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Description

AI engineering can be transparent rather than opaque. With a suite of tools for tracing, assessment, prompt management, and more, HoneyHive emerges as a comprehensive platform for AI observability and evaluation, aimed at helping teams create dependable generative AI applications. This platform equips users with resources for model evaluation, testing, and monitoring, promoting effective collaboration among engineers, product managers, and domain specialists. By measuring quality across extensive test suites, teams can pinpoint enhancements and regressions throughout the development process. Furthermore, it allows for the tracking of usage, feedback, and quality on a large scale, which aids in swiftly identifying problems and fostering ongoing improvements. HoneyHive is designed to seamlessly integrate with various model providers and frameworks, offering the necessary flexibility and scalability to accommodate a wide range of organizational requirements. This makes it an ideal solution for teams focused on maintaining the quality and performance of their AI agents, delivering a holistic platform for evaluation, monitoring, and prompt management, ultimately enhancing the overall effectiveness of AI initiatives. As organizations increasingly rely on AI, tools like HoneyHive become essential for ensuring robust performance and reliability.

Description

With a suite observability tools, you can confidently evaluate, test and ship LLM apps across your development and production lifecycle. Log traces and spans. Define and compute evaluation metrics. Score LLM outputs. Compare performance between app versions. Record, sort, find, and understand every step that your LLM app makes to generate a result. You can manually annotate and compare LLM results in a table. Log traces in development and production. Run experiments using different prompts, and evaluate them against a test collection. You can choose and run preconfigured evaluation metrics, or create your own using our SDK library. Consult the built-in LLM judges to help you with complex issues such as hallucination detection, factuality and moderation. Opik LLM unit tests built on PyTest provide reliable performance baselines. Build comprehensive test suites for every deployment to evaluate your entire LLM pipe-line.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Claude Yes 
LangChain Yes 
LlamaIndex Yes 
OpenAI Yes 
Pinecone Yes 
Codestral Yes 
Databricks Yes 
DeepEval No 
Flowise No 
Gemini Yes 
Gemini 1.5 Flash Yes 
Gemini 2.0 Yes 
Kong AI Gateway No 
LiteLLM No 
MLflow Yes 
Mistral 7B Yes 
Predibase No 
Snowflake Yes 
Tome Yes 

Integrations

Claude Yes 
LangChain Yes 
LlamaIndex Yes 
OpenAI Yes 
Pinecone Yes 
Codestral No 
Databricks No 
DeepEval Yes 
Flowise Yes 
Gemini No 
Gemini 1.5 Flash No 
Gemini 2.0 No 
Kong AI Gateway Yes 
LiteLLM Yes 
MLflow No 
Mistral 7B No 
Predibase Yes 
Snowflake No 
Tome No 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

$39 per month
Free Trial Yes 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

HoneyHive

Founded

2022

Country

United States

Website

www.honeyhive.ai/

Vendor Details

Company Name

Comet

Founded

2017

Country

United States

Website

www.comet.com/site/products/opik/

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