# 6.4 Assessing data and model maturity Before you start creating or using a language technology solution, it's important to check how good the NLP components you're using are. This includes the pre-trained models or the data you use to train them. This initial check helps ensure that your solution is strong and works well in real situations. Whether you're working on machine translation (MT), automatic speech recognition (ASR), or using large language models (LLMs) for natural language generation, it's crucial to evaluate how good your data and models are before getting started. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://4bcplaybook.clearglobal.org/6.-language-technology-implementation/6.4-assessing-data-and-model-maturity.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.