BoundaryML

BoundaryML is a software publisher focused on developer tooling for building applications powered by large language models. Its flagship product, BAML, is described as the programming language for agents and serves as a domain-specific language designed to make interactions with LLMs more reliable, testable, and maintainable. BAML addresses a common challenge in AI application development: obtaining structured, predictable outputs from models that otherwise return free-form text. Developers use BAML to define function signatures, typed inputs and outputs, and prompt templates in a dedicated syntax, which the toolchain then compiles into native client code for languages such as Python and TypeScript. This approach allows engineering teams to treat LLM calls much like ordinary typed functions, complete with validation, parsing, and retry logic, rather than hand-writing fragile string manipulation code. Typical use cases include building AI agents, chatbots, data extraction pipelines, classification systems, and retrieval-augmented generation workflows, where responses must conform to a schema before being consumed by downstream application logic. BAML also supports integration with multiple model providers, giving developers the flexibility to switch between or combine different LLMs without rewriting their application code. The tooling around the language typically includes a playground environment for iterating on prompts, testing utilities for evaluating outputs against expected results, and observability features for tracing how functions behave in production. By offering a single, focused package, BoundaryML positions itself within the growing category of AI infrastructure and developer experience software, targeting software engineers and machine learning practitioners who want to bring the rigor of traditional software engineering, including type safety, version control, and automated testing, to the process of building LLM-powered features and agentic systems.