Glossary · 1 minute read
What Is Natural Language Processing (NLP)?
Natural language processing (NLP) is the field of AI focused on enabling computers to understand, interpret, and generate human language. It covers tasks like classification, entity extraction, sentiment analysis, translation, summarization, search, and question answering. Modern NLP is powered largely by large language models, which handle many of these tasks with a single model and far less task-specific engineering than before. NLP turns unstructured text— emails, documents, chats—into structured, usable outputs and answers.
NLP is how computers work with human language. Here's what it is, what it does, and how large language models transformed what's possible with text.
What NLP is
Natural language processing (NLP) is the field of AI focused on enabling computers to understand, interpret, and generate human language.
What NLP does
| Task | Example |
|---|---|
| Classification | Sort emails by topic |
| Entity extraction | Pull names, dates, amounts |
| Sentiment analysis | Gauge tone |
| Translation | Between languages |
| Summarization | Condense documents |
| Search & Q&A | Answer from your data |
NLP turns unstructured text—emails, documents, chats—into structured, usable outputs.
How LLMs changed NLP
Modern NLP is powered largely by large language models, which handle many tasks with a single model and far less task-specific engineering than before. This made advanced NLP—summarization, Q&A, extraction—accessible to more teams. See hire NLP engineers.
Where it's used
NLP underlies chatbots, document AI, semantic search, and support automation—anywhere language is the input or output.
Still needs evaluation
Language is messy, so NLP systems need evaluation on real text to be reliable—the discipline that separates production NLP from demos.
Why FISTA
FISTA Solutions builds production NLP—search, extraction, summarization—with rigorous evaluation, through AI enablement, backed by 150+ projects across 12+ countries.
Building with language AI? Talk to FISTA.
Share-ready article cover
Download the generated social format.
Clear answers
Questions raised by this field note.
Straightforward guidance for evaluating scope, fit, and the next step.
01What is natural language processing?
The field of AI focused on enabling computers to understand, interpret, and generate human language—covering tasks like classification, extraction, translation, summarization, search, and question answering.
02What is NLP used for?
Search, chatbots, document understanding, sentiment analysis, translation, summarization, and extracting structured data from text. It turns unstructured language—emails, documents, chats—into usable outputs and answers.
03How have LLMs changed NLP?
Large language models handle many NLP tasks with a single model and far less task-specific engineering than before, making capabilities like summarization and Q&A far easier to build. They've made advanced NLP accessible to more teams.
Continue exploring
Related capabilities
Start with the hard problem
Need the outcome owned, not merely analyzed?
Tell us where delivery is constrained. We’ll map the fastest credible path from intent to verified production.