honeyhive-ai

honeyhive-ai

HoneyHive is an AI-native observability and evaluation platform for production agents that unifies tracing, live and offline evaluation, monitoring, and human-in-the-loop review to help teams debug, test, and improve agent behavior at scale.

honeyhive-ai is ai agents software teams evaluate for ai agents. Use this page to review pricing, integration signals, and the best alternatives before you commit.

Free API
#450 in AI Agents (450 tools)
Added 0 year ago
Data reviewed Jul 16, 2026

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Quick Overview

Best for: AI Agents

What it does

AI Agents software for decision-makers comparing workflow fit and alternatives.

Best fit

AI Agents

Pricing snapshot

Free

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honeyhive-ai

HoneyHive provides an observability and evaluation layer specifically for production AI agents, unifying tracing, online and offline evaluation, monitoring, experiments, and human review into a continuous improvement loop. It is designed to instrument agents on any stack with OpenTelemetry, support 100+ LLMs and agent frameworks, and give teams a single source of truth to debug agent behavior, detect regressions, and route failures for human review. The platform targets enterprise-grade use with tenant-scoped isolation, compliance (SOC 2, GDPR, HIPAA BAA available), and deployment options including SaaS, hybrid, and self-hosted virtual data planes.

AI observability and evaluation platform for LLM applications.

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Key Features

OpenTelemetry-native Tracing

Instrument any agent on any stack with OpenTelemetry to capture traces and replay sessions, with graph and timeline views for debugging complex multi-agent systems.

Online Evaluation & Alerts

Continuously evaluate live traces using LLM-as-a-judge or custom code, detect failures and drift, and configure alerts and automations to surface issues before users are impacted.

Experiments & Offline Eval

Turn production failures into test suites, run offline experiments against datasets, compare changes to baselines, and detect regressions prior to release with CI/CD integration.

Annotation Queues & Human Review

Route flagged traces to domain experts, capture human review with custom rubrics and audit trails, and use feedback to align evaluators and curate datasets.

Tenant Isolation & Data Plane Architecture

Virtual data planes provide logical tenant isolation by default (with physical isolation available), keep sensitive payloads isolated per tenant, and support customer-owned CMKs and SIEM forwarding.

Developer Tooling & Integrations

Includes a full CLI, API access, MCP docs integration for IDEs, ready-made skills for coding agents, and Git-native dataset/versioning to automate workflows.

Pricing

Free Tier Available

Offers a free start (CTA on site: "Start for free").

Use Cases

Debugging and Root-Cause Analysis

Use distributed tracing, session replays, graph/timeline views, and AI-assisted root-cause tools to investigate agent failures and complex multi-agent interactions.

Production Monitoring & Drift Detection

Continuously monitor live traces and user feedback, detect drift and failure modes, and alert teams to regressions or production issues.

Safety & Regression Testing

Convert production failures into offline test suites and run experiments to compare new releases against baselines, integrating with CI/CD to catch regressions before deployment.

Human-in-the-Loop Quality Assurance

Route edge cases to domain experts for annotation with custom rubrics and maintain an audit trail to improve evaluator alignment and dataset curation.

Integrations

OpenTelemetry

Primary instrumentation standard — "OpenTelemetry-native" support to instrument agents across frameworks and stacks.

Identity Providers (SSO/SAML)

Integrates with Okta, Azure AD, Google, Ping for SSO, JIT provisioning, MFA enforcement, and session policies.

SIEM & Logging

Stream audit logs and metadata to Splunk, Datadog, or any SIEM; supports SIEM forwarding and audit logging.

GitHub / CI/CD

Git-native dataset/versioning and CI/CD integration to run automated test suites over every commit.

Developer Tools & MCP

MCP real-time doc search integration for IDEs and ready-made skills for coding agents (examples shown for Claude, Cursor, VS Code).

Benefits

Faster debugging and visibility into agent behavior via OpenTelemetry-native traces, session replays, and specialized graph/timeline views.
Continuous quality improvement by combining live evaluation, offline experiments, and automated regression detection.
Enterprise-grade data isolation, compliance, and access controls (tenant-scoped virtual data planes, SOC 2, GDPR, HIPAA options).

Limitations

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Frequently Asked Questions

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Getting Started

  1. 1 Step 1: Sign up on the HoneyHive site ("Start for free" or request a demo).
  2. 2 Step 2: Instrument your agent with OpenTelemetry to send traces to HoneyHive (or install HoneyHive tracing skills from the project repo).
  3. 3 Step 3: Use the honeyhive CLI or API to create metrics, configure evaluators, and set up dashboards, alerts, and annotation queues; integrate experiments into CI/CD.

Support

docs

Documentation and MCP docs available (https://docs.honeyhive.ai/).

demo

Product demos available via the site CTA ("Get a demo").

self-serve

Sign up and start for free using the web interface and use the honeyhive CLI and API for onboarding.

API

Available: Yes
Documentation:

API Reference and docs are available (https://docs.honeyhive.ai/).

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