🛡️ ARGUS

Deterministic Energy Supply Chain Resilience Engine & Intelligence Platform

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📌 Strategic Overview

ARGUS is an advanced agentic intelligence platform built for ET AI Hackathon 2026 — Problem Statement 2: AI-Driven Energy Supply Chain Resilience. It enables geopolitical risk analysts and strategic decision-makers to model the cascading economic and supply-chain impacts of macro-level shocks to global maritime chokepoints (e.g., Strait of Hormuz, Bab el-Mandeb).

Rather than relying purely on generative LLM hallucinations, ARGUS utilizes a strict Agentic-to-Deterministic Pipeline: extracting unstructured threat signals, converting them to immutable mathematical states, computing real-world physics (SPR drawdowns, tanker lead times, elasticity-based price surges), and synthesizing the math back into a strategic intelligence briefing — all in under 6 seconds.

✨ Core Capabilities

🚢 Live Maritime Intelligence

• Real-time AIS Tracking: Integrates AISstream.io websockets to map live vessel traffic inside critical disruption corridors (e.g., Fujairah anchorages).
• Dark Zone Profiling: Actively correlates missing AIS data with IMF PortWatch to "own" AIS sparsity as a deliberate transponder-suppression finding.

🧠 Multi-Agent Fallback Architecture

• Primary Engine: Powered by NVIDIA NIM (meta/llama-3.1-70b-instruct) for rapid, high-accuracy extraction.
• Resilience Failover: If the primary AI engine faults or hallucinates (e.g., JSON markdown wrapping), ARGUS automatically falls back to Groq (llama-3.3-70b-versatile), ensuring the dashboard never crashes during a crisis simulation.

📉 Mathematical Cascade Engine

• Dynamic Elasticity Math: Converts raw volume loss (mbd) into dynamic supply-shock premiums.
• Heuristic Procurement Ranking: Evaluates global oil alternatives based on Landed Cost, Lead Time, and Sanctions compliance, re-routing supply chains instantly.

🕵️ D-SHIELD: Adversarial Audit System

• Every intelligence claim generated by ARGUS is challengeable. Users can click any synthesized sentence to launch an adversarial LLM audit (D-SHIELD), verifying the claim against the underlying mathematical state and extracting live sources.

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⚙️ System Architecture

graph TD
    A[Signal Trigger / Threat Query] --> B[Agent Pipeline: Extraction → Normalization → Validation]
    B -->|Structured JSON| C[Deterministic Cascade Engine]
    C -->|Supply Deficit mbd| D[Crude Price Surge Model]
    D -->|Elasticity Premium| E[GDP Impact & Pump Price Calc]
    D -->|SPR Drawdown Strategy| F[Heuristic Procurement Ranking]
    F -->|OFAC Sanctions Filter| G[Agent Synthesis & Briefing]
    G --> H[Next.js Dashboard + PDF Export]
    
    subgraph Live Data
        I[Serper.dev Web Search]
        J[EIA Spot Price API]
        K[AISstream.io WebSocket]
    end
    
    I --> B
    J --> C
    K --> H

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🖥️ Dashboard Features

Real-Time Signal Trigger

Submit disruption scenarios (e.g., "OPEC cuts production by 2mbd") via the signal panel. ARGUS timestamps the request and streams pipeline progress in under 6 seconds.

Agent Transparency Terminal

Every pipeline stage — extraction, normalization, validation, transformation, synthesis — is streamed live with color-coded log lines and timestamps. Full observability into how each number is derived.

Strategic Command Dashboard

Key metrics at a glance: Cost Delta per day ($675M+), Pump price surge (₹24.75/L), SPR drawdown rates, Vulnerability Index per chokepoint. Stacked area charts track supply deficits across crude, diesel, and gasoline.

D-SHIELD Audit Layer

Click any intelligence claim to launch an adversarial audit. D-SHIELD traces the claim back to its source OPEC announcement, pipeline transform, and deterministic model version — with confidence scores.

PDF Export

One-click export generates a comprehensive PDF report including the executive summary, disruption table, dashboard charts, and full pipeline trace for stakeholder review.

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🚀 Installation & Deployment

1. Backend Setup (FastAPI)

Navigate to the backend directory and set up your virtual environment:

cd backend
python -m venv venv
source venv/Scripts/activate  # (Windows)
pip install -r requirements.txt

Environment Variables (backend/.env):

NVIDIA_API_KEY=your_nvidia_key
GROQ_API_KEY=your_groq_key
SERPER_API_KEY=your_serper_key
EIA_KEY=your_eia_key
aistreamio_key=your_ais_key

Run the Backend:

uvicorn app.main:app --port 8000

2. Frontend Setup (Next.js)

Navigate to the frontend directory:

cd frontend
npm install

Environment Variables (frontend/.env.local):

NEXT_PUBLIC_API_URL=http://127.0.0.1:8000

Run the Frontend:

npm run dev

The ARGUS Intelligence Dashboard will be accessible at http://localhost:3000.

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🔒 Security & Resilience

• API Protection: All API keys are managed via environment variables (backend/.env). Live OSINT uses in-memory caching to prevent rate-limit exhaustion.
• Multi-Agent Fallback: Primary NVIDIA NIM (llama-3.1-70b) with automatic failover to Groq (llama-3.3-70b-versatile) if the primary faults.
• Network Stability: AIS WebSocket uses exponential backoff while True loops to survive server disconnections without dropping the client stream.
• Data Integrity: Strict regex filtering cleans markdown-wrapped JSON payloads from LLM responses.

"In geopolitical risk, confidence is nothing without calculation. ARGUS bridges the gap."