class Engineer:
def __init__(self):
self.name = "Asaf Lecht"
self.role = "Full-Stack AI/Data Engineer"
self.location = "Israel 🇮🇱"
self.stack = ["Python", "TypeScript", "SQL", "Google Cloud"]
def mission(self):
return "Bridging legacy enterprise data with modern AI architectures."I specialize in building production-ready systems that solve complex workflows. My work ranges from manufacturing video analysis to Semantic Search engines for legacy archives. I focus on clean architecture, type safety, and automated deployment pipelines, ensuring that Big Data makes sense.
| Languages | AI & Data | Frameworks | DevOps & Tools |
|---|---|---|---|
   |
    |
    |
   |
AI-Powered Video Analysis for Manufacturing
- The Tech: Python (Flask), TypeScript (React), Google Gemini 1.5 Pro, FFmpeg.
- The Solution: A full-stack application that integrates LLMs to analyze manufacturing footage, featuring a custom-built frame extraction engine.
Semantic Search for Legacy Archives
- The Tech: Python, ChromaDB, OpenAI, LangChain.
- The Solution: A Retrieval-Augmented Generation (RAG) pipeline to index and search old PST/OST files, allowing users to "chat" with years of email history.
IoT & Digital Signage System
- The Tech: PyQt6, Docker, Hebrew Calendar Algorithms.
- The Solution: A robust digital signage application handling complex RTL language support and location-based API triggers.