Both trace agents, run experiments and score production traffic. Braintrust is built around the eval loop, with unlimited users on every plan and an analysis agent in the product; Logfire is built around the trace, putting model and tool calls in the same view as the rest of your application. Where your team spends most of its time, iterating on evals or debugging production, usually decides it.[1][4]
Braintrust is a hosted evaluation platform organised around experiments, while Logfire is Pydantic's OpenTelemetry observability platform that traces the whole application and adds evals, prompt versioning and an AI gateway. Both are proprietary platforms with open-source SDKs, and both companies are independent. Logfire's gateway can redact or block model calls; Braintrust's gateway, in public preview, routes and logs them.
| Decision factor | Braintrust | Logfire |
|---|---|---|
| Ownership | Independent; $80M Series B in February 2026 | Pydantic, independent; $12.5M Series A in 2024 |
| Centre of gravity | Experiments: dataset, task, scorers, compare | Traces across the whole application, then evals |
| Production scoring | Scoring rules run on logged production data | Evaluators run in your application in the background |
| Human review | Review scores, reviewer assignment, blind reviews | Run annotations in beta; queues in early access |
| Gateway | Public preview, free, no SLA; routing, caching and logging | Guardrails that flag, redact or block, plus spend caps |
| Self-hosting | Enterprise; data plane only, Braintrust runs the control plane | Enterprise; full platform on Kubernetes via Helm |
| Free tier | Starter: 1 GB processed data, 10K scores, 14-day retention | Personal: 10M records a month, 1 seat, 30-day retention |
| First paid tier | Pro: $249 a month, unlimited users | Team: $49 a month, 5 seats |
| Capability | Braintrust | 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 | Partial |
Braintrust's product starts from the experiment. You bring a dataset, define a task and scorers, run variants and compare, from the SDK, the CLI or the UI. Loop, its in-product agent, reads project data, writes scorers and runs evals, and since September 2026 Patterns group production behaviour for review; both are in public preview. Workflow evals that use provider batch APIs, which Braintrust promotes as roughly 50% cheaper per run, entered public preview in September 2026.
Logfire starts from tracing. Its SDKs are OpenTelemetry wrappers that record HTTP requests, database queries, logs and metrics as well as model and tool calls. Evals arrive through pydantic-evals: datasets defined in code or hosted in Logfire, experiments compared against a baseline, and runs on demand or in CI. A team whose hard problems sit in prompt and scorer iteration tends to lean Braintrust. A team whose agent bugs come from the systems around the model tends to lean Logfire.
Braintrust's online scoring rules run scorers asynchronously on logged production data, with sampling and filters, and record results as score spans. Scorers can be written in TypeScript or Python, pushed from the CLI or created in the UI. Logfire's live evaluations run inside your application through pydantic-evals, in the background at a sample rate you choose, and send results as OpenTelemetry events. Neither changes the output a user sees. The practical difference is where evaluator code lives: in Braintrust's platform, or in your own codebase and deployment.
Braintrust has the more complete review workflow: categorical, continuous or free-form review scores, assignment to reviewers, multiple and blind reviews, and required scores. Its free Starter plan allows one human review score per project. Logfire's run annotations, a Pass, Neutral or Fail verdict with comments and tags, are in beta, annotation queues are early access, and annotations do not feed experiment or live-eval aggregates.
Both vendors sell a gateway, and they are not equivalent. Braintrust Gateway is a unified API to OpenAI, Anthropic, Google, AWS and others with caching and logging. The hosted version is free, in public preview and has no SLA; it replaces Braintrust's deprecated AI proxy. Braintrust documents no blocking, guardrails or approvals: alerts, Patterns and behaviour specs judge traces after logging.
Logfire's gateway moved into Logfire in March 2026 and gained guardrails in July. Each rule can observe, flag, redact or block prompts and completions containing secrets, personal data or policy violations, and hard spend caps stop requests once a budget is used. It also handles failover and weighted load balancing. The limit is scope: it covers model calls routed through it, not an agent's tool actions.
Self-hosting is Enterprise only for both, with a real difference in what you run. Braintrust lets you host the data plane in AWS, GCP or Azure, but always operates the control plane, including the UI, authentication and metadata. Logfire's Enterprise self-hosted option runs the full platform on Kubernetes via Helm, with PostgreSQL 16 or later and object storage, and a dedicated single-tenant option in any GCP region is also offered.
As of 20 October 2026, Braintrust Starter is free with 1 GB of processed data, 10K scores and 14-day retention; Pro is $249 a month with 5 GB, 50K scores and 30-day retention, and every plan has unlimited users. Logfire Personal is free for 10M records and one seat; Team is $49 a month for five seats, with extra seats at $25; Growth is $249 a month with unlimited seats and up to 90-day retention. Extra records cost $2 per million. Braintrust meters data volume and scores, Logfire meters records, so model both against Braintrust'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 can act on what it finds through runtime policies, approval holds and a kill switch scoped to a run, an agent or a team. Braintrust documents no run-time controls; Logfire's gateway can block model calls but does not cover tool actions or approvals. Prefactor has no prompt playground or prompt registry and its platform is hosted, so if prompt iteration is the daily work, either of these is the better pick for it. 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.