Moe's AI Agent Platform

The Problem

Businesses want AI agents but face a brutal choice: expensive custom development or rigid no-code tools that don't fit their workflows. We needed to prove that a flexible, self-hostable agent platform could be built quickly and affordably.

The gap

• Custom agents — $50k+ and months of development
• No-code platforms — Limited customization, vendor lock-in
• Open source options — Require significant technical expertise

The Build

We built Moe's AI from scratch in a focused 48-hour sprint:

Technical stack

• Frontend — Next.js 15 with React 19, Tailwind CSS
• Backend — Supabase (Postgres + Auth + Realtime)
• AI — Multi-model support (GPT-4, Claude, Gemini)
• RAG — pgvector for knowledge base embeddings

Features shipped

1. Agent builder — 4-step wizard for creating agents
2. Multi-channel — Slack, Discord, WhatsApp, Email integrations
3. Knowledge base — Upload docs, auto-chunk and embed
4. Analytics — Conversation tracking, response quality metrics
5. Human-in-loop — Approval workflows for sensitive actions

The Outcome

Deployed in 48 hours:

• 7 app screens — Dashboard, agents, knowledge, analytics, settings
• Full auth system — Sign up, sign in, password reset
• Marketing site — Landing page with waitlist
• Production-ready — Deployed on Vercel with Supabase backend

What this proves

A functional AI agent platform doesn't require months of development or massive budgets. With the right architecture decisions and focused execution, you can go from zero to deployed MVP in days.

Tech Stack

Next.js React 19 Supabase pgvector Tailwind CSS Vercel