Aipify – Your Agentic-to-API Platform

Inspiration

I wanted to book a Waymo ride programmatically, but quickly realized there was no public API. I set that aside until CalHacks, where I was trying to query event details and prizes — and again, found myself needing heavy infrastructure for a small gain.

I started noticing this pattern everywhere: whenever humans interacted with interfaces, it required complex setups to automate or access data. Meanwhile, AI agents have become smart enough to reason, plan, and act like us — but there’s still no easy way to query them programmatically. That’s when I thought, why not fix this?

What it does

Aipify turns agentic workflows into simple, queryable REST APIs — allowing you to expose complex AI-driven actions as endpoints in seconds.

How we built it

I built Aipify using:

🧠 Groq – for high-speed inference
⚙️ Lava Labs – for agent orchestration
🤖 Fetch.ai – for autonomous agent logic
🐳 Docker – to isolate and manage AI containers
🌐 Browserbase – to give agents real browser access
💬 Claude – for reasoning and planning
🧩 Chroma – for vector memory and context recall
🚀 FastAPI – for the backend and API layer
💻 Next.js – for the web interface

Together, they create a full-stack system that spins up intelligent agents, executes tasks, and exposes those capabilities as REST endpoints.

Challenges we ran into

Spinning up and managing live AI-powered Docker instances was surprisingly difficult. Keeping them stable, responsive, and secure while running browsers and agents in real-time required deep debugging and experimentation.