# Predicting {% hint style="info" %} We are currently working on POCs for prediction. If you are interested in starting a POC or becoming a design partner to have your hands on the **Blocktorch Fire Beetle Prediction** first and shape its roadmap please [let us know](mailto:contact@blocktorch.xyz) {% endhint %} **Blocktorch's Fire Beetle Prediction** will be key in improving observability, making web3 DevOps more efficient, and increasing threat detection. By using advanced analytics and machine learning, blocktorch's predictive models can guess future system issues, allowing teams to deal with them before they cause problems. Blocktorch's proprietary prediction helps you spot unusual behavior and track performance changes for a quicker reaction. Furthermore, the algorithms can predict workflow slowdowns and help manage resources better. Especially for threat detection blocktorch's prediction is a valuable , spotting possible security issues early, lowering the chances of breaches and allowing for early action. Adding prediction into these areas in your engineering workflows can boost productivity and strengthen system security. {% hint style="info" %} The black fire beetle is an insect, with sensor design with the ability to detect flames perhaps as far as 80 kilometres away. It can also hear the cracking of the wood and sense combustion products in very small amounts by using supersensitive receptors which are located in tiny pits on the beetle’s chest receptors. {% endhint %} --- # 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://docs.blocktorch.xyz/use-cases/predicting.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.