HoneyHive

HoneyHive traces LLM/agent execution (spans, tool calls, multi-turn sessions) via OpenTelemetry-native Python and TypeScript SDKs, then layers evaluation on top: LLM-as-judge and code-based evaluators, human annotation queues, dataset curation from production traces, and CI/CD regression gating. It explicitly separates 'observe / evaluate / improve' as one workflow rather than three separate tools, and supports 50+ auto-instrumented libraries (LangChain, LangGraph, AWS Strands, Google ADK, OpenAI Agents SDK, etc.) per its pricing FAQ.

The free Developer tier is a real, usable tier (not a crippled trial): 10,000 events/month, up to 5 users, automated + human evaluations, prompt versioning, full observability suite, CI/CD integration and 30-day retention, all with no credit card (honeyhive.ai/pricing). The Python SDK is unusually actively maintained for a Series-A vendor's client library — PyPI shows releases roughly every 1-2 weeks over the past year, most recently 1.5.1 on 2026-07-23, spanning a full 0.x-to-1.0 rewrite with published migration guides (pypi.org/pypi/honeyhive/json). Security posture is documented in real detail rather than asserted: a public docs page breaks out encryption, network isolation, and a control-plane/data-plane separation with three concrete hosting tiers (multi-tenant SaaS, dedicated cloud, self-hosted), backed by a live Drata trust center for SOC 2 Type II, GDPR, and HIPAA (docs.honeyhive.ai/v2/setup/security). It also runs a real public status page with incident history (status.honeyhive.ai).

Only one price point is public: the $0 Developer tier described above. The only other listed plan is 'Enterprise' with 'Custom Pricing' for events, retention, requests/minute, users, workspaces, and hosting — every row in the plan-comparison table above the free tier reads 'Custom' (honeyhive.ai/pricing). There is no visible mid-tier (e.g., a $99 or $499/month 'Team' plan) for a company that outgrows the free 10,000 events but isn't ready for an enterprise procurement conversation. HoneyHive does offer a startup discount for companies with under $5M raised, but that's also gated behind contacting sales.

HoneyHive raised $7.4M total ($5.5M Seed led by Insight Partners plus a previously-unannounced $1.9M Pre-Seed led by Zero Prime Ventures), announced alongside its GA launch on 2025-04-08 (honeyhive.ai/post/honeyhive-raises-7-4m). It names Commonwealth Bank of Australia as a customer on its homepage, with vendor-stated figures of '17M retail consumers' and '55K internal users' served by agents built on the platform, plus a claim that CBA ranks #4 on the Evident AI Index — that ranking is independently confirmed for CBA in the 2025 Evident AI Index (commbank.com.au newsroom, October 2025), though the specific claim that HoneyHive is the observability layer behind CBA's production agents is the vendor's own framing and unverified beyond the homepage case study. HoneyHive also states it was named an 'emerging leader' in Gartner's 2026 Market Guide for AI Evaluation and Observability Platforms (a Market Guide is descriptive coverage, not a ranked/quadrant report).

HoneyHive's GitHub org has 16 repos, but none is the product itself: the Python SDK (3 stars, 3 forks) and TypeScript SDK/CLI (2-3 stars each) are MIT-licensed client libraries that talk to HoneyHive's hosted API; the 'cookbook' repo (3 stars) is examples, not the product. This is normal for a hosted SaaS and not a red flag, but a buyer evaluating HoneyHive as 'open source' would be wrong — the self-hosted option ships as a Helm-chart deployment of a closed platform, not something you can read on GitHub.

G2 and Capterra both blocked automated access (403/CAPTCHA) at time of writing, so no independent review-volume or rating figure could be confirmed for this listing. TrustRadius and similar review sites were not checked. The '340% agent accuracy improvement' and '5x faster development cycle' figures in HoneyHive's own funding announcement are customer-reported anecdotes in a company blog post, not independently audited benchmarks, and are not repeated here as fact.