Dottxt provides an API that ensures large language model outputs conform to user‑defined schemas such as JSON Schema, regex patterns, or context‑free grammars, eliminating the need for post‑processing and retries. Its dotjson, dotgrammar, and dotlambda libraries integrate with any inference stack to deliver deterministic, schema‑compliant data for production AI applications.
Funding
$8.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
7OFounders
Product
Problem
Developers integrating large language models into production systems often face unpredictable output formats, requiring extensive post‑processing, retries, and validation to enforce schemas such as JSON or custom grammars. This unreliability hampers deployment speed, increases error rates, and adds operational overhead.
Solution
Dottxt offers an API platform that guarantees each LLM response conforms to a predefined schema by construction. Users specify schemas in JSON Schema, regular expressions, or context‑free grammars, and the service generates compliant data without the need for defensive parsing or retry loops. The platform also provides composable libraries—dotjson for JSON Schema enforcement, dotgrammar for arbitrary grammars, and dotlambda for reliable function calling—that can be integrated into any inference stack. By delivering per‑call reliability, Dottxt enables developers to embed LLM capabilities into production pipelines with confidence and reduced engineering effort.
Target Audience
Primary customers are software engineers and product teams building AI‑enabled applications that require deterministic, schema‑compliant LLM outputs, as well as inference service providers seeking to add structured generation capabilities to their platforms.
Features
- API endpoint that produces outputs matching user‑defined JSON Schema, regex patterns, or context‑free grammars
- dotjson library for seamless JSON Schema enforcement within existing inference pipelines
- dotgrammar library that parses and enforces arbitrary context‑free grammars during generation
- dotlambda module enabling reliable function‑calling patterns from LLM outputs
- No‑retry generation: outputs are correct by construction, eliminating validation loops and defensive parsing
- Compatible with any LLM model, including open‑source and commercial providers
- Simple three‑step integration workflow (define schema, call API, receive structured result)