HoneyHive is an advanced AI evaluation and observability platform designed to help developers build reliable AI products. It offers tools for performance monitoring, prompt management, dataset curation, and automated evaluation, ensuring quality and accountability in AI applications. The platform allows tracking metrics, debugging interactions, and managing every aspect—from prompt versioning to logging needs. HoneyHive supports large-scale operations with features like Distributed Tracing, Human Annotation, and seamless integration with various AI frameworks and cloud services.
• performance monitoring
• prompt management
• user feedback management
• automated evaluators
• distribution tracing
An event refers to a single trace span, structured log, or metric label combination sent to our API as OTLP or JSON.
An automated evaluator is a function (code or LLM) that helps you unit test any arbitrary event or combinations of events to generate a measurable score.
Yes, HoneyHive allows you to filter and curate datasets which can be annotated and exported for fine-tuning.
All data is encrypted in transit and at rest, with regular penetration tests and varied hosting solutions.
Yes, we support logging up to 5MB per span, allowing for approximately 1.7M tokens.
Prompts are stored as YAML configurations, which can be fetched using the API.
You can log traces using our SDKs and API endpoints or via batch ingestion.
• 10k events per month
• 90d log retention
• Up to 2 users
• Full evaluation and observability suite
• Custom usage limits
• SSO & SAML
• VPC hosting add-on
• Dedicated support and SLA
AI evaluation and observability platform for building reliable AI products.
AI evaluation and observability platform for building reliable AI products.
AI evaluation and observability platform for building reliable AI products.
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