Pydantic Case Studies
Showing 7 of 14 matching case studies
Customer stories
Logfire and Pydantic Evals give Evergreen.ai end-to-end observability and continuous evaluation for financial-services AI agents.
See how Evergreen.ai runs observable financial-services AI agents→
AutonomyAI gives coding agents Logfire via MCP to check production after merge and file follow-ups.
Learn how AutonomyAI caught 12 no-op deployments in five weeks→
Qualio uses Pydantic AI and Evals to turn plain-language quality criteria into auditable release gates.
Learn how Qualio gates every release with 300 evaluations→
Pydantic AI grounds STCC's clinical RAG in triage decision trees; Logfire makes every answer reviewable.
Learn how STCC reached 0% hallucinations in clinical triage→
Logfire gives GIC sub-second trace queries for live evaluation, deviation detection, and agent self-correction.
See how GIC made trace queries 150× faster→
Overjoy pairs Pydantic AI with Logfire to see costs and traces, then improve agents from real usage.
Learn how Overjoy caught a 20× cost spike before it burned budget→
Datalayer uses Pydantic AI's readable, type-safe stack to run Jupyter agents across four protocols.
Explore Datalayer's multi-protocol Jupyter agent stack→
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