Pydantic AI
Build agents you’ll actually ship to production

Name: Pydantic Logfire
Brand: Pydantic

Trace production agents, turn failures into eval cases, and improve what ships with Pydantic Logfire. Bring your agents written in Python or TypeScript.

Continuously improve your agents with insights from your traces and evals. Protect your data and control your spend with Logfire AI Gateway.

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From the team behind Pydantic Validation

60K+ GitHub stars
1BN+ monthly downloads

Trusted across the Python ecosystem and by engineering teams building the systems people rely on.

12×

faster issue resolution across more than 50,000 AI research workflows.

Boosted.ai case study

150×

faster trace queries, making live evaluation and agent self-correction possible.

General Intelligence Company case study

20×

cost spike caught before it burned through the team’s budget.

Overjoy case study

Problem

AI applications fail in production in ways existing tools can’t see

The answer can be wrong even when every service is healthy. Evals that ignore production are exercises in creative writing: they test the cases you imagined, while the real failure sits in a tool call, model response, API, or database query.

AI tracing

Model output looks healthy

Application monitoring

The database timeout is elsewhere

Solution

One trace across your agent, model calls, APIs, and database

Logfire keeps the full execution path together, so you can debug what broke, evaluate what worked, and improve the agent from real production evidence.

Agent
Model
API
Database

One requestOne source of truth

Outcome

One trace gives every team a better decision

Move from a symptom to the evidence that explains it—without stitching together separate tools or guessing from averages.

Evaluation

Synthetic test sets miss the failures users actually hit.

Turn production failures into eval cases and verify the fix.

Engineering

Tool sprawl turns incidents into archaeology.

Follow one request through every layer of the application.

Cost

Retries and model choices quietly burn budget.

See cost in context and cut what is not earning its keep.

Security

Sensitive data can cross more systems than expected.

Inspect the path, enforce policy, and retain the evidence.

Integrations

Logfire works with your entire stack

Built on OpenTelemetry, with first-party SDKs for Python, JavaScript and TypeScript, and Rust. Trace agent frameworks, application code, databases, and the infrastructure underneath them without rebuilding your application around an observability vendor.

Agent frameworks

Follow agents and tool calls across verified OpenTelemetry paths, without tying production visibility to one framework.

Pydantic AI LangGraph CrewAI AutoGen Google ADK Claude Agent SDK Strands Agents Mastra See the support matrix

Explore agent observability

Python

Rust

Built on the tracing and OpenTelemetry ecosystem.

tracing opentelemetry log crate

Any language via OpenTelemetry

Any framework with OpenTelemetry instrumentation works. Our SDKs are convenient wrappers, not a lock-in boundary.

Go Java .NET Ruby PHP Erlang / Elixir Swift C++

Infrastructure

Keep the services, hosts, clusters, containers, and cloud metrics underneath each request in the same investigation.

Dashboards & alerts

Elasticsearch MongoDB Redis PostgreSQL Kafka NGINX and more…

Compute

Hosts Kubernetes Docker AWS Lambda

Metrics

Cloud providers System metrics

Explore infrastructure monitoring

Our mission

Building the best developer experience on planet earth

Pydantic did not start as a business idea. It started with a developer problem worth solving well. The team behind the validation library now brings the same obsession with clear APIs, useful defaults, and open standards to the whole AI engineering stack.

About Pydantic Work with us

“ I started working on Pydantic out of frustration that type hints did nothing at runtime, and curiosity about whether they could validate data.
Pydantic’s growth means the maintainers behind it now get to build more products on the same principle: the most powerful tools can still be easy to use. ”