AEIRS – Autonomous Enterprise Intelligence & Reporting System

AEIRS is a unified AI-powered analysis platform designed to extract insights from videos, audio, images, and tabular datasets.

It combines LLM reasoning, automated analytics, and interactive visualization into a single modular system.

🚀 Core Modules

🎥 SnapSum — Video & Audio Intelligence

Analyze video/audio content with AI-driven understanding.

Capabilities

• Automatic transcription
• Contextual summarization
• Sentiment analysis with visual indicators
• Key-point extraction
• Conversational Q&A with the media content

Supported Formats

• MP4, MOV
• MP3, WAV

📊 AEIDS — Automated Enterprise Intelligence for Datasets

AI-powered exploratory data analysis for structured data.

Features

• CSV / Excel upload
• Automated EDA (statistics, correlations, anomalies)
• Interactive visualizations
• Insight extraction and export (JSON / HTML reports)
• Persistent analysis history

🤖 NEXUS AI — Intelligent Data Copilot

An embedded AI assistant that understands your analysis context.

Capabilities

• Natural language Q&A over dataset insights
• RAG over stored analysis outputs
• Optional OCR & image understanding via vision models
• Context-aware reasoning inside the analysis workflow

🧠 System Architecture

Frontend (HTML/CSS/JS)

    |
    
    v

FastAPI Backend (Modular Routers)

    |
    
    ├── SnapSum Pipeline (Media Analysis)
    
    ├── AEIDS Pipeline (Dataset Analysis)
    
    ├── NEXUS AI (RAG + Reasoning)
    
    |

Vector DB (Pinecone / FAISS)

    |

SQLite (Metadata & History)

🛠 Tech Stack

Backend

• FastAPI
• Uvicorn
• Groq LLMs (Text + Vision)
• Pinecone / FAISS (Vector Search)
• pandas, numpy
• SQLite

Frontend

• HTML, CSS, JavaScript
• Font Awesome
• Responsive UI
• Dark / Light theme support

📂 Project Structure

AEIRS-DATA-and-VIDEO-REPORTER/

│

├── AEIRS/

│ ├── analyser.py

│ ├── detectors.py

│ ├── pipeline.py

│ ├── llm_explainer.py

│ ├── models.py

│ ├── auth.py

│ └── app.py

│

├── frontend/

│ ├── video_analysis.html

│ ├── new.html

│ └── login.html

│

├── uploads/

├── requirements.txt

└── README.md

⚙️ Setup & Installation

1️⃣ Clone Repository

cd AEIRS-DATA-and-VIDEO-REPORTER/AEIRS

2️⃣ Install Dependencies

pip install -r requirements.txt

3️⃣ Configure Environment Variables

Create a .env file or export variables:

GROQ_API_KEY=your_key_here

PINECONE_API_KEY=your_key_here

4️⃣ Run Application

uvicorn app:app --reload

Access:

http://localhost:8000 → Login

/video-analysis

/dataset-analysis

📌 Use Cases

• Enterprise video audits
• Interview & meeting analysis
• Automated business intelligence
• Dataset exploration for analysts
• AI-assisted reporting workflows

🔒 Security Notice

API keys must never be committed to source code or documentation.

Always use environment variables or secret managers.

📈 Future Enhancements

• Role-based authentication
• Cloud deployment (Docker + AWS/GCP)
• Multi-user project spaces
• Streaming video analysis
• Model switching support