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Data as of May 29, 2026
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Pydantic (Samuel Colvin)
Data validation library and AI agent framework
AI InfrastructureFounded 2023#2 of 55 in AI Infrastructure
Updated May 29, 2026
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Company profile
What is Pydantic (Samuel Colvin)?
Pydantic is a company built around its popular open-source Python library, which provides robust data validation, parsing, and serialization. It plays a crucial role in the AI ecosystem by enabling developers to define clear, type-hinted data schemas, essential for building reliable AI applications and agents that process structured information. This ensures data integrity and facilitates seamless interaction between different components in complex AI workflows.
Latest company data
Primary data point
Downloads
1.0B/30d
Tracked package: PyPI pydantic
▲ +14%Updated 1d ago
Other data points
Dependent projects
56.9K
Projects depending on tracked package: PyPI pydantic
Updated 9h ago
GitHub stars
27.9K
Main repository stars
Updated 9h ago
Hacker News
3/30d
Position #35 in category discussion
Updated 9h ago
Repository health
Maintenance data from the main open-source repository.
OpenSSF ScorecardSource: OpenSSF ScorecardUpdates: WeeklyCaveat: Score 0–10 across security practices; not all checks apply to every repoMethodology →
6.7
Releases (30d)Source: GitHub release dataUpdates: WeeklyCaveat: Published releases in the last 30 daysMethodology →
0
Repository usage
Public repositories and source files importing packages tied to Pydantic (Samuel Colvin).
Repos importingMetric: Public GitHub repos using company packagesSource: ecosyste.ms Packages APIScope: UTC daily snapshotUpdates: DailyFreshness: 48h target; 48h expected source lagConfidence: HighCaveat: Public GitHub dependency data only; private repos and direct API use outside those packages are not visible.Methodology →
49.4K0%
About Pydantic (Samuel Colvin)
Pydantic is a company built around its popular open-source Python library, which provides robust data validation, parsing, and serialization. It plays a crucial role in the AI ecosystem by enabling developers to define clear, type-hinted data schemas, essential for building reliable AI applications and agents that process structured information. This ensures data integrity and facilitates seamless interaction between different components in complex AI workflows.
FounderSamuel Colvin
Funding
$17M · 2 roundsRaised $17M total. Category position #2 of 55 in AI Infrastructure.
Series A2024
$13MSequoia Capital
Seed2023
$5MSequoia Capital
Investors
Sequoia Capital
Tracked packages (1)
1 PyPI
pydantic
PyPIMain PyPI packagepydantic
A powerful Python library for data validation, parsing, and serialization, widely used for defining data schemas and ensuring data integrity.