Overview
Looking for Co-Founder (Business / Management) – AI Language Learning App. I’m building a language learning mobile app powered by LLMs, focused on efficient, privacy-friendly, and personalized learning. The product is mobile-first (Flutter, at least for MVP) and fine tuned LLM on external data. I’m looking for a co-founder, who can mainly handle the business and management side, especially pitching, fundraising, and representing the startup.
This is an early-stage startup, but the problem, tech direction, and ambition are clear. If you’re active in the Swiss startup ecosystem and want to lead the business and fundraising side of an AI education startup, I’d love to connect.
Responsibilities
* Manage business and governance tasks, including pitching, fundraising, and representing the startup.
* Help set strategic direction and coordinate with the technical founder on product goals and execution.
* Engage with investors (angels, grants, accelerators) and the Swiss startup ecosystem.
Technology & Product Direction
* Flutter (iOS / Android)
* Fine tuning large/small language models
* Python ML stack (PyTorch, ONNX, TFLite / Core ML)
* Backend: FastAPI / Firebase / Supabase
* Strong focus on performance, cost efficiency, and privacy
Who I’m looking for
* Swiss national or C resident permit
* Comfortable with startup management, pitching, and networking
* Interested in fundraising (angels, grants, accelerators)
* Technically curious (no need to code daily, but able to understand the product)
* Interested in AI, education, and early-stage startups
What I bring
* Product vision and hands-on technical development
* Experience with Flutter and applied ML
* Long-term commitment to building a real company
Project description
Most language learning apps rely on static content or rule-based exercises that fail to adapt to individual learners. More recent AI-driven solutions depend heavily on large cloud-based LLMs, resulting in high costs, latency, limited offline functionality, and growing concerns around data privacy. These constraints make truly personalized and scalable language learning difficult.
Advances in Large Language Models (LLMs), model distillation, and efficient inference enable personalized language learning. Fine tuned, optimized models can provide contextual feedback, adaptive exercises, and conversational practice with lower latency, reduced cost, and stronger privacy, while remaining suitable for mobile and on-device deployment.
XYZ is a mobile-first language learning app built with Flutter, designed around efficient AI from the ground up. By leveraging Large Language Models, XYZ delivers personalized practice, intelligent feedback, and adaptive learning paths while prioritizing performance, cost efficiency, and user privacy. The platform focuses on real learning outcomes rather than generic content consumption.
Technology Stack
* Flutter (iOS / Android)
* Small, distilled, and quantized language models
* Python ML stack (PyTorch, ONNX, TFLite / Core ML)
* Backend services via FastAPI, Firebase, or Supabase
* Emphasis on low-latency inference and privacy-first design
Vision
XYZ aims to make high-quality, personalized language learning accessible at scale by combining modern mobile development with efficient, practical fine tuned LLM models.
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