What Is NLP (Natural Language Processing)?
NLP is AI that works with human language: classifying, extracting, summarising and generating text. How it relates to LLMs and where it's used in business.
Natural language processing (NLP): the field of AI concerned with understanding and generating human language (classifying text, extracting information, summarising, translating and answering) that today is largely powered by large language models.
Natural language processing (NLP) is the field of AI concerned with understanding and generating human language (classifying text, extracting information, summarising, translating and answering) that today is largely powered by large language models.
NLP covers tasks like sentiment analysis, entity extraction, classification, summarisation and question answering. Modern LLMs handle most of these flexibly, but focused, cheaper models still win for narrow, high-volume tasks like routing or tagging.
Why it matters
Most business text (tickets, contracts, emails, reviews) is unstructured and underused. NLP turns it into structured signal you can act on: route this ticket, flag this risk, summarise this thread. Choosing between a big general model and a small focused one is a real cost-and-latency decision.
How Finzarc thinks about it
We apply NLP pragmatically: an LLM where flexibility pays, a small model where volume and cost rule. See intelligent document processing and what we build.
Related
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Questions, answered.
What is natural language processing?
NLP is AI that understands and generates human language, classifying, extracting, summarising, translating and answering, today largely powered by large language models.
Is NLP the same as an LLM?
NLP is the field; LLMs are the current dominant tool for it. LLMs handle most NLP tasks flexibly, but smaller focused models still win for narrow, high-volume jobs like routing or tagging.
What is NLP used for in business?
Turning unstructured text (tickets, contracts, emails, reviews) into action: routing, entity extraction, risk flagging, sentiment and summarisation. Most business language is underused signal.
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