Best AI Agent Framework for Workflows: Restack vs Windmill vs Pydantic AI

What These Frameworks Do

Restack is an open-source framework designed to assist engineers in creating, deploying, and scaling autonomous AI applications. It features stateful execution over long horizons, automatic retries with exponential backoff, and rate-limited task queues, leveraging Temporal workflows and Kubernetes-native orchestration to ensure high reliability and scalability.

Windmill is an open-source workflow engine and developer platform to build endpoints, workflows, UIs and AI agents. It supports coding in TypeScript, Python, Go, PHP, Bash, C#, SQL, Rust, Ruby and R, or any Docker image, alongside intuitive low-code builders.

Pydantic AI is the Python AI SDK: a typed, extensible agent loop with every model a string swap away. Pydantic AI Harness is built for work that runs for hours, with tool and output validation to catch invalid data and durable execution to recover from interruptions.

Architecture and Design Philosophy

Restack emphasizes enterprise-scale orchestration. It allows shipping AI agents "like real product features" with version control for prompts and tools, feedback loops, A/B testing, no-code experience definition, observability and tracing, durable workflows (handling retries, rate limits, long-lived state), and Kubernetes-native scaling—without heavy infrastructure management. It is built for product teams that want stronger feedback loops around agent experience while engineering teams keep runtime reliability under control on Kubernetes.

Windmill combines code-first flexibility with low-code accessibility. It is an open-source workflow engine that lets teams turn scripts into scalable UIs, APIs, and scheduled jobs—without managing complex infrastructure. Windmill follows a clean server/worker split where stateless API servers handle HTTP routing, authentication, flow orchestration, and UI serving, while stateless workers pull jobs from a PostgreSQL-backed queue and execute them in isolated processes. This architecture means horizontal scaling is trivially achieved by adding worker replicas.

Pydantic AI takes a Python-first, type-safety approach. Its differentiator is type safety: you define expected agent outputs as Pydantic models, and the framework validates the LLM's response against that schema, with reflection and self-correction that re-prompts the model when output does not match. Code-driven agent composition enables custom routing and interaction logic, unlike pre-defined orchestration patterns found in other frameworks.

Language Support and Developer Experience

Restack supports Python and TypeScript, integrating with existing tools and libraries.

Windmill offers the broadest language support across the three. It supports multi-language scripting – write workflows in Python, Node.js, or Go. Beyond those, it also supports PHP, Bash, C#, SQL, Rust, and Ruby.

Pydantic AI is Python-only, but built by the Pydantic team, it brings FastAPI-style type-safety and ergonomics to agent development. It is model-agnostic (OpenAI, Anthropic, Gemini, Mistral, Groq, Ollama, Bedrock and more) with first-class Model Context Protocol support.

Long-Running Workflows and Durability

For workflows that span hours or days, durability matters. Restack provides a comprehensive framework for building autonomous AI agents with features like long-running workflows (persisting state for months or years), task queues with concurrency control, built-in retry policies, cron scheduling, and REST API integration for asynchronous execution.

Windmill handles durability through its PostgreSQL-backed job queue. The combination of sub-50ms queue-to-execution latency (benchmarked against Airflow, Prefect, and Temporal) with full script sandboxing via nsjail is unusual — most fast orchestrators sacrifice isolation, and most secure orchestrators sacrifice performance.

Pydantic AI Harness is built for work that runs for hours, with tool and output validation to catch invalid data and durable execution to recover from interruptions. Attach TemporalDurability and the same agent runs inside a Temporal workflow under durable execution: every model and tool call becomes a durable activity, so a run working through a background queue survives restarts, failures, and long waits.

AI Integration and Agent Orchestration

Restack is built specifically for multi-agent systems. It supports the creation of multi-step, decision-based workflows. Users can employ AI models ranging from zero-shot tasks to more complex multi-agent reasoning configurations, accommodating a variety of AI models.

Windmill increasingly supports agentic workflows. A developer uses Windmill's MCP server integration and Claude AI assistance to build agentic workflows where LLMs generate and run scripts, inspect results, and chain follow-up actions — all observable and resumable through the Windmill UI. The AI integration goes beyond autocomplete: Windmill's MCP server exposes scripts and flows as tools that Claude can discover and invoke, enabling LLM-driven automation where the agent itself can compose and run Windmill workflows.

Pydantic AI enables multi-agent systems through code. Dynamic workflows are now a first-class capability in the Pydantic AI Harness. Build multi-agent systems with Pydantic AI: delegate to sub-agents through tools, hand off between agents in your code, or orchestrate them with graphs.

Pricing and Licensing

Restack offers free access to its open-source core, though specific commercial pricing details aren't publicly standardized.

Windmill offers a generous free tier. Windmill self-hosted Community Edition is free with unlimited executions. Cloud plans include Free (1,000 executions per day), Team at $10 per user per month (unlimited executions), and Enterprise with custom pricing. Windmill splits users into two categories: Developers ($20 per month) can write scripts, build flows, and create apps. Operators ($10 per month) can execute existing scripts and apps, but cannot create or modify.

Pydantic AI is fully free. Pydantic AI and Pydantic AI Harness are open source under the MIT license. You pay your model providers and hosting services. Logfire and AI Gateway are optional Pydantic products with their own pricing.

When to Use Each Framework

Choose Restack if:

You're building enterprise-scale autonomous systems that require Kubernetes orchestration
You need strong feedback loops and monitoring between product and engineering teams
Long-running workflows with persistent state across weeks or months are central to your use case
You want tight integration between agent behavior definition and operational reliability

Choose Windmill if:

You need a flexible, code-friendly alternative to visual-only automation platforms
You want to serve multiple languages and run scripts in your existing tech stack
You're building internal tools, data workflows, or backend jobs that may later include AI
You prefer a PostgreSQL-based queue over external workflow engines
Cost efficiency matters, and you plan to scale from a handful of developers to many operators

Choose Pydantic AI if:

You're working primarily in Python and value type safety and validation
You want the lowest barrier to entry for building production agents
You're already using the Pydantic ecosystem or FastAPI
You need maximum flexibility in model selection and integrations without vendor lock-in
You're fine managing your own infrastructure for durability (via Temporal or similar)

The Bottom Line

Restack is designed to assist engineers, machine learning engineers, software developers, automation engineers, and data scientists building production systems at scale. Windmill excels for teams that want code-driven workflows without infrastructure overhead. Pydantic AI is ideal for Python teams prioritizing type safety and rapid development.

For autonomous workflow development, the best AI agent framework for workflows depends on your infrastructure maturity, team expertise, and whether you prioritize operational control (Restack), flexible scripting (Windmill), or developer ergonomics and type safety (Pydantic AI).