On-Device Model Execution
Run quantized models on local CPU/GPU hardware. Private conversation and workspace data never leave the machine without explicit operator routing.
Partial private Windows companion
Local Intelligence · no public installer
Local Intelligence currently combines local-model conversation, speech, presence, bounded Desktop file access, and durable task records. A narrow file-open workflow is accepted. Wider Windows control and scoped file transactions are still under verification and are not deployed.
| Working privately | Under acceptance | Planned |
|---|---|---|
| Conversation, speech, presence, bounded Desktop find/read, and durable task records. | Scoped file edit/copy/move/rename, recovery, packaging, and real Windows acceptance. | Wider app/window/settings control, business and email tools, public package, and portable Linux adapters. |
The private build can converse, speak, track durable tasks, and perform a narrow file-open workflow. Broader application, window, settings, and business workflows are not shipped.
Private models run directly on your hardware. Short, measured context packets keep execution fast and prevent memory bloat.
Actions are strictly bound to declared project directories. The engine is architecturally blocked from scanning unapproved drives.
Tasks maintain a persistent lifecycle (queued, running, paused, draining cancel, completed) that survives system restarts.
Worker claims of success are treated as unverified hypotheses. Independent artifact SHA-256 hashing and test suites certify completion.
Run quantized models on local CPU/GPU hardware. Private conversation and workspace data never leave the machine without explicit operator routing.
Every automated action is isolated to registered project directories. The application cannot invent paths, guess directories, or touch unapproved partitions.
Tasks possess durable state machines outside the model's context window. Pausing, canceling, or rebooting preserves exact task progress and audit trails.
Independent verification engines confirm that declared output files exist, match expected cryptographic hashes, and pass automated acceptance tests.
Local Intelligence prioritizes deterministic safety and auditability over unchecked generative autonomy.
Ask about Local Intelligence.
Private local operator app, project scopes, task progress, and verified artifacts.