2026
Alos
UX/UI Design
Service Design
Overview
Alos is a service ecosystem designed to reduce isolation among Alzheimer's and dementia caregivers through meaningful peer support. Grounded in public health framework, the platform uses an empathetic NLP matchmaking system to connect individuals over shared daily struggles, personal diary entries, and community-verified coping strategies.
My contribution
Service framing & information architecture
Visual design system & interactive prototyping
Usability testing & user validation
Project’s scope
Public health service, AI matchmaking logic, mobile app, physical onboarding touchpoints.
Timeframe
4 months, February - June 2026
01
Research & Problem Framing
In Italy, around 4 million dementia caregivers face heavy daily burdens with minimal public system support. Through direct observations, field inquiries, and qualitative interviews, we mapped their lived journeys to uncover unmet emotional needs and identify critical service intervention touchpoints.
02
Core Insights
Lack of post-diagnosis support
Without guidance, caregivers are forced to improvise medical, legal, and daily care routines alone.
Need for pratical peer advice
Clinical guidelines often fail to address daily hurdles, creating a need for practical peer advice.
Need for safe spaces
Stigma around struggling hinders emotional openness, driving the need for a safe space outside family.
03
Service Concept
Framed as an institutional public health service, Alos translates peer-to-peer solidarity into an integrated ecosystem combining digital touchpoints, community tools, and intelligent matching.
Alos
The right peer by your side, exactly when it feels heaviest.
Diary
A quick daily check-in, a note in the moment, all kept safe in one place.
Chats
Stay close to those who've helped you, and those you can help next.
Discover
Guiding you to helpful hands, care networks, and local warmth nearby.
Badges
Keep going! Your efforts never go unnoticed.
Community
You're not in this alone.
Become part of something bigger.
04
AI System
Rather than replacing human interaction, the AI functions as a context-aware matchmaking engine. This recommendation system leverages the RAG paradigm to provide targeted context to an LLM via semantic search. The AI acts as an "augmented" decision engine, analyzing the retrieved texts from the databases to validate the matchmaking between caregivers and generate a tailored explanation for the proposed match.
05
Process & Validation
06
UI Design System
Key Learnings
End-to-end service design orchestration
Designing for high-vulnerability contexts
Human-centered AI matchmaking
Additional credits
Project developed with Diana Berselli, Cecilia Ferrentino, Agnese Pozzi, and Vittoria Volontè for Politecnico di Milano.