agent · AI Agents Frameworks

PydanticAI

ai.pydantic.devupdated Aug 1, 2026view as JSON

18 fields evidenced · 37 with no public information. Every value below links to the document it came from and the date we checked it.

Trust gap

How this is scored

Runtime governance

unscored

Are scope, spend, and authority enforced while the agent runs?

Audit trail

2/3

Is there a tamper-evident record of what it actually did?

Scored from 2 evidenced field(s): audit_trail, explainability. Automated score; capped at 2 pending review.

Compliance

unscored

Are compliance obligations attached per engagement?

Outcome settlement

unscored

Does payment depend on a verified result?

Insurance & indemnity

unscored

Can the deployment be insured, and is the customer indemnified?

Assurance

Insurance available: no public information
ai.pydantic.dev · checked Aug 1, 2026 · source did not state this
Insurance carriers: no public information
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Coverage limits: no public information
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Indemnification: no public information
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Liability cap: no public information
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Audit trail: Tightly integrates with Pydantic Logfire , our general-purpose OpenTelemetry observability platform, for real-time debugging, evals-based performance monitoring, and behavior, tracing, and cost tracking.
“Tightly integrates with Pydantic Logfire , our general-purpose OpenTelemetry observability platform, for real-time debugging, evals-based performance monitoring, and behavior, tracing, and cost tracking.”
ai.pydantic.dev · checked Aug 1, 2026
Tamper-evident log: no public information
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Explainability: Tightly integrates with Pydantic Logfire , our general-purpose OpenTelemetry observability platform, for real-time debugging, evals-based performance monitoring, and behavior, tracing, and cost tracking.
“Tightly integrates with Pydantic Logfire , our general-purpose OpenTelemetry observability platform, for real-time debugging, evals-based performance monitoring, and behavior, tracing, and cost tracking.”
ai.pydantic.dev · checked Aug 1, 2026
Runtime governance: no public information
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Permission scopes: no public information
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Compliance certifications: no public information
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Regulatory alignment: no public information
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Outcome-based pricing: no public information
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Settlement mechanism: no public information
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Dispute process: no public information
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SLA terms: no public information
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Evaluation coverage: no public information
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Agency

Autonomy level: no public information
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Human oversight: no public information
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Goal complexity: build production grade applications and workflows with Generative AI
“build production grade applications and workflows with Generative AI”
ai.pydantic.dev · checked Aug 1, 2026
Action space: built-in capabilities for thinking , web search , web fetch , image generation , MCP , tool search , and more; Pydantic AI Harness is our official library of ready-made capabilities — code execution, file access, guardrails, sub-agent orchestration, and more
“built-in capabilities for thinking , web search , web fetch , image generation , MCP , tool search , and more; Pydantic AI Harness is our official library of ready-made capabilities — code execution, file access, guardrails, sub-agent orchestration, and more”
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Operating environment: build interactive applications with streaming event-based communication
“build interactive applications with streaming event-based communication”
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Initiative: Enables you to build durable agents that can preserve their progress across transient API failures and application errors or restarts, and handle long-running, asynchronous, and human-in-the-loop workflows with production-grade reliability.
“Enables you to build durable agents that can preserve their progress across transient API failures and application errors or restarts, and handle long-running, asynchronous, and human-in-the-loop workflows with production-grade reliability.”
ai.pydantic.dev · checked Aug 1, 2026

Safety

Safety evaluations: no public information
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Red teaming: no public information
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Safety policy: no public information
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Usage restrictions: no public information
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Model or system card: no public information
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Incident reporting: Join Slack or file an issue on GitHub if you have any questions.
“Join Slack or file an issue on GitHub if you have any questions.”
ai.pydantic.dev · checked Aug 1, 2026
Third-party evaluations: no public information
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Data handling: no public information
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Practicality

Pricing model: no public information
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Price point: no public information
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Availability: no public information
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Deployment options: Pass the built-in 'test' model , which runs entirely offline without calling an LLM
“Pass the built-in 'test' model , which runs entirely offline without calling an LLM”
ai.pydantic.dev · checked Aug 1, 2026
Integrations: Integrates the Model Context Protocol and various UI event stream standards
“Integrates the Model Context Protocol and various UI event stream standards”
ai.pydantic.dev · checked Aug 1, 2026
Supported regions: no public information
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Support model: no public information
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Foundation models

Base models: Supports virtually every model and provider: OpenAI, Anthropic, Gemini, DeepSeek, Grok, Cohere, Mistral, and Perplexity; Azure AI Foundry, Amazon Bedrock, Google Cloud, Ollama, LiteLLM, Groq, OpenRouter, Together AI, Fireworks AI, Cerebras, Hugging Face, GitHub, Heroku, Vercel, Nebius, OVHcloud, Alibaba Cloud, SambaNova, and Z.AI.
“Supports virtually every model and provider: OpenAI, Anthropic, Gemini, DeepSeek, Grok, Cohere, Mistral, and Perplexity; Azure AI Foundry, Amazon Bedrock, Google Cloud, Ollama, LiteLLM, Groq, OpenRouter, Together AI, Fireworks AI, Cerebras, Hugging Face, GitHub, Heroku, Vercel, Nebius, OVHcloud, Alibaba Cloud, SambaNova, and Z.AI.”
ai.pydantic.dev · checked Aug 1, 2026
Model provider: Supports virtually every model and provider: OpenAI, Anthropic, Gemini, DeepSeek, Grok, Cohere, Mistral, and Perplexity; Azure AI Foundry, Amazon Bedrock, Google Cloud, Ollama, LiteLLM, Groq, OpenRouter, Together AI, Fireworks AI, Cerebras, Hugging Face, GitHub, Heroku, Vercel, Nebius, OVHcloud, Alibaba Cloud, SambaNova, and Z.AI.
“Supports virtually every model and provider: OpenAI, Anthropic, Gemini, DeepSeek, Grok, Cohere, Mistral, and Perplexity; Azure AI Foundry, Amazon Bedrock, Google Cloud, Ollama, LiteLLM, Groq, OpenRouter, Together AI, Fireworks AI, Cerebras, Hugging Face, GitHub, Heroku, Vercel, Nebius, OVHcloud, Alibaba Cloud, SambaNova, and Z.AI.”
ai.pydantic.dev · checked Aug 1, 2026
Model swappable: If your favorite model or provider is not listed, you can easily implement a custom model .
“If your favorite model or provider is not listed, you can easily implement a custom model .”
ai.pydantic.dev · checked Aug 1, 2026
Open weights: no public information
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Fine-tuning: no public information
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Context window: no public information
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Ecosystem

Protocols supported: Integrates the Model Context Protocol and various UI event stream standards
“Integrates the Model Context Protocol and various UI event stream standards”
ai.pydantic.dev · checked Aug 1, 2026
Tool use: The @agent.tool decorator let you register functions which the LLM may call while responding to a user.
“The @agent.tool decorator let you register functions which the LLM may call while responding to a user.”
ai.pydantic.dev · checked Aug 1, 2026
Multi-agent: Pydantic AI Harness is our official library of ready-made capabilities — code execution, file access, guardrails, sub-agent orchestration, and more
“Pydantic AI Harness is our official library of ready-made capabilities — code execution, file access, guardrails, sub-agent orchestration, and more”
ai.pydantic.dev · checked Aug 1, 2026
API access: Sign up for our newsletter, The Pydantic Stack , with updates & tutorials on Pydantic AI, Logfire, and Pydantic
“Sign up for our newsletter, The Pydantic Stack , with updates & tutorials on Pydantic AI, Logfire, and Pydantic”
ai.pydantic.dev · checked Aug 1, 2026
Open source: no public information
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Marketplace presence: no public information
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Impact

User base: no public information
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Deployment scale: no public information
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Target sectors: build coding agents, research assistants, and anything in between
“build coding agents, research assistants, and anything in between”
ai.pydantic.dev · checked Aug 1, 2026
High-risk domains: Here is a concise example using Pydantic AI to build a support agent for a bank
“Here is a concise example using Pydantic AI to build a support agent for a bank”
ai.pydantic.dev · checked Aug 1, 2026
Documented incidents: no public information
ai.pydantic.dev · checked Aug 1, 2026 · source did not state this