCA
Integrates with leading orchestration frameworks
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HoneyHive enables you to filter, curate, and label datasets from production logs for fine-tuning and evaluation.
Filter and add underperforming test cases from production
Invite domain experts to annotate and provide ground truth labels
Manage and version fine-tuning datasets across workspaces
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Run online evaluators on your live production data to catch LLM failures automatically.
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Evaluate faithfulness and context relevance across RAG pipelines
Write assertions to validate JSON structures or SQL schemas
Implement moderation filters to detect PII leakage and unsafe responses
Semantically analyze text for topic, tone, and sentiment
Calculate NLP metrics such as ROUGE-L or METEOR
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Sync and async logging. Does not require proxying your requests via our servers.
Any model, any framework, any cloud. Works with any model, orchestration framework, or GPU cloud.
Extensible data model. Helps you monitor your LLM chains, agents, and RAG pipelines with end-to-end visibility.
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