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⚡ PRODUCTINTEL SPOTLIGHT

The Goated Product Placement & ROI Intelligence Engine.

ProductIntel Spotlight is a high-fidelity analytics platform designed to quantify the impact of product placements in video content. By combining Llama-4 vision tracking with Gemma-4 marketing intelligence, Spotlight transforms raw video into actionable executive strategy.

Spotlight Dashboard (Placeholder: Update with real screenshot)


🚀 Key Features

1. Neural Masking Pipeline (SAM3)

  • Keyframe Interpolation: Uses meta-llama/llama-4-scout to identify and lock onto products every 1 second.
  • Temporal Precision: High-accuracy bounding box interpolation handles scene cuts, camera pans, and motion blur.
  • Neural Alpha Masks: Generates frame-by-frame transparency masks for every tracked product.

2. Marketing Intelligence (Agentic ROI)

  • Scene Analyst: Examines character-product interactions and emotional context.
  • Market Analyst: Quantifies visibility rate, screen coverage, and airtime.
  • Ad Strategist: Brainstorms campaign optimizations and revenue attribution ideas.
  • Powered by gemma-4-31b-it (Dense Architecture).

3. Executive Dashboard

  • Attention Retention Analysis: Interactive second-by-second exposure charts.
  • High-Density Metrics: Visibility scores, Peak Frame Coverage, and Airtime stats.
  • Executive Strategy HUD: AI-generated strategic insights and campaign optimization logs.

🛠️ Technology Stack

  • Backend: FastAPI, Python 3.10+
  • Frontend: Next.js 14, TailwindCSS, Framer Motion
  • AI Engine: LangGraph (Orchestration), Groq (Vision), Google Vertex/Gemma 4 (Reasoning)
  • Vision: OpenCV, PIL, Llama-4-Scout

🚦 Getting Started

1. Requirements

  • Python 3.10+
  • Node.js 18+
  • Groq API Key
  • Google Cloud Credentials (for Gemma 4)

2. Installation

# Clone the repository
git clone https://github.com/KrishMaske/HackKEAN.git

# Setup Backend
cd backend
pip install -r requirements.txt
cp .env.example .env # Add your keys

# Setup Frontend
cd ../frontend
npm install

3. Execution

# Run Backend (Port 8000)
cd backend
python main.py

# Run Frontend (Port 3000)
cd frontend
npm run dev

🧪 Pipeline Flow

  1. Ingestion: Scene is uploaded; Llama-4 identifies the most prominent product.
  2. Rendering: Neural mask video is generated via keyframe interpolation.
  3. Analysis: ROI stats are calculated from the rendered masks.
  4. Strategy: Gemma-4 agents brainstorm executive insights based on the ROI data.
  5. Delivery: Dashboard populates with the complete "Proper" analytical story.

🏛️ Project Structure

  • backend/app/agents/: Marketing Agent definitions.
  • backend/app/services/masking.py: The core temporal tracking engine.
  • backend/app/services/orchestrator.py: Agentic workflow management.
  • frontend/src/app/page.tsx: The high-fidelity React dashboard.

Created with ⚡ by the ProductIntel Team.

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