BAML
Claim this toolThe first language for building reliable AI agents with type safety and structured outputs.
Visit WebsiteFreemiumVisit Website
Tracked since2026
0 reviews trackedThe Bottom Line
Entry price
Free plan available, paid tiers above
Biggest pro
Significantly improves reliability of AI pipelines
Biggest con
Requires learning a new language (BAML)
TL;DR - BAML
- A new language for building reliable, type-safe AI agents.
- Generates native code for Python, TypeScript, Ruby, Go, integrating with any LLM.
- Enables structured outputs, CI/CD testing, and automatic error handling for AI pipelines.
Pricing: Free plan available
Best for: Growing teams
What is BAML?
BAML (Basically A Made-Up Language) is a new programming language designed to make AI pipeline development 10x more reliable. It addresses the current developer experience challenges in building AI agents by introducing type safety and structured outputs for interactions with Large Language Models (LLMs).
BAML is for developers who want to build robust AI applications, offering a complete development workflow from defining prompts and functions to testing and deployment. It integrates seamlessly with existing programming languages like Python, TypeScript, Ruby, and Go, generating native functions that can be called directly within your codebase. This approach aims to reduce errors, improve iteration speed, and ensure predictable results from LLMs, making AI development more efficient and less prone to unexpected behaviors.
The tool is designed to work with any LLM provider and supports multi-cloud deployment, allowing developers to deploy their AI agents without special configurations. Key benefits include type-safe AI interfaces, validated structured outputs in various formats (JSON, XML, YAML), and the ability to test agents in CI/CD pipelines, along with automatic retry and fallback mechanisms for enhanced reliability.
Available on: Web, macOS, Linux, Windows
Pros & Cons
Pros
- Significantly improves reliability of AI pipelines
- Provides type safety for AI interactions
- Generates native code for popular programming languages
- Enables structured and validated outputs from LLMs
- Facilitates testing of AI agents in CI/CD
Cons
- Requires learning a new language (BAML)
- Limited information on advanced features or enterprise support
Preview
Key Features
Define prompts and functions in BAMLGenerate native functions in Python, TypeScript, Ruby, GoType-safe AI interfacesStructured outputs (JSON, XML, YAML, etc.)Test agents in CI/CD with baml-cli testAutomatic retry and fallback for failed requestsVSCode extension for developmentWorks with every LLM provider
Pricing Plans
Free TrialPricing checked Jul 9, 2026
Free
$0 / month
- Playground
- CLI & Editor extension access
- Unlimited BAML schemas
- TypeScript type generation
- Basic schema validation
- Local development
- Single developer
- Open source
Team
$25 / month
- Everything in previous plans
- Advanced type generation
- Runtime validation
- Unlimited schemas
- Team collaboration
- Unlimited developers
- Private schemas
- Custom transformations
Enterprise
Custom
- Everything in previous plans
- On-premise deployment
- SSO & SAML integration
- Custom rate limits
- Audit logs & compliance
- 99.9% uptime SLA
- Dedicated account manager
- Priority support
Reviews
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BAML FAQ
How does BAML improve the reliability of AI agents?
BAML enhances AI agent reliability by introducing type safety and structured outputs for interactions with Large Language Models (LLMs). This approach aims to reduce errors and ensure predictable results from LLMs, making AI development more efficient.
Which teams would benefit most from using BAML?
Teams of developers focused on building robust AI applications will find BAML most beneficial. It provides a complete development workflow for defining prompts and functions, testing, and deployment, which is ideal for creating reliable AI agents.
How does BAML compare to LangChain for building AI applications?
BAML differentiates itself from tools like LangChain by focusing on type safety and structured outputs to make AI pipeline development more reliable. It requires learning a new language, BAML, to achieve these benefits, while generating native functions for existing programming languages.
What kind of outputs can BAML generate from LLMs?
BAML can generate validated structured outputs from LLMs in various formats, including JSON, XML, and YAML. This capability ensures that the data received from LLMs is predictable and usable within applications.
Does BAML include a free tier for developers?
Yes, BAML is available on a free tier, allowing developers to get started with the language and its features. Paid plans are offered for users who require more usage and advanced features.
How does BAML support integration with existing codebases?
BAML integrates seamlessly with existing programming languages such as Python, TypeScript, Ruby, and Go. It achieves this by generating native functions that can be called directly within your codebase, simplifying the adoption of AI capabilities.
Source: boundaryml.com