HoneyHive

Overview

HoneyHive is based in New York and San Francisco, specializing in an observability and evaluation platform for AI applications. The company, founded in 2022 by experts from Microsoft, Amazon, and JP Morgan, focuses on supporting enterprises building, testing, deploying, and improving reliable AI products—particularly those involving large language models and generative AI workflows.

The platform functions as a comprehensive DevOps stack for AI, featuring agent observability for insights into performance and behaviors, structured evaluation using both LLMs and human feedback for safety assurance, and ongoing improvement by converting production failures to test cases. It is equipped for enterprise-grade deployments and scalability, serving the needs of complex AI teams and Fortune 100 companies.

Basic Information

Contact Details

• Website: honeyhive.ai
• LinkedIn: linkedin.com/company/honeyhiveai
• Twitter: twitter.com/honeyhiveai

Key Focus Areas & Initiatives

• Software development
• AI system reliability
• Model evaluation
• AI failure detection
• AI model benchmarking
• AI system audit
• AI evaluation
• AI lifecycle management
• Model performance metrics
• AI pipeline visualization
• LLM failure detection
• Regression testing
• AI system health checks
• AI model fine-tuning datasets
• Online evaluation
• Automated testing
• Model debugging
• AI pipeline monitoring
• Semantic analysis of logs
• Data analytics
• AI monitoring
• Custom evaluator creation
• AI system compliance
• AI observability
• OpenTelemetry
• Cloud-native observability
• AI system observability
• Distributed tracing
• Performance dashboards
• OpenTelemetry integration
• RAG pipeline monitoring
• Dataset curation
• AI safety and moderation
• Automated alerts
• Prompt versioning
• AI debugging
• Version control prompts
• Model performance
• AI pipeline automation
• AI pipeline diagnostics
• Dataset management
• Regression analysis
• AI pipeline traceability
• Model testing
• Production log curating
• Trace analysis
• Error root cause analysis
• Performance analytics
• Collaborative workspace
• Collaborative prompt management
• Human review
• Evaluation metrics
• Data logging
• Multi-model support
• Cloud computing
• Performance monitoring
• Human-in-the-loop
• Model benchmarking
• Multi-tenant AI observability
• Regression detection
• AI and machine learning
• Prompt management
• Experiment tracking
• AI system metrics
• AI model versioning
• Dataset annotation
• Metrics and alerts
• AI model drift detection
• B2B
• Consulting
• Services
• Computer systems design and related services
• Enterprise software
• Enterprises
• Computer software

Technologies Used

• AI
• Amazon AWS
• Basis
• Circle
• Discord
• Domo
• Gmail
• Google Apps
• Google Font API
• Google Tag Manager
• Google Workspace
• Gusto
• IoT
• KNIME
• Mobile Friendly
• Python
• Remote
• Render
• Rippling
• Ruby On Rails
• SAP
• Sisense
• Snowflake
• Splunk
• ZoomInfo
• Zscaler
• reCAPTCHA

Affiliated Organizations & Regional Branches