Definition: Natural language processing (NLP) is the field of AI and linguistics that enables computers to read, interpret, analyze and generate human language in text or speech.
Classification (topic, sentiment, intent), named entity recognition, information extraction, translation, summarization, question answering and text generation.
Early NLP relied on hand-written rules, then statistical models over word counts. Neural models and word embeddings followed, and transformers made today's large language models possible. LLMs now handle many tasks that once needed a separate model, though compact specialized models can still be faster and cheaper for high-volume classification or extraction.
Real-world text is messy: scanned documents, abbreviations, multiple languages and domain jargon. Production systems combine OCR, tokenization, models and validation rules, and are measured against labeled test sets. Evaluation should cover every language, channel and document type the system will actually see.
Ryz NLP engineers build extraction, classification and language systems on your data, working on your team. One Ryz-built driver-support agent handles calls in three languages (case study).
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