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Pydantic AI logo

Pydantic AI

AI Agents

Verified Publisher·Pending reviewVerified Adoption·Pending reviewEnterprise Ready·Pending review

Python agent framework from Pydantic for production LLM applications with typed models, tools, evals, and structured outputs.

Public links
Visit WebsiteDocumentation

Developers also use

Generated from similarity, co-save, category, project, and adoption signals.

Continue logo
Continue

AI Agents· continue.dev

Open source

Open-source AI code assistant and agent framework for IDE workflows, custom models, and team knowledge.

Why recommended

Same category

Keep evaluating Pydantic AI

Comparisons, category adoption data, and shortlist guides that answer the questions this profile raises next.

Weigh Pydantic AI against the alternatives

  • Pydantic AI alternativesEvery ai agents product developers evaluate in place of Pydantic AI.
  • Pydantic AI vs ContinueSide-by-side pricing, API surface, and adoption evidence.
  • Pydantic AI vs OpenAI Agents SDKSide-by-side pricing, API surface, and adoption evidence.
  • Pydantic AI vs Google Agent Development Kit

Enterprise fit

Buyer brief for procurement and architecture review

Source-labeled signals for cost, reliability, security, integration, and adoption proof. Missing compliance evidence is shown as a gap, not guessed.

Compare for enterpriseExport brief
Inferred

Commercial model

Open source profile signal; exact enterprise terms need buyer review.

View source
Needs verification

Reliability

No status page, uptime, or SLA evidence attached

Needs verification

Security/compliance

No security, trust, or compliance source attached

Source linked

Integration fit

API available with docs/profile signal

View source
Verified

Adoption proof

1 verified adoption signal

Buyer recommendation

Shortlist only after verifying Reliability and Security/compliance.

API signal supports workflow automation.Docs are linked for implementation review.Open-source path can reduce lock-in review.At least one buyer evidence source is linked or verified.

Vendor value loop

Vendors receive anonymous aggregate evaluation demand by default. Account details are shared only after explicit buyer contact or consent.

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Real data backfill while adoption proof grows

These are source-linked enrichment paths for missing fields. They are treated as proxies until claimed-company data and first-party tokens& adoption events replace them.

GitHub repository APIfreeStars, forks, license, topics, releases, default branch, repo freshness, and public contributor signal.OpenSSF ScorecardfreeOpen-source security posture checks for repos before enterprise review.Wikidata company graphfreeParent company, acquisition, and ownership hints to avoid misleading same-owner comparisons.

Events / Tours

Pydantic AI developer events

Hackathons, workshops, office hours, launches, and partner challenges tied to this product.

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No public events yet

Claimed teams can add hackathons, webinars, office hours, and challenges, then measure attendee to usage ROI.

Public implementation evidence

Public projects using Pydantic AI

Judging lockedEvent-linked buildSource: https://luma.com/horizonagentshackSubmissions are locked for judging after the event close.
Anonymous builder6 days ago
Mission Continuity

What happens when an AI agent remembers the task but forgets what it was allowed to do? Mission Continuity is a working experiment built with Claude, Pydantic AI, and Sentience Governor. Our agent investigates a synthetic billing dispute but cannot issue refunds, modify records, delete information, or contact the customer. We compare two architectures across context compaction. The baseline carries forward an AI-generated summary. The governed version also preserves critical evidence verbatim and reintroduces the original Mission Kernel on every request. Sentience Governor records execution and flags scope violations; the application manages compaction and guards prohibited actions. In one recorded baseline run, the agent attempted to contact the customer after restrictions disappeared from its summary. Governor flagged the attempt; no real customer was contacted. The governed run retained all six tracked facts and mission limits without a prohibited attempt. In a controlled omission test, baseline retained 2/6 facts versus governed 6/6. We also tested Liquid AI summarization offline and exported 1,241 execution-evidence rows to RawTree for SQL analysis. A fresh live governed run completed 27 tool calls and one compaction, retained 6/6 facts, and produced a report scoring 4/5 against a withheld answer key. The project includes a working Streamlit console, verifiable replays, and reproducible experiments.

Listed tools (6)

Scroll for more
  • Pydantic AIPython agent framework from Pydantic for production LLM applications with typed models, tools, evals, and structured outputs.
  • Claude Code RouterOpen-source router for Claude Code that lets builders route coding-agent requests across OpenAI-compatible model providers and custom backends.
  • Liquid AIpendingAdded by the builder while publishing buildstuff. Pending catalog review before becoming a public tool profile.
  • TinybirdpendingAdded by the builder while publishing buildstuff. Pending catalog review before becoming a public tool profile.
  • Black Forest LabspendingAdded by the builder while publishing trexpush. Pending catalog review before becoming a public tool profile.
  • SGSentience GovernorpendingAdded by the builder while publishing Mission Continuity. Pending catalog review before becoming a public tool profile.
0 0 0Open

AgentRank trust profile

Public proof buyers and agents can trust

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AgentRank

51

Public signals · ★ 20,249

Trust Score

47

observed

Category Rank

#5

AI Agents · public signals

Protocols

API, SDK

Agent-readable metadata

Tracked Developers

0

Known active developer activity

Profile Status

Unclaimed

Owner action needed

Trust Registry

AgentRank evidence file
observed

Source breakdown

GitHub20,249

68% confidence

Protocol support

APISDK
Adoption over time
Last 8 weeks+699 GitHub stars in 30d · cohort private · trust 47

Timeline appears after verified events.

We do not draw a fake adoption chart before live usage, self-reported proof, or challenge activity exists for this product.

Private (N<7)

active developers

Private (N<7)

verified adoptions

Private (N<7)

retention

Your developer adoption profile is already visible.

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Developer identities

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Account map

Developer identities, account mapping, retention cohorts, and competitor overlap are available on Growth and Enterprise plans.

About Pydantic AI

Python agent framework from Pydantic for production LLM applications with typed models, tools, evals, and structured outputs.

Resources
DocsDocs

Official implementation documentation.

GitHubGitHub

Public source repository.

Official websitelaunch_source

Public source used by the daily production tool intake.

GitHub
3 Resources
GitHub Stats

20,249

Stars

2,810

Forks

1,137

Issues

Quick Info
PricingOpen source
Open sourceYes
API availableYes
36,067
5,447
Open source
Why recommended

Same category

OpenAI Agents SDK logo
OpenAI Agents SDK

AI Agents· openai.github.io

Open source

Open-source Python SDK for building, running, tracing, and handoff-driven AI agents with OpenAI models and tools.

Why recommended

Same category

29,792
4,841
Open source
Why recommended

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Google Agent Development Kit logo
Google Agent Development Kit

AI Agents· adk.dev

Open source

Open-source code-first toolkit for building, evaluating, debugging, and deploying production AI agents across Google ADK runtimes.

Why recommended

Same category

21,688
4,084
Open source
Why recommended

Same category

Julep logo
Julep

AI Agents· julep.ai

Freemium

Serverless platform for building stateful AI agents and multi-step LLM workflows with memory, tasks, and external tool integrations.

Why recommended

Same category

6,576
968
Open source
Why recommended

Same category

Side-by-side pricing, API surface, and adoption evidence.
  • Pydantic AI vs JulepSide-by-side pricing, API surface, and adoption evidence.
  • Check the adoption evidence

    • AI Agents developers actually keep usingFiltered to products with verified usage events, cohort breadth, and retention.
    • AgentRank category rankingsHow every category is ordered by adoption proof, trust, and protocol support.
    • Best AI Agent FrameworksShortlist guide for this category, with the tradeoffs written out.
    • Best Open Source AI ToolsShortlist guide for this category, with the tradeoffs written out.

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    Agent-readable protocol evidence raises trust and commercial readiness.

    Benchmark proof

    Benchmark proof pending

    Attach latency, cost, accuracy, reliability, or eval evidence to unlock the performance component.

    Trust gaps

    Verify publisher ownership
    Send SDK/API telemetry
    Attach benchmark evidence

    Enterprise verification can enrich evidence and export proof packages, but cannot buy rank.

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    Next best action

    Claim Pydantic AI before competitors use this profile as proof.

    Connect usage events, resolve developer identities, and see which accounts are evaluating Pydantic AI.

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    Resolve developer activity into companies, teams, and enterprise accounts.

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    Retention cohorts

    Track first API call through 7/30/90-day retention and expansion.

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    Competitor overlap

    Find developers evaluating alternatives and switching between tools.

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    Category benchmark

    Compare activation, retention, and growth against your market.

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    Recommended actions

    Prioritized DevRel, product, and sales plays based on live adoption signals.

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