What the term really means
A Large Language Model is trained on large text collections and can analyse and generate language.
How it works in practice
An LLM can analyse and produce language but is not a source of truth for a company, inventory or current law without appropriate evidence.
The decision to make before implementation
Choose a model for the task; larger is not always better when latency, privacy or predictable cost matters.
How to verify that it works
Compare quality on your own cases, languages, context length, tools, safety, cost and version stability. Compare results with an agreed baseline and review routine cases, difficult exceptions and human hand-offs separately. A practical LLM test should have an owner, a review date and a recorded example of an outcome the team will not accept.
The PAR HOUSE Agency approach
We approach LLM from the workflow rather than a tool demonstration. Choose a model for the task; larger is not always better when latency, privacy or predictable cost matters. We then build a small measurable scope, record assumptions and expand only after quality review.
