01 / ALA
Memory
Long-term personal memory
Organizes life data into retrievable, authorized memory assets.
How it is built
- Layered memory
- Relationship graph
- Local-first processing
Use cases
- Family albums
- Voice stories
- Cross-member Q&A
ALA / CAPABILITIES
Capabilities with purposeA clear result at every step
This page explains how ALA capabilities become product modules: lifelong memory, personality modeling, continuous evolution, future simulation, decision assistance, real-world collaboration, and digital legacy.
Design and prototype validation · Delivery in agreed phases
01 / EXPERIENCE
From an interaction to a useful result
Illustrative workflows only. No personal data is accessed and no real tasks are executed.
- 01
Ask: find last year's birthday photos
- 02
Check access: search only authorized albums
- 03
Match people and dates: return candidate records
- 04
Show sources: the user confirms, edits or refines
02 / MODULES
Seven product capabilities
Each capability maps to a concrete module across data organization, cognition, simulation, collaboration, and governance.
02 / ALA
Personalization
Coherent digital identity
Learns values, habits, preferences, and communication style.
How it is built
- Preference profile
- Expression style
- Versioned identity
Use cases
- Age-appropriate dialogue
- Family companionship
- Authorized communication
03 / ALA
Growth
Continuous capability growth
Updates with life stages, goals, and family changes.
How it is built
- Stage growth
- Skill expansion
- Feedback loop
Use cases
- Growth archive
- Family coordination
- Long-term agent
04 / ALA
Scenarios
Future scenario exploration
Compares paths and risks without replacing human decisions.
How it is built
- Scenario variables
- Path comparison
- Explainable output
Use cases
- Learning plans
- Family planning
- Option comparison
05 / ALA
Decision support
Personalized assistance
Provides advice while final decisions remain with the user.
How it is built
- Goal detection
- Option comparison
- Human confirmation
Use cases
- Purchasing advice
- Task priorities
- Family reminders
06 / ALA
Collaboration
Real-world task collaboration
Coordinates reminders, search, communication, content, and device actions.
How it is built
- Intent routing
- Multi-agent orchestration
- Device integration
Use cases
- Messages
- Learning support
- Local Agent tasks
07 / ALA
Digital legacy
Inheritable digital assets
Preserves experience, knowledge, stories, and creative output under authorization.
How it is built
- Asset archive
- Inheritance control
- Emotional continuity
Use cases
- Memory books
- Elder stories
- Knowledge legacy
03 / DELIVERY
Productization path
Deployment follows a terminal-first, edge-enhanced, cloud-coordinated route.
Home terminal
Handles daily interaction, voice messages, content display, and member identification.
Voice UIMember IDLocal display
Local AI node
Runs local inference, sensitive data handling, caching, and device linkage.
Local AgentPrivacy firstDevice linkage
Edge-cloud service
Provides heavy inference, model distribution, synchronization, and operations.
Model deliveryEdge inferenceOperations
04 / TRUST
Data sovereignty and ethical boundary
ALA must be authorized, explainable, revocable, and human-directed.
01Sensitive data is local-first by default.
02Voice, image, and persona use require explicit records and revocation.
03Children and elders require role boundaries and guardianship controls.
04Decision support explains assumptions and keeps final decisions with users.
Start with one clear use case
Define the people, devices and data boundaries. Together, we scope the first release, acceptance tests and delivery plan.