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HACK

MATRIX

Virtual Desktop Pet & AI Assistant

Domain : Open Innovation

Team : CODING ROCKERZ

· Anmay Sunil Nayak

· Mohammed Nabeel Shaikh

· Ananya Bhat

· Amrutha Pai

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THE PROBLEM

Reminder apps are plain, generic utilities with no personality or engagement

They’re completely disconnected from what user is actually doing on screen.

Users get no contextual help – its just notification then silence.

Who is affected?

Desktop power users & Remote workers → Teams relying on individual productivity → Workplace focus & Task-completion culture

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WHY THIS PROBLEM EXISTS

Reminder

tools built as isolated localities

Privacy concerns discourage screen-aware features

AI assistants live in browser tabs not in desktop

->

No Context Awareness

Re-explains context each time

Lost focus

->

->

Current Approach:

Manual Notes → App Switching → Delay → Missed deadlines

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OUR SOLUTION

INTRODUCING Virtual Desktop Pet & AI Assistant

Enables desktop users to stay focused & get contextual help by pairing a companion pet with privacy first & screen-aware AI assistant

USER

Question or reminder request

Virtual Desktop pet & AI Assistant

AI reads screen context + question

Chat answer / Reminder alert

Stays on track , less context switching

Core capabilities

Capability Value

01 [smart reminder] [recurring alert with pet animation ,so alerts feel alive]

02 [Contextual AI assistant] [ask about your screen ,get real answer]

03 [Privacy-first design] [Capture only on consent,always visibly active]

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PROTOTYPE / PRODUCT EXPERIENCE

User journey

01 — INPUT

User ask pet a question,optionally selecting a window/screen to share.

02 — PROCESS

AI analyzes the captured screen context alongside the question

03 — OUTPUT

Answer appear in the pet’s chat bubble

04 — ACTION

User acts on the answer-or later,the pet fires the reminder with its alert animation.

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WHAT MAKES US DIFFERENT?

WHY THIS APPROACH?

Existing Approach Virtual Desktop pet & AI Assistant

Reminders are isolated from screen context ✓

No AI assistance built in ✓

Generic non customizable interface ✓

No visible privacy indicators during data use ✓

API keys often stored in plaintext/cloud synced ✓

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TECHNICAL ARCHITECTURE

Tech stack:

Frontend :

Flutter(windows desktop)

Riverpod(state management)

Rive/Lottie(pet animations)

Window_manager,tray_manager

Backend :

Dart isolates/Timer

hotkey_manager,screen_capturer,dio(hotkey,capture,AI API calls)

Storage :

Isar/Hive

flutter_secure_storage

Deployment :

Flutter build windows

MSIX/Inno setup installer

NO cloud server – fully local +direct AI API calls

Workflow Image

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FEASIBILITY + IMPACT

FEASIBILITY

IMPACT

Technical

1.Flutter-desktop – production ready

2.Screen capturer,isar,flutter-secure-storage

3.BYO AI API key via dio

Operational

DEV-machines+personal API keys

Local installer , no servers

Hackathon MVP

PET UI + Animation

Reminder CRUD +notification

AI screen+ Q&A with consent

Who benefits?

Desktop users, students,remote workers

What improves?

Faster counter recovery

Fewer missed reminders

Why does it matter?

Less cognitive overhead-less app switching

Then a bottom progression:

Prototype → MVP → Pilot → Scale

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Real-world pilot

NEXT MVP

User testing

Reliability

API key security review

UI refinement

LATER Deployment

Public windows release

Real-world pilot

Usage analytics

IMPLEMENTATION ROADMAP

NOW

Pet window +animation

Reminder CRUD+notification

Screen capture+ AI Q&A FLOW

Consent dialogue +privacy indicator

WHAT HAPPENS NEXT?

SCALE

Expansion

More AI providers

Macos/Linux support

More pet

customisation

Critical point Clearly separate:

Already built->the Now colums (pet window+ animations ,Reminder CRUD +notifications,screen capture +AI Q&A flow ,consent dialog +privacy indicator) vs.

Planned-> NEXT ,LATER, and SCALE columns

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TEAM + EXECUTION

Anmay Nayak

Desktop window and Backend engineer

Mohammed Nabeel Shaikh

AI Integration Engineer

Ananya Bhat

Testing and documentaion

Amrutha Pai

UI/UX