I’ve been building a platform called Dank AI (www.ai-dank.xyz), basically a “Vercel for AI agents.” You define an agent in JavaScript with our framework, connect a GitHub repo, and it deploys to a production URL in one click (containerized, with secrets, logs, CPU/RAM selection, etc.).

I recently added a big update so that now you can also deploy and host weaviate vector databases alongside your agent. I put together this AI chatbot example to show how easy it is to define an agent with Dank, integrate weaviate memory for RAG, and connect to an application frontend. The project is designed to run the whole demo locally from a single command, and you can immediately deploy the agent + weaviate on Dank cloud, and deploy the front end on Vercel (just set env variables accordingly to switch the project from local to prod).

It’s set up so you can fork it and immediately build your own Dank agent application without worrying about infra. I hope this makes it easier to build and deploy AI agents. Any feedback you have would be greatly appreciated.

Congrats on the project! I think a project coined as a "Vercel for AI Agents" is well-needed, especially in 2026 with many companies integrating Agents in their workflows. By ensuring developers can create AI Agents easily through a popular programming language and stashing the code on a GitHub Repo to deploying it to a production URL seamlessly seems like an appealing value proposition. Wishing you all the best with the project!