Local LLM inference
About Local LLM inference
The Aresto daemon runs supported models on the device, manages their memory, and exposes one system interface to agents and applications.
Aresto OS
Agents are the execution layer.
Aresto OS gives software memory, schedules, tools, and explicit permissions. It plans, acts, and brings you finished work while authority stays with you.
Not another assistant
An assistant waits for a question. Aresto's agents work from the context, schedules, and capabilities you give them, then return with the result.
The Aresto daemon runs supported models on the device, manages their memory, and exposes one system interface to agents and applications.
Agents work from a shared layer of decisions, preferences, files, relationships, and outcomes instead of rebuilding context in every application.
Tune behavior with persistent instructions, model choices, tools, examples, feedback, and review rules. Supported workloads can add deeper model adaptation.
Agent Studio turns a described role into a configuration with named tools, permissions, and interface scope. This system is in development.
Speak a direction or deliberately show the camera what matters. Touch and keyboard stay available for precise review and correction.
Network access is opt-in and scoped. Agents run in sandboxes, request named capabilities, and fail closed when access is missing.
Time, events, and completed work can wake bounded workflows, so useful preparation begins without another prompt.
Review what ran, which capabilities an agent used, what changed, and where approval is still waiting.
Choose local, connected, or automatic routing. The daemon handles model selection and switching through one interface.
Traditional shell commands and natural-language instructions share one terminal, with direct controls for modes and system status.
Native Linux software sits beside AI-native .aresto applications whose manifests declare tools, permissions, and interface scope. The .aresto model is in development.
Fifty agents arrive prepared for the research, drafting, analysis, preparation, and follow-up common to professional work.
Context, carried forward
Aresto remembers the decisions behind the files, the preferences behind the edits, and the way your work moves from one person to the next. It starts closer to useful.
One intelligence layer
The OS coordinates memory, inference, tools, and schedules across the whole system. Intelligence can be local or connected. Every action still crosses the device's permission boundary.
Authority is the architecture
Every capability is granted explicitly, every important action is visible, and every grant can be revoked. Agents fail closed when access is missing.
Aresto OS
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