Trad-Bot: Visual Workflow Automation SaaS

Overview

Trad-Bot is a production-ready workflow automation platform that allows users to visually design, automate, and execute workflows using triggers, AI agents, messaging platforms, and external APIs.

Inspired by tools like Zapier and n8n, Trad-Bot focuses on developer-friendly automation, AI-powered nodes, and type-safe execution — all wrapped in a modern SaaS experience.

What Users Can Do

• Build Visual Workflows: Design workflows using a drag-and-drop canvas powered by React Flow.
• Configure Trigger Nodes: Start workflows via Webhooks, Google Forms, Stripe events, or manual triggers.
• Use AI Agents: Integrate OpenAI, Claude, and Gemini for intelligent automation.
• Send Messages: Dispatch messages to Discord and Slack directly from workflows.
• Make HTTP Requests: Call external APIs using customizable HTTP nodes.
• Run Background Jobs: Execute long-running or async workflows reliably using Inngest.
• Manage Subscriptions: Handle billing and plans with Polar payments.
• Secure Authentication: User auth handled via Better Auth.
• Monitor Errors: Track runtime errors with Sentry + AI-assisted debugging.

Why I Built This

I wanted to build something that pushes beyond CRUD apps and forces me to think like a systems engineer.

Trad-Bot exists to solve problems like:

• How do you orchestrate workflows reliably?
• How do you execute background jobs without blocking requests?
• How do you maintain type safety across frontend, backend, and jobs?
• How do you build a real SaaS, not just a demo?

This project is my deep dive into event-driven systems, automation engines, and scalable SaaS architecture.

Tech Stack

• Next.js 15 (App Router) – Full-stack framework
• TypeScript – End-to-end type safety
• React Flow – Visual workflow canvas
• Tailwind CSS + Shadcn UI – Modern UI system
• tRPC – Fully type-safe APIs
• Prisma ORM – Database access layer
• Neon Postgres – Serverless Postgres database
• Inngest – Background job orchestration
• Better Auth – Authentication system
• Polar – Payments & subscriptions
• OpenAI / Claude / Gemini – AI workflow nodes
• Sentry – Error tracking & AI monitoring

Key Technical Highlights

• Visual DAG-based workflow engine
• Event-driven execution model
• Background job processing via Inngest
• Strong isolation between workflow definition and execution
• End-to-end type safety using TypeScript + tRPC
• Production-grade error monitoring and alerting

Current Status

Trad-Bot is actively under development and already structured as a real SaaS product, including:

• Auth
• Billing
• Background jobs
• Error tracking
• AI integrations

The focus is now on stability, scalability, and UX polish.

Future Plans

• Add more trigger sources (GitHub, Cron, Email)
• Introduce workflow versioning
• Add execution logs & visual debugger
• Team collaboration & shared workflows
• Marketplace for community-built nodes