Schema-based AI interfaces
Define AI prompts and structured outputs in BAML schemas, then generate native code in your target language. The site shows TypeScript type generation and examples that compile to Python, TypeScript, Ruby, and Go.
BAML
ClaimBAML is a developer tool for building AI applications with type safety and reliability. It helps teams define structured AI outputs, test prompts, and generate native code for languages like Python, TypeScript, Ruby, and Go.
AI development tool with typed schemas and generated code
BAML is a developer tool for building AI apps with type safety and reliability. It centers on defining AI prompts and structured outputs in a schema-first language, then generating native code for application languages such as Python, TypeScript, Ruby, and Go.
The site positions BAML as a full workflow for AI development: define prompts and functions, test them in an editor or CI/CD pipeline, generate code from the same definitions, and deploy the result as ordinary application code. The product also includes a browser playground for editing and running BAML programs, plus pricing tiers for individual developers, teams, and enterprises.
Core capabilities
Testing and validation workflows
Validate outputs and test prompts before deployment. The home page highlights schema validation, CI/CD testing, automatic retry, and fallback responses for failed requests.
Interactive playground
Use the browser playground or editor-based workflow to edit and run BAML programs. The playground page shows a workspace, file explorer, prompt editor, and test case runner.
Multi-provider LLM support
Connect BAML to different LLM providers and client configurations. The playground example includes OpenAI and Anthropic clients, and the home page says BAML works with every LLM provider.
Developer tooling
Use CLI and editor extension access for development workflows. The pricing page explicitly includes CLI and editor extension access in paid plans, and the home page references VS Code and `baml-cli` commands.
Native deployment fit
Deploy generated code in normal application environments without special runtime requirements from BAML. The home page says BAML generates native code that can be used in multi-cloud deployment targets such as AWS Lambda, Vercel, Google Cloud, Azure Functions, and Railway.
Common use cases
Typed output generation
Use BAML when you want to define structured AI outputs and generate types from the same source, so downstream code can rely on a predictable shape instead of parsing ad hoc text.
Prompt iteration and testing
Use the browser playground to iterate on a prompt, inspect the BAML file, and run a test case before moving the same definition into the rest of your codebase.
Automated regression checks
Use BAML in a CI/CD pipeline to validate that prompts and agent outputs still behave as expected after changes.
Application integration
Use the generated language-specific code in application stacks that need direct integration with Python, TypeScript, Ruby, or Go.
Team AI development
Use BAML when your team needs a shared workflow for development, collaboration, and private schemas rather than isolated prompt scripts.
Pros and Cons
Pros
- Combines prompt definition, schema validation, testing, and code generation in one workflow.
- Generates native functions in multiple programming languages rather than requiring a separate runtime abstraction layer.
- Shows support for different usage contexts, including local editing, browser-based playground work, and CI/CD testing.
- Provides a free plan, paid team plan, and enterprise option, which makes the product easy to evaluate before committing.
- Offers conservative reliability features such as validation, retries, and fallback responses.
Cons
- The public pages do not provide step-by-step setup instructions from the linked getting-started docs because that page returns a 404.
- Some integration details are visible only in examples, so supported providers and environments are broader in presentation than in documented implementation detail.
- Enterprise and support capabilities are listed on the pricing page, but the public sources do not describe technical limits or deployment prerequisites in depth.
FAQ
What pricing options does BAML offer?
BAML provides a free plan for individual developers, a Team plan for development teams, and an Enterprise plan for large organizations with custom needs. The pricing page also shows a 14-day free trial for paid plans.
How do teams use BAML in practice?
The site shows BAML running through a browser-based playground and describes CLI and editor extension access in paid plans. The home page also mentions use in VS Code and CI/CD workflows.
What languages and model providers does BAML support?
BAML is designed to generate native functions in languages such as Python, TypeScript, Ruby, and Go from BAML schemas and functions. The home page also states that it works with every LLM provider.
What does a typical BAML workflow look like?
The playground page shows defining an LLM client, a structured output type, a function prompt, and a test case in a single BAML file. The home page also emphasizes schema validation and testing prompts or functions before deployment.
Does BAML have team and enterprise support options?
The pricing page lists support for upgrading or downgrading plans, startup and education discounts, and enterprise support options such as custom contracts and account management. Specific implementation details for onboarding are not provided on the source pages.
Quick Facts
- Category
- Developer Tool
- Product type
- AI application development tool
- Primary users
- Developers building AI applications
- Source domain
- boundaryml.com
- Pricing model
- Free plan, Team plan, Enterprise plan
- Workflow
- Define schemas, test prompts, generate native code, deploy normally