HoneyHive

What is HoneyHive?

HoneyHive is an AI observability and evaluation platform built for teams that deploy LLM agents in production. It provides distributed tracing, online evaluations, session replays, and monitoring across 100+ LLMs and agent frameworks through native OpenTelemetry integration. Teams use it to track cost, latency, quality, and failures across their AI workflows, then run experiments and evaluations to improve reliability before and after shipping. HoneyHive is aimed at engineering and product teams that need visibility into multi-agent systems, particularly in finance, enterprise SaaS, and developer tooling.

Key Features

• Distributed Tracing: Traces end-to-end AI workflows across 100+ LLMs and agent frameworks using OpenTelemetry. Includes graph and timeline views, session replays, filters, groups, and user feedback capture for inspecting complex multi-agent systems.
• Online Evaluation: Runs live evaluations on production traffic to detect failures in quality, safety, and performance. Monitors latency and cost metrics alongside quality scores, catching silent failures in real time.
• Experiments and Regression Testing: Tests agents offline against large datasets, compares workflows side by side, and detects regressions before releases with CI/CD integration. Production failures can be turned into test cases for future runs.
• Custom Evaluators: Supports LLM-as-a-judge and code-based evaluators, plus human review fields for grading outputs. Teams can define business-specific criteria beyond generic metrics.
• Annotation Queues: Routes flagged traces to reviewers with queue automation, custom rubrics, and audit trails. Curates datasets from human feedback and aligns LLM evaluators with domain expert input.
• Prompt Studio: A collaborative workspace for managing, versioning, and editing prompt templates, model variants, and functions. Supports live collaboration, access to 100+ models, and 1-click deployment via proxy endpoint.
• Alerts and Drift Detection: Sends real-time alerts for agent failures, drift, and key issues based on custom thresholds, so teams can respond to production anomalies without constant manual monitoring.
• Custom Dashboards: Builds and saves custom charts for cost, latency, quality, and business KPIs. Supports slicing data across dimensions for quick insights tailored to each team's needs.

Use Cases

• Debugging Multi-Agent Production Failures: An engineering team building web-browsing agents used HoneyHive evaluations to identify edge cases and accuracy issues during development. Over a few months of iterating on prompts and logic based on eval results, they improved agent accuracy on their target tasks by 340%.
• Scaling AI Across Business Units: A senior engineer at a financial services company integrated HoneyHive evals into development pipelines across multiple business units. By running pre-production offline evaluations and monitoring production traces with OpenTelemetry, the team accelerated their development cycle by 5x.
• Continuous Quality Monitoring: Teams running LLM agents in production use HoneyHive to track quality scores alongside latency and cost. Online evaluations flag degradation in real time, and dashboards give product managers visibility into agent behavior without deep coding.

Strengths and Weaknesses

Strengths:

• OpenTelemetry-native tracing works across 100+ LLMs and frameworks without vendor lock-in
• Combines observability and evaluation in a single platform, covering the full agent development lifecycle
• The Python SDK gets positive feedback for being lightweight and quick to integrate
• Free tier includes the full observability and evaluation suite, not a stripped-down version
• Collaborative features like annotation queues and prompt studio bring domain experts into the loop alongside engineers

Weaknesses:

• Community presence is thin, with no active Discord, Slack, or forum for peer support
• Free tier is limited to 10,000 events per month and 30-day data retention, which can be restrictive during heavy testing
• Documentation covers core features well but is sparse on advanced integrations and edge cases
• Error messages for dataset uploads can be vague, and eval schema changes have occasionally broken workflows without clear migration guides

Pricing

• Developer (Free): $0 forever. Full observability and evaluation suite including distributed tracing, alerts, custom dashboards, experiments, CI/CD integration, prompt studio, and annotation queues. Limited to 10,000 events per month, 30-day data retention, 1,000 max requests per minute, and up to 5 users. Email support. No credit card required.
• Enterprise: Contact sales. Adds advanced security (SSO with Okta, Azure AD, Google Workspace), extended data retention, higher event limits, and dedicated support. SOC 2 Type II certified, HIPAA compliant with BAA available, GDPR compliant.

HoneyHive also offers a startup discount program.

FAQ

How does HoneyHive integrate with existing LLM frameworks?

HoneyHive is OpenTelemetry-native and works with 100+ LLMs and agent frameworks for unified tracing. It provides SDKs for Python and TypeScript to upload data, manage prompts and models, and run evaluations. CI/CD integration connects experiments directly to your deployment pipeline.

How long does it take to get started with HoneyHive?

Sign up for free (email only, no credit card), create a project, install the SDK, set your API key and project name, and initialize the tracer. Developers report getting their first eval pipeline running in 15 to 30 minutes.

How does HoneyHive compare to LangSmith?

Both platforms cover AI observability and evaluation, but HoneyHive differentiates with OpenTelemetry-native support across all frameworks (not just LangChain), agent-specific features like multi-agent graph views and session replays, and collaborative dataset management for domain experts. HoneyHive emphasizes full agent development lifecycle coverage with UI-managed prompts and CI/CD integration.

Does HoneyHive support self-hosting?

Self-hosting or on-premise deployment is not documented. HoneyHive runs as a cloud-based platform with multi-tenant SaaS hosting on AWS US-West-2. Enterprise customers should contact sales for data residency options.

What security certifications does HoneyHive have?

HoneyHive holds SOC 2 Type II certification, is HIPAA compliant with BAA available, and meets GDPR requirements. It supports encryption at rest with AWS KMS (customer-managed keys), TLS 1.2+ in transit, RBAC, and SSO via Okta, Azure AD, Google Workspace, OneLogin, and custom SAML providers.