Daniel Hintergrundbild
Daniel

Daniel

Verifizierte:r Freelancer:in

Freelancer:in

Zetel

Über mich

I love building tech products, especially lately with Generative AI. I've built a few MVPs for different startups so far, my most recent one being for a young Silicon Valley AI-centered startup where I've been focusing on AI-based autonomous agents. I believe that in the future, machines will build machines, which is why I'm very interested in projects involving code generation. Example: I built one product where an LLM generates data science python code that analyzes arbitrary datasets and plots results in interactive charts. I'm also open to consulting jobs. If you want to know which LLM to use or which direction to go, please ask. I'm happy to help.

Skills

Expert:in

Artificial Intelligence Application
ChatGPT
VueJS
Full Stack Development
Firebase
Chatbot
TypeScript
Python
Prompt Engineering
Flask
Generative AI
Progressive Web App
Frontend Development
Tailwind CSS

Fortgeschritten

UI Design
Figma
UX Design
Softwareentwicklung
Cloud Computing
CI/CD
Analytische Fähigkeiten
NodeJS
Github
GitLab
Lean Startup
Data Engineering
Agile Software Development
Produktdesign
Google Cloud Platform
Webdesign
Webentwicklung
Data Science
Analytical Thinking
PostgreSQL
Data Analysis
CSS
Cloudflare
Slack
Visual Studio Code
Technische Dokumentation
Projektmanagement
Data Visualisation
Applications Development
Kundenakquise

Junior:in

Webflow
AI Image Generation
Amazon Web Services
Backend Development
CRM
Data Sharing
Datenpflege
Docker
Elasticsearch
Erklärvideos
Infrastructure Deployment
LinkedIn
Linux
Machine Learning
MongoDB
MySQL
Personalmanagement
Pricing Strategy
Produktmanagement
Sales

Projekte

  • Onereview

    Auftraggeber:in

    2023 — 2023

    OneReview is a product developed by our team consisting of Harry, Eliska, and Ben. 

    We won first prize for it at the Hackathon held at On Deck in San Francisco. OneReview is a Chrome beta extension that summarizes the most important customer reviews into one trusted review. It saves time by providing concise highlights and pros/cons of products, eliminating the need to read through multiple reviews.

    It detects real reviews and filters out fakes, ensuring reliability. Users can also compare products and their highlighted reviews side by side.

    The Chrome extension is built with TypeScript and Vue. The server is built with Python, scraping information from Amazon using ScraperAPI and analyzing reviews in an LLM pipeline centered around Anthropic's Claude LLM.

    More infos: https://yep.so/p/onereview

  • Eezo

    Eezo ·

    2023 — heute

    Build autonomous Agents like Legos

    Develop and use pre-build code blocks like Legos to build arbitrary powerful autonomous agents in minutes.

    I initiated this project myself. I collaborated and consulted with startups to build and discuss AI-based autonomous agents. I identified several components necessary for each agent to construct an autonomous agent and decided to simplify the entire process with Eezo.

    Visit https://eezo.ai (legacy website, new website is launching soon)

    The realization of this project involved speaking with users, conceptualizing a solution based on their needs, and designing the UI/UX in Figma, along with tests which included a chat interface. I built the frontend, incorporating a Slack-like UI block system that can be dynamically generated by AI and assembled in the backend using Vue.js and TypeScript. Planning and constructing the backend relied on Google Cloud + Firebase, Supabase (PostgreSQL), utilizing Python and TypeScript. I developed a WebSocket-based RESTful API that enables users to connect their code to the AI, employing a variety of prompting techniques and advanced RAG, among other methods, around OpenAI's LLMs. I designed and coded the website to showcase real examples of the product's capabilities. For organization and brainstorming, Notion and Figma were my primary tools.

  • Rokin

    Rokin ·

    2022 — 2023

    ROKIN is an engineering-focused search engine that improves search efficiency and collaboration. It sends tailored queries to top search engines, filters results, and organizes them for engineers. Teams can collaborate, share relevant content, and avoid duplicating work.

    This project was supported by Fraunhofer Ventures, Esa, Media Lab Bayern, and the SCE. 

    My task involved building the entire frontend, which included features such as managing search result lists, collaboration tools for teams to jointly search for parts for large projects with real-time chat, and a marketplace to share and sell existing lists of well-curated search results for highly specialized projects.

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