Natural Language Processing (NLP)
The field of AI that enables computers to read, interpret, and generate human language. NLP is the foundation beneath every AI feature that touches text — document extraction, classification, search, summarization, and automated communication.
What is Natural Language Processing?
Natural Language Processing (NLP) is the branch of AI concerned with making computers understand and work with human language — written or spoken. It covers a wide range of tasks: recognizing what a sentence means, identifying entities (names, dates, amounts), classifying documents by type or topic, translating between languages, summarizing long texts, and generating coherent new text.
NLP is not a single algorithm. It is a collection of techniques — from rule-based pattern matching to neural networks trained on billions of documents. Modern NLP is dominated by transformer-based models (like the ones powering GPT and Claude), which learn language structure and meaning from massive training corpora rather than hand-coded rules.
What NLP Actually Does
Behind the scenes of most business AI features, NLP is doing the work. When an AI agent reads a supplier email and routes it to the right team, that is NLP. When a system extracts a due date from an invoice, that is NLP. When a search query returns semantically relevant documents instead of just exact keyword matches, that is NLP.
Entity extraction: Pull company names, amounts, dates, part numbers from unstructured text
Classification: Route incoming emails, tickets, or documents to the right category or queue
Summarization: Condense long contracts, reports, or email threads to key points
Sentiment analysis: Gauge tone in customer communications or supplier responses
Translation: Process documents in multiple languages without separate pipelines
NLP in Operations
For operations teams, NLP is what makes it possible to automate document-heavy processes without requiring every input to be perfectly structured. Purchase orders arrive as PDFs in varying formats. Customer complaints come as free-text emails. Supplier confirmations use different terminology for the same concepts. NLP handles that variation — reading intent and extracting meaning the way a trained employee would, but at the volume and speed a human team cannot match.