Natural Language Processing (NLP)

BERT answers questions better than humans. 93.2 vs. 89.5 F1 score on the SQuAD benchmark. That is natural language processing (NLP): machines that read, understand, and process human language.

What NLP actually does

Named Entity Recognition (NER) identifies people, places, and companies in text — state-of-the-art F1 above 93%. Sentiment analysis determines whether a customer review is positive or negative, current models exceed 95% accuracy. Machine translation (DeepL, Google Translate) is also NLP.

The leap to large language models

Classical NLP trains a specialized model per task. LLMs like GPT and Claude handle all these tasks with a single model. The Transformer architecture from 2017 enabled that shift. NLP as a discipline has not disappeared — it lives inside every LLM.

Where businesses benefit

The NLP market: $37-53 billion (2025). Financial services hold 21% market share — for contract analysis, compliance screening, risk assessment. Healthcare grows fastest at 24% annually.

The quickest entry point: document classification. Sorting emails, searching contracts, analyzing customer feedback. All tasks that can be automated in weeks. We help you get started.