Modern AI Observability and Evaluation

One platform for every team in your organization to observe, evaluate, and govern AI agents in production.

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Partnering with leading firms.
From AI startups to Fortune 100 enterprises.

Distributed Tracing

See inside any agent, any framework, anywhere

Trace 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 & Alerts

Continuously monitor agent failures at scale

Run 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.

Experiments

Confidently ship changes with automated evals

Turn 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 Queues

Shape agent quality with expert feedback

Bring 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.

Enterprise-grade security

SOC 2 Type II certified. GDPR and HIPAA compliant. SSO, SAML, RBAC, and self-hosting available.

Trust Center ↗

SOC-2, GDPR, and HIPAA compliant

SOC-2 Type II, GDPR, and HIPAA compliant to meet your security needs.

Hybrid or Self-hosted

Choose between multi-tenant SaaS, single-tenant SaaS, hybrid SaaS, or full self-hosting.

Fine-grained RBAC

Project & workspace isolation, SAML/SSO, custom permission groups.

Trusted by Fortune 500 enterprises.

Powering AI observability at Australia's largest bank

HoneyHive powers observability, evaluation, and governance across mission-critical AI systems at CBA, enabling safe and responsible use of AI agents serving 17M+ consumers.