---
title: "Introduction"
description: "Simple, battle-tested framework for building reliable AI applications"
---

## Overview

Timbal is an open-source python framework for building reliable AI applications, battle-tested in production with transparent architecture that eliminates complexity while delivering concurrent execution, robust typing, and interface stability in an ever-changing ecosystem.

It offers both autonomous Agents for complex reasoning and explicit Workflows for step-by-step control, all built on unified primitives that make AI applications composable, traceable, and scalable.

- **[Agents](./agents)**: Agents are autonomous execution units that orchestrate LLM interactions with tool calling. 

  Best for:
  - Complex reasoning tasks requiring multiple steps
  - Dynamic tool selection based on context
  - Open-ended problem solving with autonomous decision making
  - Multi-turn conversations with memory across iterations

- **[Workflows](./workflows)**: Fine-grained control over your AI pipeline with explicit step-by-step execution. 

  Best for:
  - Complex data processing pipelines with multiple stages
  - Predictable processes with defined execution paths
  - Performance-critical applications requiring concurrent execution
  - Workflows where explicit control over step dependencies is needed

## Key Features

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  <Card
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    Persistent context across agent interactions with automatic state management.
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  <Card
    title="Model Routing"
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    Seamless multi-provider support with consistent APIs across all models.
  </Card>
    <Card
    title="Composability"
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    Build complex applications from simple, reusable primitives.
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  <Card
    title="Tracing"
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    Complete execution visibility with automatic logging and debugging.
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  <Card
    title="Evals"
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    Built-in evaluation framework for testing and validating AI outputs.
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  <Card
    title="Deployment"
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    Production-ready deployment with scaling and monitoring capabilities.
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</Columns>

## Why are we building this?

- **Simplicity over complexity**: Unlike LangGraph, CrewAI, and other frameworks that abstract away what's really happening, Timbal keeps things transparent. Under the hood, it's just LLM calls and async function execution - no hidden magic, no opaque abstractions.

- **Developer experience first**: We believe you shouldn't need to learn a new mental model to build AI applications. If you understand functions and async/await from any modern programming language, you understand Timbal. Most agents are built in 10-20 lines of code.

- **Battle-tested architecture**: Our core abstractions have been refined through real-world production usage. The framework is designed around proven patterns: async generators, Pydantic validation, and event-driven processing.

- **Robust interfaces**: Strong typing and validation make it nearly impossible to break things from the outside, while clean abstractions make internal modifications straightforward. The framework fails fast with clear error messages.

- **Performance by design**: Built for production workloads with concurrent execution, efficient memory management, and minimal overhead. Every design decision prioritizes speed and scalability.

- **Stability in a chaotic ecosystem**: Providers change and release new APIs monthly. Timbal provides a stable abstraction that shields your applications in production.
