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Boundary BAML

A domain-specific language and platform for generating reliable, type-safe structured outputs from large language models (LLMs) with enhanced developer experience.

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Product Overview

What is Boundary BAML?

Boundary BAML is a specialized programming language designed to simplify and optimize prompt engineering for LLMs by enabling developers to write structured, type-safe prompts and receive validated structured data outputs. It supports any LLM, programming language, and schema, providing autocomplete, live previews, and robust parsing that corrects LLM errors. BAML significantly improves developer productivity by integrating prompt logic directly into code editors like VSCode, eliminating the need for complex setups and allowing seamless function-like calls to LLMs with guaranteed output structure and type safety.


Key Features

  • Type-Safe Structured Outputs

    Generates fully type-checked, structured data from LLMs, ensuring reliable and predictable outputs even during streaming.

  • Universal Compatibility

    Works with any large language model, programming language, and custom schema, offering maximum flexibility.

  • Developer-Friendly Environment

    Includes a VSCode playground with live prompt previews, autocomplete, linting, and hot-reloading for rapid prompt development.

  • Efficient Token Usage

    Utilizes type-definitions instead of JSON schemas, reducing token consumption by up to 60% without loss of information.

  • Robust Parsing and Validation

    Automatically parses and validates LLM outputs against defined schemas, correcting errors and ensuring data integrity.

  • Cross-Language SDKs

    Provides native SDKs for Python, TypeScript, and Ruby, enabling seamless integration and usage as native functions with autocomplete and type safety.


Use Cases

  • Reliable Data Extraction : Extract structured information from unstructured text such as resumes, emails, or documents with high accuracy.
  • Agent and Chatbot Development : Build dependable AI agents and chatbots that require precise structured responses and complex prompt logic.
  • Prompt Engineering and Testing : Rapidly develop, test, and iterate on prompts within an integrated environment to optimize LLM interactions.
  • Enterprise AI Pipelines : Deploy robust AI data processing pipelines with guaranteed structured output for large-scale batch processing.

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Analytics of Boundary BAML Website

Boundary BAML Traffic & Rankings
26.92K
Monthly Visits
00:01:46
Avg. Visit Duration
8040
Category Rank
0.44%
User Bounce Rate
Traffic Trends: Sep 2025 - Nov 2025
Top Regions of Boundary BAML
  1. 🇺🇸 US: 57.83%

  2. 🇻🇳 VN: 9.64%

  3. 🇩🇪 DE: 6.82%

  4. 🇮🇳 IN: 4.67%

  5. 🇹🇭 TH: 4.45%

  6. Others: 16.59%