Hello! I'm Elisabeth, an AI Full-Stack Engineer.
More than 3 years experience building intelligent systems.
TypeScript / React / Next.js / Tailwind CSS / Framer Motion / React Query
Node.js / FastAPI / PostgreSQL / Supabase / Redis / REST APIs
LangChain / LlamaIndex / OpenAI API / Groq API / LLaMA 3 / Mistral / RAG Pipelines
Vercel / Docker / CI/CD / Git / GitHub Actions
Passionate about building AI-powered applications that solve real problems
Design and develop full-stack web applications with integrated AI functionality, focusing on automation systems, SaaS platforms, and internal business tools. Deliver end-to-end solutions from concept and architecture to deployment and optimization.
Built a system that analyzes financial statements, categorizes spending, and allows users to query their data using natural language
Developed a SaaS app that organizes tasks/notes and generates daily and weekly plans using AI reasoning
Created internal tools for businesses to streamline workflows, track data, and reduce manual operations
Total Experience
3+ years in AI & Full-Stack
A comprehensive system that analyzes financial statements, categorizes spending patterns, and enables users to query their financial data using natural language processing.
A SaaS application that intelligently organizes tasks and notes, then generates personalized daily and weekly plans using AI-powered reasoning and prioritization.
Internal tools built for businesses to streamline workflows, automate repetitive processes, track operational data, and significantly reduce manual operations.
Most web apps just store and display data. AI-native apps reason over it. This article breaks down how I design full-stack applications that combine traditional systems with LLMs—covering architecture, RAG pipelines, and how to turn static dashboards into intelligent, queryable systems.
A deep dive into building responsive, real-time AI applications. I explore how I use modern full-stack tools to handle live data, user interactions, and AI responses—while maintaining performance, scalability, and a seamless user experience.
Manual workflows kill productivity. In this article, I show how I design and build internal tools and automation systems that replace repetitive tasks using AI—covering everything from input pipelines to decision-making outputs that actually save time and money.
Speed matters in AI products. This article explores how I integrate high-performance inference using Groq and open-source models like LLaMA 3 and Mistral to deliver fast, cost-efficient AI features in real-world applications without sacrificing quality.