Why It Matters
Before LLMs, getting a computer to handle language tasks required building narrow, task-specific systems. One for translation. Another for summarisation. Another for classification. Each was expensive to develop and brittle when the input deviated from what it expected. LLMs changed this by providing a single foundation that can handle a wide range of language tasks out of the box. For businesses, this means access to capabilities that were previously only available to organisations with dedicated AI research teams. Drafting content, extracting data from unstructured documents, answering customer questions, and analysing feedback at scale are all now practical and affordable. See our AI development services for how we put this to work for clients.
Example
An accountancy firm receives hundreds of pages of client correspondence each week. Staff previously spent hours reading through emails and documents to identify action items and deadlines. Using an LLM integrated into their document management system, the firm now processes incoming correspondence automatically. The model reads each document, extracts key dates, obligations, and questions, and produces a structured summary for the relevant team member. Work that took an hour per client now takes minutes, and nothing falls through the cracks.
LLMs are a type of generative AI. Browse the full glossary for related definitions.
