Sentix AI: Enterprise Product Intelligence

The Global Consensus Engine for Market Sentiment Analysis.

Sentix AI is a high-performance market intelligence platform that aggregates global signals from YouTube and Reddit to provide deep, "Agent-Verified" product insights. By utilizing a multi-agent orchestration layer, it doesn't just summarize data—it audits it for blindspots and biases.

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🚀 Key Features

• Global Consensus Engine: Aggregates video transcripts and social discourse to generate a unified Sentiment Score.
• Agent-Verified Audits: Uses "System Audits" to identify blindspots in reviewer data, ensuring users see what’s missing from a product review.
• Insight Pills: Auto-generated tags for key Strengths and Weaknesses.
• PDF Intelligence Reports: Exportable executive summaries of product performance.
• Smart Alternatives (BETA): AI-driven pivot recommendations based on cross-platform pain points.

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🤖 Multi-Agent Architecture

The system operates using a specialized agentic workflow:

1. Signal Extractor Agent: Fetches and parses global data (YouTube Transcripts/Metadata).

2. Consensus Agent: Synthesizes multiple reports into a single global brief.

3. Audit Agent: Scrutinizes source data to find "Blindspots" (e.g., missing technical details, biased sponsorships).

4. Verdict Agent: Calculates the final global sentiment score () using a weighted logic:

5. Alternative Agent (WIP): Maps user pain points to competitor products via Reddit discourse.

Important

DEMO NOTE: The "Alternative Agent" (Phase 5) is currently under active development. For the current demo version, the alternatives.html page uses a high-fidelity hardcoded model based on iPhone 16 Pro Max data to demonstrate the intended output of the Reddit Scraper.

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🛠 Tech Stack

• Framework: Django (Python 3.10+)
• Frontend: Bootstrap 5, Bi-Icons, HTML5/CSS3
• Intelligence: Gemini 3 pro preview
• Data Sources: YouTube Data API v3, Praw (Reddit Wrapper)
• Reporting: html2canvas, jsPDF

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📂 Project Structure

├── sentix_project/          # Django Root
├── intelligence/            # Main AI Application
│   ├── templates/
│   │   ├── index.html       # Dashboard UI
│   │   └── alternatives.html # Phase 5 Demo Page
│   ├── views.py             # Agent Orchestration Logic
│   └── urls.py              # System Routing
├── static/                  # CSS, JS, and Brand Assets
└── manage.py

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⚙️ Installation & Setup

1. Clone the Repository:

git clone the repo

2. Install Dependencies:

pip install -r requirements.txt

3. Environment Variables: Create a .env file in the root directory:

and enter your credentials

4. Run the Server:

python manage.py runserver

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📈 Roadmap

• Phase 1: Signal Extraction & Transcription
• Phase 2: Multi-Agent Consensus Logic
• Phase 3: System Audit & Blindspot Detection
• Phase 4: Intelligence PDF Exporting
• Phase 5 (In Progress): Live Reddit Alternative Scraper