How I Built an AI Personal Safety & Emergency Assistant Using Multi-Agent Systems
The 5-Day Google & Kaggle AI Agents Intensive Course was one of the most transformative learning experiences I’ve had. I came into the course excited but unsure about how complex multi-agent systems really work. By the end, I built a complete AI Personal Safety & Emergency Assistant—a multi-agent emergency detection system that analyzes risk, triggers alerts, and assists users during dangerous situations.
This post is a reflection on what I learned, how the course changed my understanding of agentic AI, and how I built my capstone project.
What I Learned From the 5-Day Intensive
Before this course, my idea of “agents” was very basic. But the training revealed how powerful AI agents are when combined:
Day 1 — The Fundamentals
I learned the foundations: reasoning loops, agent instructions, routing, and agent orchestration.
Day 2 — Tools
This day taught me how agents use tools to extend their abilities beyond text — a key concept I used later to build simulated SMS, email, and call alerts.
Day 3 — Memory
This unlocked a turning point for me. Agents that remember past interactions behave more intelligently.
I implemented risk trend detection where repeated danger messages trigger escalation.
Day 4 — Evaluation & Observability
This taught me how to test, track, and debug agent behavior — essential for safety systems.
Day 5 — Agent-to-Agent Communication
I learned how agents can collaborate to form a full workflow.
This is what allowed me to design a multi-agent pipeline for emergency response.
My Capstone Project: AI Personal Safety & Emergency Assistant
Inspired by real-world safety challenges, I built a system that acts when people can’t call for help themselves.
Problem
Millions face emergencies where they are unable to call or message family or police.
Seconds matter — and AI can react faster than humans.
Why Agents?
Agents fit this problem because they can:
- Detect danger from text inputs
- Decide the correct action
- Trigger emergency-like responses
- Guide users step-by-step
- Escalate automatically when needed
Traditional chatbots cannot do this. Agents can.
Architecture I Built
My system includes three cooperating agents:
1. Risk Detector Agent
Classifies messages as:
- SAFE
- EMERGENCY
2. Action Planner Agent
Decides what to do:
- reassure
- ask more details
- escalate to emergency mode
3. Responder Agent
Provides urgent step-by-step instructions in critical situations.
Memory Module
Tracks:
- previous messages
- previous risk levels
- escalation patterns
Tool Simulation
I built safe simulated tools:
-
send_sms_alert() -
send_email_alert() -
send_call_alert()
Gemini Integration (Mock Model)
Demonstrates:
- danger classification
- emergency message generation
All of this was done inside a Kaggle Notebook.
What I Tested
I evaluated my agents across scenarios:
- Clear emergency (“I am bleeding, please help!”)
- Safe message (“I reached home safely.”)
- Ambiguous risk
- Escalating danger (“Someone is following me → I am in danger → He is attacking me”)
The system behaved consistently, escalated correctly, and triggered alerts responsibly.
What This Project Taught Me
1. Multi-agent systems are extremely powerful
Combining simple agents created a system far more intelligent than a single model.
2. Memory changes everything
The moment agents remember context, their decisions become smarter.
3. Tools transform agents into action-takers
Even simulated tools felt like building the foundation of a real safety product.
4. Clear instructions matter more than code
The course proved that well-written agent instructions are as important as model power.
If I Had More Time
I would add:
- Voice-based danger detection
- GPS-based location alerts
- Mobile app interface
- Real API integrations (Twilio, WhatsApp)
- Deployment on Cloud Run / Agent Engine
Final Thoughts
The Google × Kaggle AI Agents Intensive didn't just teach me agents —
It taught me how to build impactful, real-world AI systems.
My capstone project, AI Personal Safety & Emergency Assistant, is only the beginning.
And this course has opened the door to a new world of possibilities.
Thank you Google, Kaggle, and the entire AI Agents community.
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