Scale AI across your organization without losing control.
100+
LLM models & frameworks supported
Fortune 500
regulated clients across industries
~1 ms
observability overhead in production
10k+
requests per second supported
AI agents are powerful. Trust is the hard part.
Agents can execute successfully and still take the wrong path, use the wrong tool, or produce the wrong outcome. HoneyHive makes their behavior visible and continuously measurable across the enterprise.
See what every agent actually does.
Understand behavior across teams, models, vendors, and environments—from one place.
Know when quality changes.
Evaluate live traffic, detect regressions, and surface emerging risk before isolated failures become systemic.
Prove every agent meets the standard.
Define what good looks like, measure against it continuously, and apply the same expectations across every agent.
Scaling AI means scaling uncertainty.
Agents pass tests and still fail in production
Quality drifts without triggering traditional errors
Problems surface through users, not monitors
Every team defines quality differently
Risk teams lack evidence that controls are working
Every agent, observed and evaluated.
Complete trajectories across prompts, tools, and handoffs
Continuous evaluation of live production outcomes
Regression detection before and after every change
Production failures turned into regression datasets
Shared evaluations and monitors applied by default
Make reliability the default.
Give every team self-serve observability and evaluation, with the shared tooling, standards, and workflows to build and operate production agents across the enterprise.
Org-wide Policies
Define evaluation and monitoring standards once and apply them consistently across every agent you trace in HoneyHive.
Agent Skills
Give developers reusable agent skills to instrument applications, set up evaluations, investigate failures, and more using coding agents.
CLI and Config-as-Code
Manage evaluators, datasets, prompts, and alerts as code—version them in Git, automate workflows in CI, and make them accessible to coding agents.
Granular RBAC
Isolate teams and define custom roles across dozens of fine-grained permissions, scoped to organization, workspace, or project.
Data Exports
Export traces, evaluations, and metrics to your warehouse, lakehouse, or streaming platform in open formats.
One source of truth for everyone building agents.
HoneyHive is designed for the full cross-functional team: from the engineer instrumenting the first agent to the risk officer signing off the last deployment.
Set the foundation.
Give every team a proven way to instrument, evaluate, and operate agents across frameworks, clouds, and business units.
Debug, evaluate, ship.
Debug complete trajectories, test changes on real production cases, and catch regressions before customers do.
Turn expertise into evaluation.
Review real outputs, define rubrics, and make expert judgment reusable across every agent and release.
Produce audit-ready evidence.
See traces, evaluation results, and human reviews in one defensible record for internal and regulatory review.
Your data stays under your control
Agent traces carry rich, highly sensitive I/O that traditional observability can’t handle. HoneyHive is designed specifically for AI traces and centralizes visibility without centralizing sensitive data, keeping every deployment isolated by design.
Fully managed SaaS. Isolated by default.
HoneyHive operates both planes, with a virtual data plane isolated for each tenant.
Sensitive data never leaves your environment.
Store traces and run evals in your cloud. HoneyHive manages the rest.
Fully self-hosted. Nothing leaves your network.
Both planes run in your infrastructure, deployed and managed through Kubernetes.
The same controls, every deployment
Define custom roles across dozens of fine-grained permissions, scoped from organization down to project.
Audited to SOC 2 Type II. GDPR-compliant with EU data residency. HIPAA BAA available for healthcare.
Okta, Azure AD, Google, PingSSO. JIT provisioning, enforced MFA, and session policies managed by your IdP.
Stream audit logs to Splunk, Datadog, or any SIEM. Every access, change, and export is auditable upstream.