Grand Prize
Globot
Multi-Agents. 2M-token compliance analysis. Satellite imagery risk detection. Globot turns sudden supply chain chaos into confident decisions in 60 seconds.
Core trick
Gemini vision reads satellite imagery for port congestion, and a red-team agent challenges each routing decision before it is applied.
Built with
chromadbclerkcrewaideck.glfastapigemini-3-flashgemini-embeddingsgemini-visionpythonreactsqlitetypescriptvitewebsocket
Description
Inspiration
On a Friday at 4:55 PM, the Red Sea crisis erupts. You're responsible for $50 million in cargo, drowning in Excel spreadsheets while Reuters updates flood in. Your boss is yelling. What do you do?
This scenario inspired
Globot
— an Agentic AI system that transforms reactive crisis management into
proactive defense
.
What it does
Globot is a
5-Agent AI Reasoning Engine
powered by Gemini 3 that:
🔭
Market Sentinel
: Monitors geopolitical signals from Reuters/Bloomberg in real-time
🛡️
Risk Hedger
: Calculates financial impact of route changes (fuel costs +$180K, freight volatility)
🚢
Logistics Orchestrator
: Automatically replans shipping routes to avoid conflict zones
📋
Compliance Manager
: Analyzes 500-page insurance policies using Gemini's 2M token context window
⚖️
Adversarial Debate
: Red-team tests every decision to prevent AI hallucinations
Key Innovation
: We use
Gemini Vision
to analyze satellite imagery, detecting port congestion and canal blockages 6 hours before official announcements.
How we built it
Backend
: Python + FastAPI + CrewAI (Multi-Agent Orchestration)
Frontend
: React + TypeScript + Deck.gl (3D Globe Visualization)
AI
: Gemini 3 Flash (Reasoning) + Gemini Vision (Satellite Analysis) + Gemini Embeddings (RAG)
Auth
: Clerk (Enterprise-grade authentication)
Database
: SQLite + ChromaDB (Vector Store)
Challenges we ran into
aiohttp Compatibility
: Python 3.13 introduced breaking changes; we implemented monkey patches to maintain CrewAI compatibility
Long Context Window
: Feeding 500-page legal documents required careful prompt engineering
Multimodal Reasoning
: Getting Gemini Vision to output structured risk assessments from satellite images
Accomplishments we're proud of
Visual Risk Intelligence
: First supply chain AI to use satellite imagery for early warning
Explainable AI
: Every decision shows a transparent Chain-of-Thought reasoning process
Human-in-the-Loop
: All critical decisions require human approval — responsible AI in action
What we learned
Gemini's multimodal capabilities enable use cases impossible with text-only models
Long context windows unlock enterprise document understanding
Multi-agent systems are more robust than single-model approaches
What's next for Globot
Integration with
Bloomberg Terminal API
for live market data
MarineTraffic API
for real-time AIS ship tracking
Sentinel-2 Satellite API
for automated port monitoring
Expansion to
air freight
and
rail logistics
README excerpt
# Globot
[](docs/assets/award-gemini3-grand-prize.png)
[](https://github.com/Vector897/Globot/stargazers)
[](https://github.com/Vector897/Globot/network/members)
[](https://github.com/Vector897/Globot/actions/workflows/ci.yml)
[](LICENSE)
[](backend/requirements.txt)
[](frontend/package.json)
[](https://www.crewai.com/)
[](https://deepmind.google/technologies/gemini/)
[](https://deck.gl/)
> ### 🏆 **Ranked #1 overall — combined technical execution and business value — among 4,499 projects built by 35,508 participants worldwide at the Gemini 3 Hackathon.**
<p align="center">
<a href="docs/assets/award-gemini3-grand-prize.png">
<img src="docs/assets/award-gemini3-grand-prize.png" alt="Globot — Grand