AIEngineering
No Bad Outputs
"Structured generation is the future of LLMs.”
Julien Chaumond, Cofounder & CTO, HuggingFace
Integrate LLMs seamlessly in your software stack.
Structured outputs aren't optional. They're the critical foundation that transforms experimental AI into enterprise-grade systems.
Traditional approaches waste precious development cycles on parsing and validating LLM outputs. .txt's products make data flow seamlessly through your system by providing complete control over LLMs' outputs.
Our products ensure LLMs consistently generate outputs matching any JSON Schema, regular expression, or grammar—without significant overhead.
Whether you're building mission-critical APIs, scaling inference infrastructure, or deploying AI capabilities organization-wide, .txt delivers the structured generation capabilities your engineering team needs and the reliability your business demands.
AWS marketplace
Need a hosted solution on your VPC? Our solution empowers you to rapidly deploy and scale large language models with dotjson, dotregex and dotgrammar.
dotjson
dotjson is our high-performance library for constraining LLM output to match a predefined JSON Schema. Available under a commercial license with a Python, C, C++, or Rust API.
Use cases: agent protocols, information extraction, annotation, synthetic data, function calling.
dotregex
dotregex is our high-performance library for constraining LLM output to match a predefined regular expression. Available under a commercial license with a Python, C, C++, or Rust API.
Use cases: information extraction, table generation, classification
dotgrammar
dotgrammar is our high-performance library for constraining LLM output to match a predefined grammar in EBNF, tree-sitter or Lark format. Available under a commercial license with a Python, C, C++, or Rust API.
Use cases: consistently formatted reports, support for domain-specific language, messaging protocols.
We make LLMs speak the language of every application
New rules for AI
Every powerful system begins the same way: with rules. Rules as a language, a protocol, a way for parts to fit together into something greater. The history of software is really a history of this idea: from UNIX pipes to API contracts to typed programming languages, composability has always been the path to scale.
But large language models broke that pattern. They’re powerful, but unpredictable. Flexible, but fragile. And without structure, their outputs don’t compose, they just accumulate noise. Despite their tremendous capabilities, LLMs remain unrealized potential.
That’s why we built .txt: to make LLMs predictable, programmable, and production-ready. We give developers the tools to define exactly how LLMs should respond, using clear, typed schemas that turn loose generations into reliable outputs. Our technology, structured generation, helps teams design safer, more reliable AI outputs from the ground up. Not by patching errors after they happen, but by preventing them entirely.
The result? Fewer mistakes, less wasted compute, and systems that finally feel like software: callable, composable, and testable like any other part of your stack.
Start using .txt today and start building AI systems that actually work. Join the developers who are already building the next generation of reliable, production-grade AI applications.
Talk to our team
Want to see a demo?
Fill out this form and we'll follow up with next steps.