Every tutorial out there teaches you how to use N8n or Zapier, but what if you could build your own instead? In this tutorial, we're building NodeBase, a complete workflow automation platform from scratch. Drag and drop canvas, real-time execution, Multiple integrations ready to go. Plus, we're building the full software-as-a-service layer. Payments, subscriptions, free tier, and paywalls.
By the end of this tutorial, you'll have a production-ready platform that you can actually ship and charge for. The heart of any automation platform is the canvas. We'll build a clean interface with trigger nodes and execution nodes. You'll learn how to create webhook triggers, Google form submissions, Stripe event listeners, and even manual triggers. For execution nodes, we'll build AI integrations such as Open AI, Cloud, and Gemini.
Plus some messaging platforms like Discord and Slack. And a generic HTTP request node. But Here's the key. Once you understand how these work, you will be able to add any integration you want. Airtable, Notion, SendGrid.
The only limit is your imagination. Let's build something practical. We'll start with a Google Form trigger, perfect for collecting customer feedback or survey responses. When someone submits the form, we'll send that data to OpenAI to analyze and summarize the responses. Then we'll take that summary and send it to both Discord and Slack, notifying your entire team instantly.
Each node has a configuration panel where you map data from previous steps using simple template syntax. The data flows from one node to the next, and you control exactly how it transforms along the way. Now here's where it gets visually satisfying. While the workflow is executing, each node will display its current status. You see exactly which node is working, when it completes, and if anything fails.
For example, the Google form triggers. OpenAI starts thinking and completes successfully. Then Slack fires off and succeeds. But Discord, it lights up and fails with a red error state. You can see exactly which node has the problem and you caught it in real time.
Everything updates through web sockets, which means no polling and no page refreshes. You're watching your data flow through the system as it actually happens. All of this is powered by InGest. It can handle background job execution, manage retries if something fails, and gives us real-time pub-sub messaging for those live updates you just saw. Your workflows run reliably in the background while the UI stays responsive and shows exactly what's happening.
For our database layer we're using Prisma as our ORM coupled with Neon as our Postgres provider. This gives you type-safe database queries in a modern stack. Authentication is handled by BetterAuth, which is quickly becoming the new standard for auth in the Next.js world. It comes with tons of providers out of the box and makes complex outflows actually manageable. For payments and subscriptions, we're using Polr, which gives you free tier, paid plans, and usage-based billing.
Everything you need to monetize your platform. This is more than just a coding tutorial. It's a real-world development workflow. Each chapter ends with a new branch and a pull request. We're using CodeRabbit for AI-powered pull request reviews.
So you'll see how to structure your code, handle reviews, and merge features just like you would in production. It's a complete GitHub workflow tutorial built right in. In order to make this project production ready, we are integrating Sentry for error tracking, logging, and session replace. But the real power is in their AI agent monitoring. Every time an LLM call is triggered, we get extremely detailed information.
Which model was used, exact token counts in and out, cost per request, execution duration, and the actual response output. This way, you can trace every single AI interaction in your application with complete visibility. So let's recap the full tech stack. Next.js and TypeScript for the foundation. Prisma and Neon for our database.
BetterAuth for authentication. Polar for payments and subscriptions. Ingest, powering our workflow executions with real-time updates. ReactFlow for the visual canvas. OpenAI, Cloud, or Gemini for AI integrations.
CodeRabbit for our GitHub workflow. And Sentry making it all production-ready. This isn't just a workflow automation tutorial, this is a complete playbook for building and shipping a real SaaS product. And now, let's get started. Before we dive in, using the link on the screen you can get three months of Sentry Team completely for free.
We'll be using their AI monitoring to track all our LLM calls throughout this build. If that sounds useful for your project, feel free to grab the deal. And now, let's build!