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AI Fund operates as a venture studio—not a traditional VC—collaborating with entrepreneurs and corporate partners to build new companies from inception. The tech stack reveals a LLM-forward engineering approach (Claude, DSPy, LangGraph, RAG, Pinecone, Weaviate) paired with rapid prototyping tools (Cursor, Windsurf, low-code platforms), suggesting a studio optimized for quick MVP iteration. Active hiring across engineering, product, and design—concentrated at senior and lead levels—indicates they're scaling internal capability to support multiple portfolio companies simultaneously rather than outsourcing company-building.
Tech Stack 39 technologies
Core StackAWS Supabase Cursor GitHub Copilot Figma Pinecone Weaviate RAG GitHub Slack JavaScript React Vue Angular Python PostgreSQL MySQL MongoDB Lever TypeScript GCP Windsurf DSPy Claude LangGraph X LinkedIn HTML CSS Git+9 more
What AI Fund Is Building
◆Challenges
- Candidate experience
- Manual recruiting tasks
- Launching and growing companies
- Go-to-market strategy development
- Costly and risky diligence for smbs
- Steep terms for smb hardware leasing
- Lack of trust in smb lending
- Launching new venture
- Expanding user adoption beyond taiwan
- Scaling product to other markets
▲Active Projects
- Developing ai-enabled recruiting tools
- Live shopify app and storefront integration
- Co-building phase with portfolio companies
- Fundraising preparation
- Mvp product design using low-code/no-code platforms
- Cognitive engine
- Early experimentation to mvp
- Prototype building with llms and rag pipelines
- Scalable full-stack system architecture
- Scalable design system
Hiring Activity
Steady30 roles · 9 in 30d
Department
Seniority
Notable leadership hires: Chief Executive Officer, Head of Engineering, Head of Product
Company intelligence
