Pydantic Logfire
This entry runs no foundation model. Every finding below is quoted to the vendor’s own document, or marked not disclosed where the vendor publishes nothing.
Application monitoring overlay for Pydantic — tracks successful and failed validations in production, revealing where external inputs fail to meet the system's internal contracts
No foundation model. Pydantic Logfire does not run one, so this criterion does not apply and is excluded from the grade rather than counted against it. An OpenTelemetry-based observability platform that records traces, metrics and logs from applications - including instrumenting LLM and agent calls - but performs no inference and serves no model of its own. Established from the product’s own public documentation and what it does. If that is out of date, tell us at right of reply.
Not yet assessed. We publish a sovereignty position only where the vendor documents one — we do not infer it from a domain or a company name.
Pydantic Logfire publishes a list of the other companies it uses to process customer data. It names 15 of them, each shown below with the location the vendor lists it under, in the vendor’s own words.
Taken together those entries name at least European Union, United States. That is what our place list could match in the vendor’s own words above, so treat it as a floor rather than the whole of it — the entries themselves are the record.
These are other companies, not Pydantic Logfire. Where a sub-processor is listed as operating is a fact about that company. It is not a statement about where Pydantic Logfire keeps your data, which Vannus publishes separately and only from a document in which the vendor says so.
Read from pydantic.dev on 2026-09-16. Every entry above is a verbatim span of that page.
This is the vendor’s own disclosure, reproduced. Vannus has not audited what any of these companies do with your data, and a list can change without notice. Treat it as a starting point for your own review, not a legal determination, and take advice on anything that matters.
Vannus publishes a nine-dimension trust framework — data sovereignty, training privacy, compliance posture, operational resilience, exit portability, and more. The heaviest criterion asks whether the tool builds its own AI or resells someone else's model; where the vendor discloses it, the grade cites the vendor's own documentation. No paid placements — scoring is walled off from affiliate revenue. See the methodology →