honeyhive.ai

New 2025: Year in ReviewModern AI Observability and EvaluationOne platform for every team in your organization to observe, evaluate, and govern AI agents in production.Start for freeGet a demoTracesAgentsExperimentsMonitorsAlertsEvaluatorsPlaygroundAnnotationsPartnering with leading firms. From AI startups to Fortune 100 enterprises.Distributed TracingSee inside any agent, any framework, anywhereTrace end-to-end AI workflows so teams can debug failures, understand execution paths, and standardize telemetry across every application.OpenTelemetry-native. Works across 100+ LLMs & agent frameworks.Online Evaluation. Run live evals to detect failures across agents.Session Replays. Replay chat sessions in the Playground.Filters and Groups. Quickly search across millions of traces and find outliers.Graph and Timeline View. Debug complex multi-agent systems.User Feedback. Capture implicit and explicit signals from your users.Monitoring & AlertsContinuously monitor agent failures at scaleRun online evals on live traffic, track quality alongside latency and cost, and alert on the failure modes that matter to your business.Online Evaluation. Detect issues across quality, safety, and more at scale.Alerts and Drift Detection. Get real-time alerts when your agent silently fails.Automations. Add failing prompts to datasets or trigger human review.Custom Dashboard. Get quick insights into the metrics that matter.Rich Analytics. Slice and dice your data to track custom KPIs.Annotation Queues. Surface failures to domain experts for manual review.ExperimentsConfidently ship changes with automated evalsTurn production traces into test cases, compare agents and workflows side-by-side, and catch regressions before every release.Experiments. Test your agents offline against large datasets.Datasets. Centrally manage test cases with domain experts.Custom Evaluators. Write your own LLM-as-a-judge or code evaluators.Human Review. Allow domain experts to grade outputs.Regression Detection. Identify critical regressions as you iterate.CI/CD Integration. Run automated test suites over every commit.Annotation QueuesShape agent quality with expert feedbackBring subject matter experts into the loop to review edge cases, define quality, and align your evals with real-world business context.Queue Automation. Route flagged traces to the right reviewers.Human Review. Bring domain experts into the loop in a friendly interface.Custom Rubrics. Standardize review with business-specific criteria.Dataset Curation. Git-native versioning across artifacts.Audit Trail. Capture expert feedback alongside trace context.Evaluator Alignment. Use feedback to align LLM evaluators with SMEs.OpenTelemetry-nativeOpen standards, open ecosystemEnterprise-grade securitySOC 2 Type II certified. GDPR and HIPAA compliant. SSO, SAML, RBAC, and self-hosting available.Trust Center  ↗ SOC-2, GDPR, and HIPAA compliantSOC-2 Type II, GDPR, and HIPAA compliant to meet your security needs.Hybrid or Self-hostedChoose between multi-tenant SaaS, single-tenant SaaS, hybrid SaaS, or full self-hosting.Fine-grained RBACProject & workspace isolation, SAML/SSO, custom permission groups.Trusted by Fortune 500 enterprises.Powering AI observability at Australia's largest bankHoneyHive powers observability, evaluation, and governance across mission-critical AI systems at CBA, enabling safe and responsible use of AI agents serving 17M+ consumers.Start your AI observability journeyStart for free --- Get started todayStart building for free. Upgrade for higher usage limits, dedicated support, and enterprise-grade hosting options.DeveloperFreeNo credit card requiredGet started10K events per monthUp to 5 usersSingle workspace30d data retentionFull observability and evaluation suiteEnterpriseLet's chatIdeal for large organizationsBook a demoCustom usage limitsUnlimited users and workspacesChoose between SaaS, hybrid, or self-hostingCustom SSO & SAMLDedicated support, SLA, and team trainingsPopularUsage LimitsDeveloperenterpriseNumber of Events per month10,000CustomData Retention30dCustomMax Requests per Minute1,000CustomObservabilityDeveloperEnterpriseDistributed TracingAlerts & Drift DetectionCustom DashboardsDataset CurationAnnotation QueuesData ExportEvalsDeveloperEnterpriseOnline Evaluation w/ samplingExperiments and Regression TrackingCI/CD IntegrationPrompt StudioDeveloperEnterprisePlaygroundPrompt Versioning and HistoryFunctions and External ToolsPrompt DeploymentsCustom Model ProvidersWorkspaceDeveloperEnterpriseNumber of UsersUp to 5UnlimitedNumber of Workspaces1 WorkspaceUnlimitedNumber of Projects per WorkspaceUnlimitedUnlimitedSecurityDeveloperEnterpriseSSO (social)SAML and Custom SSOBasic RBACCustom Roles and Permission GroupsHosting OptionsMulti-Tenant SaaSMulti-Tenant SaaS, Single-Tenant SaaS, Hybrid SaaS, or Self-HostedData ResidencyAWS US-West-2CustomData BoundariesLogical SeparationUp to Physical SeparationCustom Data Retention PolicyPII ScrubbingInfoSec ReviewCustom DPAHIPAA Compliance and BAASupportDeveloperEnterpriseCommunity SupportEmail SupportSlack/Teams Connect ChannelUptime and Support SLACSM and Team TrainingsTrusted by Fortune 500 enterprises.Powering AI observability at Australia's largest bankHoneyHive powers observability, evaluation, and governance across mission-critical AI systems at CBA, enabling safe and responsible use of AI agents serving 17M+ consumers.Frequently asked questionsWhat is an event?An event refers to a single trace span or metric-label combination sent to our API as OTLP or JSON. It captures any relevant data from your system, including all context fields generated by your application's instrumentation. In simple terms:-Number of Events = Number of Trace Spans + Number of MetricsWhat types of evaluations are supported?HoneyHive supports 2 primary types of evaluations:‍Automated EvaluationsThese are functions—either code-based or using LLM-as-a-judge—that automatically score your sessions, agents, or spans. They generate measurable scores and provide explanations for their assessments. Common examples include Context Relevance, Answer Faithfulness, ROUGE-L, Tool Use Accuracy, etc. HoneyHive provides dozens of standard evaluators out-of-the-box, and you can also define custom evaluators tailored to your specific needs.‍Human EvaluatorsWe strongly recommend a hybrid evaluation approach that combines automation with human oversight. This helps you account for evaluator bias and ensures alignment with your domain experts' standards. HoneyHive lets you create custom scoring rubrics and annotation queues that domain experts can use to manually grade outputs, ensuring your metrics truly reflect what matters for your use case.How does HoneyHive secure my data? All data is secure and encrypted at rest and in transit. We are SOC-2 Type II, GDPR, and HIPAA compliant, conduct regular penetration tests via 3rd-party auditors, and provide flexible hosting solutions, including self-hosting, to meet your security and compliance needs. Learn more about our platform architecture here.Can I self-host HoneyHIve?Yes, you can self-host HoneyHive on the Enterprise plan. We support self-hosting across AWS, Azure, and Google Cloud via Kubernetes, and can provide additional support for on-premise deployments. Contact us to learn more.How do I integrate my application? You can log traces using our SDKs, or async using our batch ingestion APIs. We offer SDKs in Python and Typescript with native OpenTelemetry support, and provide automatic instrumentation for 50+ popular libraries like LangChain, LangGraph, AWS Strands, Google ADK, and OpenAI Agents SDK, among others.For users using other languages, you can send your OpenTelemetry traces to our OTEL collector or manually instrument your application using our APIs.Do you offer startup discounts?Yes, we do offer startup discounts for companies with less than $5M of total funding raised. Contact us to learn more.Start your AI observability journeyStart for free --- Powerful observability, purpose-built for AI agentsTrace and monitor AI agents in production to detect anomalies, debug issues, and drive continuous improvement.Get startedRead the docs  ↗ MonitoringThe path to improving your agents starts with observing them.Online evaluationsCompute safety, quality, and performance metrics across your data to detect agent failures in production.User feedback & actionsCapture user feedback to track performance and user experience across your AI applications.Agent graphsVisualize complex agentic workflows as DAGs to understand and debug critical error cascades.Custom DashboardSave custom charts to your team workspace for quick access to insights that matter to you the most.Filters and groupsSlice and dice your data across segments and get detailed insights into application performance.OpenTelemetry-nativeLog application data synchronously and asynchronously, using our OpenTelemetry-native SDK.Monitor cost, latency, and quality at scaleAgents are non-deterministic and lead to unexpected failures in production. HoneyHive allows you to monitor agents with quantitative rigor and get actionable insights to continuously improve your app.Trace AI agents with just a few lines of codeContinuously evaluate live traces and capture user feedback.Create custom queries and monitor key metrics at scaleDebug and improve your agents with tracesAgents fail due to issues in either the prompt, model, or your data retrieval pipeline. With full visibility into the entire chain of events, you can quickly pinpoint errors and iterate with confidence.Debug chains, agents, tools and RAG pipelinesRoot cause errors with AI-assisted RCAIntegrates with leading orchestration frameworksRun online evaluations to catch LLM failures as they happenRun online evaluators on your live production data to catch LLM failures automatically.Evaluate faithfulness and context relevance across RAG pipelinesWrite assertions to validate JSON structures or SQL schemasImplement moderation filters to detect PII leakage and unsafe responsesCatch agentic failures like tool misuse or loopingCalculate NLP metrics such as ROUGE-L or Edit DistanceGet alerts when your agents fail in productionHoneyHive enables you to set up targeted alerts on any schema property to track critical incidents, and run automations to triage and root-cause issues.Get alerts on cost, latency, accuracy, or guardrail violationsEscalate failing traces to domain experts for human reviewCurate datasets from failing traces for future evaluations and resolutionsGet started with 3-lines of codeOpenTelemetry native. Our tracers use OTLP protocol, allowing seamless interoperability across your DevOps stack.SDKs and APIs. Allow you to deeply integrate with your application logic and build custom automations using your logs.Auto-instrumentation. Our tracers automatically instrument popular model providers and tools like OpenAI, Anthropic, Pinecone, and more.Get startedRead the docs  ↗ Trusted by Fortune 500 enterprises.Powering AI observability at Australia's largest bankHoneyHive powers observability, evaluation, and governance across mission-critical AI systems at CBA, enabling safe and responsible use of AI agents serving 17M+ consumers.Start your AI observability journeyGet started --- Run automated evaluations to ship with confidenceEvaluate AI agents & application to measure performance, catch regressions, simulate tricky scenarios, and ship to production with confidence.Get startedRead the docs  ↗ EvaluationContinuous testing and evaluation for your AI agentsCode, AI, and Human EvaluatorsDefine your own code or LLM evaluators to automatically test your AI pipelines against your custom criteria, or define human evaluation fields to manually grade outputs.Continuous IntegrationEvaluation runs can be logged programmatically and integrated into your CI/CD workflows via our SDK, allowing you to check for regressions.Distributed TracingGet detailed visibility into your entire LLM pipeline across your run, helping you pinpoint sources of regressions in your pipeline as you run experiments.Evaluation ReportsSave, version, and compare evaluation runs to create a single source of truth for all experiments and artifacts, accessible to your entire team.Dataset ManagementCapture underperforming test cases from production and add corrections to curate golden datasets for continuous testing.Optimized InfrastructureWe automatically parallelize requests and metric computation to speed up large evaluation runs spanning thousands of test cases.Benchmark performance and spot regressions quicklyHoneyHive enables you to test AI applications just like you test traditional software, eliminating guesswork and manual effort.Evaluate prompts, agents, etc. against datasetsScale human annotations with queues and custom criteriaCompare experiments and spot regressions in CIDebug what actually went wrong with tracesAgents fail due to due to cascading failures across tool calls, reasoning steps, and more. With full visibility into the entire sequence of actions, you can quickly pinpoint errors and iterate with confidence.Debug agents with distributed traces across complex agentic systemsUnderstand agent structure and critical paths with graphsOpenTelemetry-native, integrates with leading frameworksCurate datasets for every scenarioHoneyHive enables you to filter and label underperforming data from production to curate "golden" evaluation datasets to test and evaluate your application.Curate datasets from production, or synthetically generate using AIInvite domain experts to annotate and provide ground truth labelsManage and version evaluation datasets across your projectUse our pre-built evaluators to test your applicationContext RelevanceContext PrecisionAnswer RelevanceAnswer FaithfulnessIntent RecognitionToxicityTool Misuse20+ moreBuild custom evaluators for your unique use-caseEvery use-case is unique. HoneyHive allows you to build your own LLM evaluators and validate them within the evaluator console.Test faithfulness and context relevance across RAG pipelinesWrite assertions to validate JSON structures or find keywordsImplement custom moderation filters to detect unsafe responsesUse LLMs to critique agent trajectory over multiple stepsSet up evals with just a few lines of codeOpenTelemetry-native. Automatically trace LLM requests and agent frameworks using OpenTelemetry.Continuous integration. Integrate HoneyHive into your existing CI workflow using GitHub Actions.Flexible. Use pre-built evaluators, define your own, or use any 3rd-party evaluators.Get startedRead the docs  ↗ Trusted by Fortune 500 enterprises.Powering AI observability at Australia's largest bankHoneyHive powers observability, evaluation, and governance across mission-critical AI systems at CBA, enabling safe and responsible use of AI agents serving 17M+ consumers.Ship AI agents with confidenceGet started