LLMOps covers running an LLM application in production: quality monitoring, cost control, logging, security and shipping updates without losing control.
How to use the term
What to read alongside
This term is worth reading together with the neighbouring concepts in its section and the Gravity AI launch scenarios it belongs to.
Glossary section
What it takes for an AI scenario to work outside the demo: quality measurement, experiments, operations and control over the economics.
What it is
LLMOps covers running an LLM application in production: quality monitoring, cost control, logging, security and shipping updates without losing control.
Example in ecommerce
For an AI assistant that means tracking answers, errors, latency, cost, relevance regressions and data incidents.
Business impact
Lowers the risk of production failures and keeps the scenario manageable at scale, not only in a pilot.
A fit for terms about search by meaning, the architecture behind the results and product discovery.
Shows how AI terms turn into a real decision flow inside the product page.
Collects the product scenarios in one place and is the starting point for a demo.
We will show which scenario to start with, how to tie it to metrics and where measurable results come fastest.