Both trace agents, run experiments and score sampled production traffic. HoneyHive goes further on review and monitoring, with annotation queues, alerts and a fully self-hosted option on Enterprise; Logfire goes further on the surrounding application and adds a gateway, with self-serve plans from $49 a month. Whether you are ready for a sales process often decides it.[1][4]
HoneyHive is a hosted agent observability and evaluation platform with server-side online evals, annotation queues and monitoring, while Logfire is Pydantic's OpenTelemetry platform that traces the whole application and adds evals, prompt versioning and an AI gateway. Both are built on OpenTelemetry and both companies are independent. HoneyHive offers a free tier and then a sales conversation; Logfire publishes self-serve paid plans.
| Decision factor | HoneyHive | Logfire |
|---|---|---|
| Ownership | Independent; $7.4M raised, last announced April 2025 | Pydantic, independent; $12.5M Series A in 2024 |
| Production evals | LLM, code and human evaluators on sampled production traces | Evaluators run in your application in the background |
| Human review | Annotation queues with automations | Run annotations in beta; queues in early access |
| Gateway | None for application traffic; integrates with LiteLLM, Portkey and others | Yes, with guardrails and spend caps on model calls |
| Tracing SDKs | Python tracer; TypeScript REST client; OTLP for others | Python, JavaScript/TypeScript, Rust; any OTel SDK |
| Self-hosting | Enterprise: fully self-hosted or hybrid, documented on AWS | Enterprise: Kubernetes via Helm |
| Free tier | Developer: 10,000 events a month, up to 5 users | Personal: 10M records a month, 1 seat |
| Paid plans | Enterprise only, quote-based | Team $49 a month; Growth $249 a month |
| Capability | HoneyHive | Logfire | Prefactor |
|---|---|---|---|
| Observe | |||
| LLM call tracing | ✓ | ✓ | ✓ |
| Multi-step agent tracing (tool calls, nested spans) | ✓ | ✓ | ✓ |
| Cost tracking | ✓ | ✓ | ✓ |
| OpenTelemetry support | ✓ | ✓ | ✓ |
| Evaluate | |||
| Offline evals (datasets, experiments) | ✓ | ✓ | ✓ |
| Online evals on production traffic | ✓ | ✓ | ✓ |
| LLM-as-a-judge scoring | ✓ | ✓ | ✓ |
| Code-based evaluators | ✓ | ✓ | ✓ |
| Human review and annotation | ✓ | Partial | ✓ |
| Prompt versioning and playground | ✓ | ✓ | — |
| Act on findings | |||
| Runtime controls on live agent actions | — | Partial | ✓ |
| Gateway or proxy in the request path | — | ✓ | — |
| Licence and deployment | |||
| Open source | Partial | Partial | Partial |
| Self-hosting | ✓ | Partial | Partial |
HoneyHive is built for looking at agents. It offers traces, agent graphs, trajectories, threads, a timeline and, since September 2026, a conversation view for multi-step and multi-agent runs. Its integration list is broad on the agent side: LangGraph, CrewAI, OpenAI Agents SDK, Claude Agent SDK, Google ADK, and since August 2026 Salesforce Agentforce and Databricks Agent Bricks. Since June 2026 it also traces coding agents such as Claude Code, Codex CLI and Devin, with usage and spend analysis.
Logfire is built for looking at the application an agent runs inside. Its SDKs are OpenTelemetry wrappers that record HTTP requests, database queries, logs and metrics in the same trace as model and tool calls, with dedicated Agents and LLMs views on top. Its MCP server lets coding agents query production traces, which is a different job from tracing the coding agent itself. Both accept OTLP and read common GenAI conventions, so instrumentation can move between them.
SDK coverage differs. HoneyHive's full tracing SDK is Python; its TypeScript package is a REST API client rather than an auto-instrumenting tracer, so TypeScript teams can send OTLP instead. Logfire has SDKs for Python, JavaScript and TypeScript, and Rust, and accepts data from any OpenTelemetry SDK.
HoneyHive runs online evaluations on its side against sampled production traces, with LLM evaluators, server-side Python code evaluators and human evaluator fields; the default sample rate was lowered to 10% in May 2026. Flagged traces route to annotation queues, which gained automations in April 2026, and alerts work on self-hosted deployments since March 2026. Experiments can gate CI runs on regressions through GitHub Actions. HoneyHive's Policies feature sets organisation-wide evaluation and monitoring standards; it does not enforce anything at run time.
Logfire's live evaluations run inside your application through pydantic-evals, in the background at a sample rate, and report as OpenTelemetry events. They do not alter outputs. Human review is earlier: run annotations are in beta and annotation queues are early access. If several domain experts need to review traces each week, HoneyHive is further along today.
Prompt work is closer to even. HoneyHive has a playground and prompt versioning, and deployed prompts are fetched by name or version from its Python SDK or TypeScript client. Logfire keeps immutable prompt versions, promotes them through labels with rollout targeting, and its Prompt Playground replays prompts taken from captured traces.
HoneyHive has no gateway for application traffic and documents no blocking, guardrails or approvals; guardrail results from your own code can be logged as custom metrics. In Microsoft's ASSERT and Agent Control Specification announcement in June 2026, HoneyHive is described as the observability layer while the specification handles enforcement. Logfire's gateway, part of Logfire since March 2026, can observe, flag, redact or block model calls and enforce spend caps, though only for traffic routed through it and not for tool actions.
As of 20 October 2026, HoneyHive's Developer tier is free with no card: 10,000 events a month, 30-day retention, up to five users and one workspace, on multi-tenant SaaS in AWS us-west-2. There is no published self-serve paid plan; anything larger is Enterprise and quote-based, which includes single-tenant, hybrid and fully self-hosted deployment on AWS. Logfire Personal is free for 10M records and one seat, Team is $49 a month for five seats, Growth is $249 a month with unlimited seats, and extra records cost $2 per million. Logfire self-hosting is also Enterprise only, on Kubernetes via Helm. For cost attribution, HoneyHive added workspaces with their own provider keys in January 2026 and usage reports by workspace and project in July.
HoneyHive is a small company, about 18 to 19 staff according to third-party directories, whose last announced funding was in April 2025. See HoneyHive's pricing and Logfire's pricing.
We sell the layer this section describes. Read it with that in mind.
Stated plainly, since Prefactor publishes this page: Prefactor is an agent evaluation platform that scores each step of a run and acts on what it finds through runtime policies on tool calls and data access, approval holds for risky actions and a kill switch for a run, an agent or a team. HoneyHive observes and scores without enforcing, and Logfire's gateway covers model calls only. Prefactor has no prompt playground or prompt registry and its platform is hosted, so if prompt iteration or a fully self-hosted deployment is the requirement, one of these two fits better. See the full comparison of 15 platforms.
Reviewed against public product and documentation pages on October 20, 2026. If a vendor has changed a feature, product name, or positioning since then, send a correction and we will update it. Numbered source links in the page body point to the ordered sources below.
Prefactor scores each step of every agent run and can hold or stop an action when a score says it should not happen. Start on the free tier: 5,000 spans a month, no credit card required.
Prefactor helps teams observe, evaluate, and improve their AI agents in production, across every framework and provider.