A local LLM is a large language model that runs on infrastructure you control, such as your own servers or private cloud, instead of through a third-party service. Prompts, documents, and answers all stay inside your network.
Open-weight models can run on GPU hardware in your own data center. You give up some capability and convenience in exchange for full control over where your data lives, how fast responses come back, and what it all costs.
Organizations with strict data policies, regulated content, or classified environments often can't send equipment documentation or service data to an outside AI provider.
ResolveGrid's on-premises and air-gapped options can run on local LLMs. Workflows, computer vision, and expert escalation work the same as in the cloud, while AI model capability depends on the hardware you run it on.