Pydantic for Enterprise | Build and Run Production AI

Pydantic for enterprise
Build on the open-source Pydantic stack. Evaluate every release. Observe and govern the complete production path, from untrusted input to the answer your customer receives.
Outcomes across the Pydantic stack
Operational outcomes
It takes more than a model call to deliver a reliable answer. Pydantic connects the decisions made in code to the evidence your business needs.
Follow one trace through models, tools, APIs, databases, and background jobs. Your team sees the failing step and the customer impact in the same place.
Turn real production cases into eval datasets, define release gates in plain language, and keep the evidence that engineering, product, and compliance can review.
See token, model, and infrastructure cost alongside quality and latency. Set spending limits and route model traffic without adding another disconnected control plane.
Engineers debug the trace, product teams inspect outcomes, and security teams review the controls. Everyone works from the same production record.
Bring us your current stack and the constraints that will shape production.
Adopt the pieces you need today. The same team builds the libraries, production platform, and support path around them.
Validate untrusted data and build agents with the Python libraries developers already choose.
Test behavior against repeatable datasets and evaluation criteria before changes reach customers.
Trace any language or framework, control model traffic, and improve live systems from real usage.
Choose the operating model that fits your security, residency, and procurement requirements without changing the developer experience.
Best for: Moving from pilot to production quickly
Fully managed by Pydantic, with US or EU data residency, SSO, custom retention, and priority support.
Best for: Managed isolation and regional control
Single-tenant infrastructure in a dedicated VPC, operated and supported by the team that builds Logfire.
Best for: Keeping telemetry in your infrastructure
Deploy to your Kubernetes cluster with our open-source Helm chart and keep telemetry inside your infrastructure.
Every deployment runs the same Logfire. What changes is who operates the infrastructure, where the data sits, and which controls come with the contract.
Map residency, isolation, and ownership requirements to the right deployment.
Security and governance
Give security and procurement a direct path to independently audited controls, legal documents, data policies, and deployment details.
Production outcomes from regulated software, cybersecurity, and AI-native engineering teams.
Root cause from an hour to minutes, across 54 agents and 697K+ production runs
160 test cases and 300 evals gate every deploy
SQL alerts catch previously invisible background-job failures
Work directly with Pydantic engineers on architecture, rollout, production readiness, and performance. Enterprise plans include 24/7 priority support, setup assistance, and an SLA matched to your operating model.
Bring your timeline, production risks, and review requirements. We’ll work through the path to launch.
Pydantic is a connected stack. Pydantic Validation, Pydantic AI, and Pydantic Evals are open-source Python libraries. Logfire and AI Gateway add the production observability, governance, and operational support enterprises need once those systems are live.
Yes. Enterprise customers can choose Pydantic-managed Cloud, a Pydantic-managed dedicated environment, or self-hosted deployment in their own Kubernetes cluster. The pricing and enterprise deployment documentation contain the detailed comparison.
No. Logfire is built on OpenTelemetry and accepts telemetry from applications written in any language or framework. The first-party Python, JavaScript and TypeScript, and Rust SDKs make common integrations easier.
Yes. Logfire accepts OpenTelemetry from any language or framework, including Java, Go, .NET, Ruby, and PHP. You can use the OpenTelemetry SDKs and collectors your teams already run, while our first-party SDKs provide a more tailored experience for Python, JavaScript and TypeScript, and Rust.
Our Trust Center covers security controls, subprocessors, compliance, and the documents procurement teams typically request. SOC 2 and penetration-test reports are available through the document request process.
Enterprise pricing is custom and reflects your deployment model and negotiated usage commitment. Plans include unlimited seats and projects, volume-discounted usage, custom retention, and SLA-backed support; the pricing page contains the detailed comparison.
Bring us the hard requirements
Tell us what you are shipping, where it has to run, and what your reviewers need to see.
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