Observability & traceability
HoneyHive
Agent observability and evaluation platform aimed at enterprises running production agents. Distributed tracing captures every step including tool calls, prompts, retries, loops and handoffs between sub-agents across long trajectories, with step-by-step replay, online evals on live traffic and annotation queues that turn expert review into datasets.
commercial · generally available · Research snapshot 2026-09-06
Visit the official product source ↗Where it fits
Observability & traceability · Evaluation & testing
Useful conversation with: AI platform lead, Risk and governance manager, AI engineer.
Ask for a demonstration
Replay a multi-day agent trajectory step by step, showing every tool call and sub-agent handoff plus the evaluation scores attached to it.
Capabilities and evidence
Support labels reflect the supplied research. Documentation and vendor claims are not independent product tests. “Not established” means the researcher did not find support; it does not prove a capability is absent.
Documented by provider
HoneyHive documents distributed tracing that captures every interaction and every step of an AI application, with agent graphs and threads, curated datasets from failing production traces, experiments to track regressions, annotation queues for expert feedback, and online evals on production traces.
Limit: The docs introduction does not itemise span kinds, cost or token telemetry, retention or access controls.
Source s1
Vendor claim
The product page states runs can be replayed step by step showing every tool call, prompt and decision in order, trajectories can span hours or days, and captured behaviour includes retries, loops and handoffs between sub-agents, including agents inside ServiceNow, Microsoft Copilot and Salesforce.
Limit: Marketing page; instrumentation method for third-party platforms and the fidelity of replay are not documented in reference material.
Source s2
Vendor claim
The product page states HoneyHive powers observability and evaluation across dozens of mission-critical AI applications at Commonwealth Bank of Australia, serving agents used by 17M retail consumers and 55K internal users.
Limit: Customer scale figures are vendor-stated and not independently corroborated.
Source s2
Limitations to discuss
- No audit log, retention, RBAC or PII-redaction evidence: the security documentation page could not be retrieved.
- Governance framing is addressed at the buyer level (risk and governance teams named) rather than through documented controls.
Sources
- What is HoneyHive? · HoneyHive · official docs
Access date reported by researcher: 2026-09-06 - HoneyHive AI · HoneyHive · official product
Access date reported by researcher: 2026-09-06
Listing does not imply partnership, supplier status, a working DutyGraph integration, or a compliance certification.
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