Use this page to understand what HOM Local actually stores, how recall is grounded, and when local-first is the right move.
It keeps decisions, evidence, sessions, tools, and model choices connected so work can continue without constant manual re-briefing.
Keep the decisions, constraints, session notes, and evidence that reduce restart time on the next task.
Get context back with confidence and evidence, not raw text chunks that still leave the operator guessing.
Resume work across sessions, models, and agents without rebuilding the project context from scratch.
HOM helps AI keep the context that makes work move while keeping the persistent brain under the user's control.
The goal is a native local workspace, not a web UI. The app is where you chat, inspect memory, manage providers, review agents, and control privacy.
You work with AI directly. Memory, evidence, and confidence appear when they matter.
Inspect memories, evidence paths, related context, and the way the brain is organizing work.
Past sessions can be summarized, searched, inspected, and brought back into current work.
Provider choice, local ownership, learning controls, export, and privacy belong in the app, not hidden behind an account portal.
HOM screens what enters memory, keeps evidence attached, and returns context with confidence so operators can understand what the AI is relying on.
Low-signal material should not pollute the brain. HOM is built around saving what matters.
Answers should point back to the memories and signals that supported them.
When evidence is strong, the product can say so. When evidence is thin, the user should know.
Old context should remain reachable. Useful context rises, weak context recedes, but memory is not casually erased.
Patterns, corrections, and repeated recalls help the brain become more useful with continued work.
The point is not mystique. The user should be able to inspect why a memory came back.
HOM Local is not memory plus chat history. It is a workspace where tools, skills, sessions, and agents can share one remembered working state.
AI work can call tools and use workflows without losing the memory of why a task exists.
Reusable capabilities should be available to the agent while still feeding the same memory system.
Agent contributions should be attributable, inspectable, and constrained by the product's memory rules.
The project is the continuity anchor. Sessions become part of the project brain instead of disappearing into history.
HOM Local keeps the brain separate from any single provider. Use local models for private work, cloud models when useful, and keep the same persistent working memory across switches.
Changing models should not mean losing the project, the decisions, the evidence, or the learning history.
The practical question is simple: where should the brain live today, and who truly needs access tomorrow?
Free personal edition. The brain lives on your machine. Best for individual AI work and privacy-first building.
Coming soon for cross-device access, shared workspaces, hosted memory, and support.
Planned for organizations that need governed memory, auditability, residency, and deeper control.
HOM Local is designed so the personal brain starts on the user's machine. Outbound model calls only belong to providers the user chooses.
Memory is portable and not training data for someone else's product.
A memory product must let users leave with their memories intact.
Cloud providers and connected tools should be user-chosen, visible, and revocable.
The docs follow the same rule as the product: keep the important context close and make the next step clear.