# For Developers NeurochainAI provides a variety of services for developers building on the infrastructure such as: * **AI models**: Ready-to-use AI models (LLM, Text-to-Speech, Speech-to-Text, Image generation AI, custom proprietary models) as a service with Pay-as-you-Go pricing. * **Decentralized inference network:** Community-powered decentralized GPU network for scaling your AI models and solutions. * **Model fine-tuning**: Models fine-tuning for more accurate results on your datasets. * **Train your own models**: Infrastructure to train your own model with your dataset. * **Data-as-a-Service:** High-quality datasets for AI model training for various purposes. * **Datasets-validation-as-a-Service:** Validate your dataset using community feedback to bring it to the highest quality. * **Model-validation-as-a-Service:** Validate your AI model results via community feedback. * **SDK tools:** An all-in-one package of libraries, a compiler, and a debugger, it simplifies deployment and eliminates the need for base-level coding. * **Profit from your AI models:** Contribute your AI models and earn royalties every time someone is using them in their projects. * **Growing customer base**: A growing interest in the AI dApp store is a source of business for your AI solutions. * **Community:** Growing together and helping each other along the way. We also have a grant program for developers and businesses interested in saving time and cost for building AI solutions. Find all information here: --- # 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.neurochain.ai/nc/services-and-products/for-developers.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.