Promptotype

What Promptotype is

Promptotype is a web-based SaaS platform for developing, testing, and refining structured tasks for large language models. Its playground lets users build prompt templates and configure models, including function calling. Users can pair test queries with expected values or JSON schemas, then run a model query to fill in an expected result. The JSON Schema Editor supports schemas compatible with the OpenAI API’s json_schema response_format.

Promptotype supports testing prompts across query collections, from smaller development groups to larger production-readiness checks. It also keeps a history of runs and tests, offers scheduled automated checks with result summaries by email, and can create fine-tuned models from query collections. The Professional plan includes 60 days of query and collection run or test history, fine-tuning, and one weekly scheduled run. The free plan costs nothing; Basic is $6 a month and Professional is $10 a month, both billed monthly. A contact-based Team offering adds collaboration, periodic collection tests, and debugging of failed production queries. Promptotype is made by Baionic, LLC, which identifies itself as a Delaware corporation with a New York, New York mailing address.

Who it suits

Promptotype suits developers building structured LLM tasks who want to design prompts, test expected outputs, and run checks across query collections. Teams needing shared work, periodic collection runs, or a way to send failed production queries for debugging can consider its contact-based Team offering.

Limits

The Free plan includes the playground, expected-result testing, and code generation from playground input. Collection testing and libraries for prompt templates, model configurations, and queries are listed under Basic, which costs $6 a month.

Getting started

1. Open the Promptotype website.
2. Use the web platform.
3. Start with the Promptotype Free plan at no cost, or choose Basic at $6 a month or Professional at $10 a month, billed monthly.
4. Build a prompt template and configure a model in the playground.
5. Define test queries with expected values or JSON schemas, then run a model query to fill an expected result.

Verdict

Choose Promptotype to develop structured LLM tasks with prompt templates, expected-output checks, and collection testing. Its free plan covers playground work and test queries, while Basic adds template, model configuration, and query libraries plus collection testing. Consider the Team offering for collaboration and debugging failed production queries; its price is contact-based.