fammy.pet - SaaS B2C

fammy.pet — AI Food Safety Checker for Pets

Brief Description
A service that instantly checks the safety of any food product for dogs and cats. The user inputs the name of the product or ingredient — the system returns a veterinary assessment, detailed composition analysis, and recommendations.

What has been implemented
Backend:
Node.js / Fastify — main server
200+ endpoints, 7 business functions (2 connected on the front end)
PostgreSQL — relational database, 30+ tables, 18M+ records and relationships
Qdrant — vector database for semantic search
RAG pipeline + Embedding models for AI composition analysis
Local LLMs for veterinary assessments and comments
Data:
Scraped 7 databases (USA + France)
Products, menus, ingredients, nutrients, veterinary assessments
n8n — automation of parsing, translation, database status monitoring
Infrastructure:
Deployment: Hetzner VPS
Docker + Coolify
Supabase

Stack
Node.js Fastify Python PostgreSQL Qdrant LLM RAG Embedding Docker Coolify Supabase n8n