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SavantShopper
AI-powered fashion stylist and private CRM with a massive SEO content moat.
What it is
A hybrid AI fashion stylist and private CRM that uses a massive public content moat to capture organic traffic. The platform successfully blocks AI scrapers to protect IP while serving hundreds of indexable pages to drive high-intent leads.
- Python
- TensorFlow
- Next.js
- PostgreSQL
- OpenAI API
What it does
4 things, working.
AI-driven style recommendations
Automated content generation for SEO
Private members-only CRM
Anti-scraping protection system
Screens
See it running.
The build
Why, and how.
The problem
Fashion e-commerce faces high customer acquisition costs. The client needed a way to attract organic traffic at scale without exposing their proprietary styling algorithms to competitors.
What I built
Built a "content moat" architecture that generates high-value public content for SEO while keeping the core AI styling engine behind a secure, invite-only gate.
Under the hood
The core of SavantShopper is a custom-trained TensorFlow model that analyzes fashion trends from social media signals. This model feeds into a Next.js frontend that uses Incremental Static Regeneration (ISR) to create thousands of landing pages for trending items. We implemented a custom middleware to detect and block scraper bots (like GPTBot and CCBot) to prevent competitors from training on our curated datasets, ensuring the "Savant" algorithm remains a unique competitive advantage.
Search
We utilized a "Programmatic SEO" approach, generating unique, high-value landing pages for long-tail fashion queries (e.g., "best vintage leather jacket for petite women"). By structuring this data with rich Schema.org markup (Product, ImageObject) and ensuring internal linking clusters around core style categories, we achieved a domain authority spike and captured featured snippets for over 400 keywords.
How it was built
- Developed hybrid rendering architecture (SSG + CSR)
- Implemented advanced bot detection and rate limiting
- Created automated content pipelines for trend analysis
- Built secure, scalable user authentication system
What came of it
- Reached top search rankings for niche fashion queries
- Reduced CAC by 60% through organic lead generation
- Protected proprietary data from competitor scraping
- Scaled to thousands of active users with zero ad spend
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