claude-local-memory

To deploy offline AI with local-first memory, assess the client environment and configure a private memory layer. This process includes environment assessment, local agent stack recommendation, and private memory configuration for offline scenarios.

A privacy-first memory layer is a local storage system that preserves client privacy during offline AI operations. It configures holographic, mem0, or local files-only memory backends to ensure data remains on the client machine without external transmission.

Yes, you can use Ollama or llama.cpp for an offline agent setup. The Skill recommends the Ollama or llama.cpp stack combined with a local memory backend to maintain privacy and operate without external internet connectivity.

Yes, local AI deployment requires specific hardware capabilities. The Skill evaluates OS, RAM, disk space, and GPU or CPU capabilities during the client environment assessment to ensure the machine supports offline agent operations.

The cost to configure a local-first AI deployment ranges from $29 to $99, plus a $9 monthly maintenance fee. The Skill provides a setup runbook and an invoice template to deliver pricing for the privacy-first memory configuration.