Built for Production
Every tool we use, why we chose it, and how it fits together. No black boxes.
What We Build With
The Stack
Frontend
Server-rendered React applications with type safety and utility-first styling. Deployed to Vercel's edge network.
Backend
Python for automation and AI integration. Pydantic for structured output validation and type-safe data contracts. Express for API servers and webhook handlers.
Database
Managed Postgres with row-level security, real-time subscriptions, authentication, and file storage. Per-client projects.
Hosting
DigitalOcean droplets for backend services and Python workers. Vercel for frontend deployment with edge functions.
AI
Claude for document processing and agent reasoning. LangChain/LangGraph for multi-step workflows. LLaMA, Mistral, or Kimi for on-premise deployments where data cannot leave client infrastructure.
Automation
Custom Python scripts running on scheduled cron jobs. No per-execution pricing, no platform limits, unlimited runs.
CI/CD
Automated linting, type checking, and deployment on every push. No code ships without passing CI.
The Foundation
Why Python
Testable
Every automation we build has unit tests. Python's testing ecosystem (pytest, unittest) lets us verify behavior before deployment, not after something breaks in production.
Version Controlled
Code lives in Git. Every change is tracked, reviewable, and reversible. Low-code platforms store workflows as JSON blobs that are hard to diff and impossible to review meaningfully.
No Vendor Lock-in
Python runs anywhere. If you want to move to AWS, GCP, or your own servers, the code works. Try exporting a 200-node n8n workflow to another platform.
No Per-Execution Pricing
A Python script on a $12/month DigitalOcean droplet can run thousands of times per day. The same volume on Zapier would cost hundreds per month in execution fees.
Unlimited Ceiling
There is no feature request that Python cannot handle. Low-code platforms hit walls when you need custom logic, complex data transforms, or AI integration. Python has no ceiling.
Side by Side
Python vs Low-Code
| Feature | Python (Syntora) | n8n / Zapier / Make |
|---|---|---|
| Scalability | Unlimited. Add servers, optimize code, scale horizontally. | Capped by platform limits. Throttled at scale. |
| Debugging | Full stack traces, logging, breakpoints. Standard dev tools. | Visual logs at best. Black box at worst. |
| Code Ownership | You own every line. Take it anywhere. | Locked in the platform. Export is limited or impossible. |
| Cost at Scale | Server cost only. No per-execution fees. | Per-execution pricing. Costs grow with volume. |
| Security | Your infrastructure, your access controls, your audit trail. | Data flows through third-party servers. |
| Setup Speed | Slower initial build. Faster long-term iteration. | Fast prototyping. Slower to maintain and extend. |
The Inflection Point
When You Outgrow DIY
n8n, Zapier, and Make are good starting points. They let you connect apps and automate simple workflows without writing code.
But at some point, your workflows need custom logic that visual builders cannot express. You need error handling that goes beyond retry loops. You need AI that does more than route data between apps.
That is when you call us. We build what you outgrow n8n for. Custom Python automation that scales with your business, runs on your infrastructure, and handles the complexity that drag-and-drop tools cannot.
Ready to upgrade your stack?
Tell us what you're automating. We'll show you what Python can do that your current tools cannot.