Metatext leverages AI to classify and extract information from text and documents using custom-trained Large Language Models (LLMs). Tailored for diverse applications such as customer email categorization, legal contract analysis, and report summarization, it offers a user-friendly, no-code interface for effortless model fine-tuning. With capabilities spanning Binary, Multi-class, Multi-label, Sentiment, Topic, and Intent classifications, Metatext empowers users to create private, scalable models efficiently. It excels in extracting key information, identifying entities, and recognizing keywords. Moreover, the platform supports domain-specific text generation tasks like Question & Answering and chatbot development. Metatext streamlines model training with minimal data and annotation requirements, ensuring robust evaluation and reliable deployment integration. Its API, alongside integrations with Zapier, Google Sheets, Docker, AWS, and Hugging Face, facilitates seamless system integration. The platform's task-specific LLMs automate workflows across sectors including customer support, content moderation, healthcare, finance, and HR, enhancing operational efficiency. This SEO-optimized version aims to enhance search engine visibility while maintaining clarity and originality, helping users discover Metatext's powerful capabilities in text analytics and AI-driven automation.