Kernel console / Today

Your companion, in context.

A living foundation for memory, intent, and private intelligence.

Memories⌁
0organized long-term signals
Context window◒
68%working memory available
Sync health↗
Readylast checkpoint just now

Capture a signal

Give your kernel something to remember.

＋

Save a preference, a moment, or a working pattern. You stay in control of what becomes part of your companion.

Working memory

Active context

Live
Current focusBuild a trustworthy personal core

Primary goal · updated today

Last retrievalNo retrievals yet

Relevant memories appear here as your kernel learns.

Signal library

Recent memories

Device state

Local checkpoint

✓
This devicePrimary workspace
Ready

Your changes are persisted locally. Encrypted sync can be connected when you are ready.

Long-term memory

A library of what matters.

Three memory types keep facts, patterns, and moments distinct.

Phase 1 / Context engine

Assemble context before the model thinks.

A transparent working-memory pass selects the smallest useful slice of your personal kernel.

Build a context packet

What should the kernel help with?

⌘

The engine combines your active goal, relevant memories, and the current request without sending anything anywhere.

Runs locally against your saved memory library.

Your memory stays local until you explicitly run a Kernel response. The selected packet is then sent to the AI service.

01Recall with intent

Prompt words and pinned signals guide retrieval.

02Keep it compact

A token budget prevents context bloat.

03Show the trace

Every source is visible before inference begins.

Inference router

Choose the right brain for the moment.

A transparent decision layer balances privacy, speed, capability, and cost.

Route a request

See the kernel decide.

⇄

Evaluate runs a live AI request only when the route allows cloud inference. Sensitive requests stay blocked until a local model is available.

Decision trace

Waiting for a request

Ready
◎

Describe a task and the kernel will show its reasoning path here.

01Privacy before convenience

Sensitive context stays on-device.

02Fast by default

Local models handle the everyday.

03Quality when it counts

Cloud power is an explicit escalation.

12-month build map

From private core to ambient companion.

A measured path for making intelligence persistent, portable, and proactive.

01
In progressMonths 1–3

Core kernel

Local persistence, context paging, semantic retrieval, and explicit preference learning.

SQLiteLocal modelsRAG
42% mapped
02
PlannedMonths 4–6

Multi-device sync

CRDT-based merging, encrypted backup, and seamless handoff across devices.

CRDTsE2E encryption
03
PlannedMonths 7–9

Edge–cloud hybrid

Capability-aware routing, model escalation, and personal adapters.

Smart routingLoRA adapters
04
PlannedMonths 10–12

Ambient intelligence

Permissioned background context, voice access, and proactive assistance.

On-device voicePermissions