HoneyHive

What is HoneyHive?

HoneyHive is a modern AI observability and evaluation platform designed to help enterprises confidently scale AI agents in production. It provides continuous evaluation and observability throughout the entire agent development lifecycle (ADLC), ensuring that AI agents are trustworthy and reliable by design.

Key Features of HoneyHive

Evaluation

• Experiments: Test AI agents offline against large datasets to systematically measure AI quality.
• Datasets: Centrally manage test cases with domain experts.
• Online Evaluation: Run live LLM-as-a-judge or custom code evaluations over logs.
• Annotation Queues: Allow domain experts to grade outputs.
• Regression Detection: Identify critical regressions as you iterate.
• CI Automation: Run automated test suites with every commit.

Observability

• OpenTelemetry-native: Ingest traces via OTEL SDKs for end-to-end visibility into AI agents.
• Session Replays: Replay chat sessions in the Playground for debugging.
• Filters and Groups: Quickly search and find trends in agent logs.
• Graph and Timeline View: Rich visualizations of agent steps for better understanding.
• Human Review: Allow domain experts to grade outputs for quality assurance.

Monitoring & Alerting

• Online Evaluation: Run async evaluations on traces in the cloud.
• User Feedback: Log and analyze issues reported by users.
• Dashboard: Get quick insights into the metrics that matter.
• Custom Charts: Build your own queries to track custom KPIs.
• Alerts and Drift Detection: Get real-time alerts over critical AI failures.

Artifact Management

• Prompts: Manage and version prompts in a collaborative IDE.
• Datasets: Curate datasets from traces in the UI.
• Evaluators: Manage, version, and test evaluators in the console.
• Version Management: Git-native versioning across files.
• Git Integration: Deploy prompt changes live from the UI.
• Playground: Experiment with new prompts and models.

How Does HoneyHive Work?

HoneyHive integrates seamlessly into the AI development lifecycle, providing tools and features that ensure the quality and reliability of AI agents. By leveraging OpenTelemetry-native tracing, HoneyHive offers end-to-end visibility into AI agents, allowing developers to debug issues faster and optimize performance.

Workflow

1. Evaluation: Systematically evaluate AI agents pre-deployment over large test suites to identify regressions before they affect users.
2. Observability: Get end-to-end visibility into agents across the enterprise and analyze underlying logs to debug issues faster.
3. Monitoring & Alerting: Continuously evaluate agents against 50+ pre-built evaluation metrics and get real-time alerts when agents fail in production.
4. Artifact Management: Collaborate with your team in UI or code to centrally manage prompts, tools, datasets, and evaluators.

Why Choose HoneyHive?

Enterprise-Grade Security

• SOC-2, GDPR, and HIPAA Compliant: HoneyHive meets the highest security standards to ensure your data is protected.
• Self-Hosting: Choose between multi-tenant SaaS, dedicated cloud, or self-hosting in VPC or on-prem.
• Granular Permissions: RBAC with fine-grained permissions across multi-tenant workspaces.

Trusted by Leading Companies

HoneyHive is trusted by Global Top 10 banks and Fortune 500 enterprises in production. It has helped numerous companies improve the capabilities of their AI agents and deploy them seamlessly to thousands of users.

Customer Testimonials

• Div Garg, Co-Founder: "It's critical to ensure quality and performance across our AI agents. With HoneyHive, we've not only improved the capabilities of our agents but also seamlessly deployed them to thousands of users — all while enjoying peace of mind."
• Rex Harris, Head of AI/ML: "For prompts, specifically, versioning and evaluation was the biggest pain for our cross-functional team in the early days. Manual processes using Gdocs - not ideal. Then I found @honeyhiveai in the @mlopscommunity slack and we’ve never looked back."
• Cristian Pinto, CTO: "HoneyHive solved our biggest headache: monitoring RAG pipelines for personalized e-commerce. Before, we struggled to pinpoint issues and understand pipeline behavior. Now we can debug issues instantly, making our product more reliable than ever."

Who is HoneyHive For?

HoneyHive is ideal for:

• Enterprises: Looking to scale AI agents across their organization with confidence.
• AI Developers: Needing tools to evaluate, debug, and monitor AI agents effectively.
• Data Scientists: Requiring robust datasets and evaluation metrics for AI model training.
• DevOps Teams: Seeking seamless integration with CI/CD pipelines for automated testing.
• Domain Experts: Needing to collaborate on AI agent development and evaluation.

Best Way to Scale AI Agents

HoneyHive provides a comprehensive platform for scaling AI agents with confidence. By offering continuous evaluation, observability, and monitoring, HoneyHive ensures that AI agents are trustworthy and reliable by design. Whether you're just getting started or scaling agents across your enterprise, HoneyHive is the single platform you need to observe, evaluate, and improve your AI agents.

Conclusion

HoneyHive is a powerful AI observability and evaluation platform that helps enterprises scale AI agents with confidence. With its comprehensive features for evaluation, observability, monitoring, and artifact management, HoneyHive ensures that AI agents are trustworthy and reliable. Trusted by leading companies and compliant with the highest security standards, HoneyHive is the ideal choice for enterprises looking to deploy AI agents at scale.