Author: Syed Sajjad Hussain
Role: Applied AI Engineer
SaveIQ is a production-focused media intelligence platform built to solve a real and growing problem:
Creators and teams spend hours consuming long videos but struggle to extract insights, predict performance, and convert content into actionable assets.
SaveIQ automates this entire workflow using AI.
In today’s creator and marketing ecosystem:
- Valuable insights are locked inside long-form videos
- Manual review is time-consuming and inconsistent
- Content decisions are often intuition-based, not data-driven
- Repurposing videos into blogs or social threads takes hours
SaveIQ addresses this by turning raw media into structured intelligence
SaveIQ ingests video content and transforms it into actionable outputs using a reliable, fault-tolerant AI pipeline.
-
Universal Media Extraction
Downloads and processes videos from 50+ platforms usingyt-dlp. -
AI-Powered Content Understanding
Uses Anthropic Claude to analyze transcripts, context, and intent. -
Viral Potential Estimation
Evaluates sentiment and engagement signals to predict content performance. -
Automated Content Generation
Generates:- SEO-friendly blog drafts
- Social media threads
- Content ideas and summaries
-
Interactive UI
Clean Streamlit-based interface designed for fast iteration and usability. -
Reliability by Design
Built with retry logic and monitoring to handle real-world API failures gracefully.
- Python – Core orchestration and business logic
- Streamlit – Interactive web interface
- yt-dlp – Robust media extraction
- Anthropic (Claude API) – Content analysis and generation
- python-dotenv – Secure environment variable management
- requests – External API communication
- watchdog – File system monitoring for processing workflows
- tenacity – Retry logic for fault-tolerant AI calls
This stack prioritizes stability, security, and real-world usability over unnecessary complexity.
- Python
- pip
git clone https://github.com/your-username/saveiq.git
cd saveiq
pip install -r requirements.txt
ANTHROPIC_API_KEY=your_api_key_here
streamlit run app.py