AI Tool
Pydantic Logfire pricing, features, company info, and alternatives
A factual product page for Pydantic Logfire.
Last updated April 2026 · Pricing and features verified against official documentation
Pricing
Current public pricing tiers on file for Pydantic Logfire, last verified Apr 26, 2026.
Personal
$0 / month
No card required; includes 10M logs/spans/metrics, 1 seat, 3 projects, 2 guests, 30-day retention, and EU or US data region selection.
Team
$49 / month
Includes 5 seats, 10 guests, 5 projects, 10M logs/spans/metrics, $25 per extra seat, price cap, and 30-day retention.
Growth
$249 / month
Includes unlimited seats, guests, and projects, 10M logs/spans/metrics, price cap, self-service data deletion, BAA support, and 30-day retention.
Enterprise
Custom
Includes cloud or self-hosted deployment, 100M logs/spans/metrics, custom retention, SSO, SLA, and invoice billing.
What You Can Do With It
The main capabilities that shape how people use Pydantic Logfire today.
Ingests OpenTelemetry data and offers first-party SDKs for Python, JavaScript/TypeScript, and Rust.
Shows AI and application traces together, including LLM calls, tool calls, API requests, database queries, logs, and metrics.
Lets users query observability data with SQL and export it through a public web API.
Adds AI-specific workflow support such as token tracking, cost monitoring, conversation panels, and Pydantic validation instrumentation.
Best For
Who Pydantic Logfire is most clearly built for.
Teams that want one observability layer for LLM behavior and the surrounding application stack.
Python-heavy teams instrumenting Pydantic AI, FastAPI, or other OpenTelemetry-compatible services.
Organizations that want a free entry tier with a path to enterprise self-hosting or compliance controls.
Platforms
Where you can use Pydantic Logfire today.
Web app
API
Python SDK
JavaScript/TypeScript SDK
Rust SDK
Self-hosted
Integrations
Notable connected tools and ecosystem hooks for Pydantic Logfire.
Pydantic AI
OpenAI
Anthropic
LangChain
LlamaIndex
Mirascope
Privacy Notes
Publicly stated data-handling notes that matter when evaluating Pydantic Logfire.
The privacy statement says Pydantic Services Inc. processes personal data as the data controller for Logfire services and may collect account, device, usage, cookie, and payment data.
Compliance
Public compliance or enterprise-governance signals we found for Pydantic Logfire.
SOC 2 Type II
HIPAA
GDPR
Access
How to integrate or build around Pydantic Logfire.
Public API
Yes
Docs
Available
Alternatives
Other tools worth considering alongside Pydantic Logfire.
Open-source LLM engineering platform for tracing, prompt management, evaluations, and analytics.
Framework-agnostic platform for observability, evaluation, and deployment of AI agents and LLM apps.
AI observability and evaluation platform for tracing, scoring, and improving production AI applications.
Open-source AI observability and evaluation platform for tracing, prompt iteration, and experiments.
Product Snapshot
Pydantic Logfire is Pydantic’s observability platform for AI and general application monitoring. It combines OpenTelemetry ingestion, a web UI, SQL querying, a web API, and first-party SDKs for Python, JavaScript/TypeScript, and Rust.
What You Can Do With It
- Send traces, logs, and metrics from OpenTelemetry-compatible services into Logfire and inspect them in the web app.
- Instrument AI workflows to inspect LLM calls, tool calls, token usage, cost, and surrounding application context.
- Query records and metrics with SQL or export them through the public web API.
- Add first-party instrumentation for Pydantic, FastAPI, and other documented integrations.
Why It Stands Out
It combines general observability and AI-specific views in one product. The same platform covers request traces, database queries, logs, metrics, and Pydantic validation while also exposing token tracking, cost monitoring, and conversation panels for AI workflows.
Tradeoffs To Know
- Lower tiers keep data for 30 days, so teams that need longer retention have to move upmarket or self-host.
- Pricing is usage-based after the included 10M logs/spans/metrics, so high-volume telemetry needs spend forecasting.
- Enterprise controls such as SSO, custom retention, and self-hosted deployment sit behind the top tier.
Sources
- pydantic.dev/pricing
- pydantic.dev/docs/logfire/manage/logfire-costs
- pydantic.dev/about
- pydantic.dev/legal/terms-of-service
- pydantic.dev/legal/privacy-policy
- pydantic.dev/articles/logfire-announcement
- pydantic.dev/articles/why-logfire
- pydantic.dev/logfire
- pydantic.dev/docs/logfire/get-started/ai-observability
- pydantic.dev/docs/logfire/reference/sql
- pydantic.dev/docs/logfire/api/logfire
- pydantic.dev/docs/logfire/integrations
- pydantic.dev/docs/logfire/get-started
- pydantic.dev/docs/logfire/enterprise
- pydantic.dev/docs/logfire/reference/self-hosted/overview
- pydantic.dev/docs/logfire/manage/query-api