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I got my first recommendation on Contra, from Ryan at Haven Lifestyles.
His n8n workflows were taking down the n8n Cloud instance every day. Enterprise plan, and it still fell over after a few hours because too many runs were firing in parallel. Memory limits and workflows too complex. So I refactored the workflows, moved everything to a self-hosted instance, and put monitoring on it with Slack and email alerts.
The daily collapse is gone. Error rate went from up to 12% down to 0.1%, and self-hosting now saves them over $1,500 a month. Thanks Ryan, that was a fun one to dig into.
A lot of companies are looking at automation right now, and n8n is a good place to start. For some clients it also runs AI inside the workflow, handling checks a person used to do by hand on every case.
If you have a process like that eating time in your business, message me.
RECOMMENDED
“Marcel was incredible to work with. Our n8n workflows were continuously crashing the n8n Cloud server. Marcel pinpointed the problems, proposed a solution, and fully implemented it. Tremendous ROI working with Marcel on this.”
Ryan Rader
HavenThe network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
Just posted a new case study on Contra.
A 60-second promo for Ulta AI by Ultahost, a chatbot that runs a server through plain conversation. Script, storyboard and animation, all built around the real product UI.
Check it out
Let me know what you think💭😍
Just checked it out - this is fire Blahomyr! 🔥 A 60-second promo built around real product UI with script, storyboard and animation - that's how you do it! Love the "endless panels" concept, super clean execution in After Effects. Ulta AI's conversational server management feels so intuitive in your promo!
An automated n8n workflow that receives incoming leads via webhook, validates them, qualifies them with AI (Google Gemini), scores them, and syncs the result to Airtable without creating duplicates.
really optimized workflow
Before you add AI to your product, find the screen where your users already copy and paste.
That's usually where the real AI feature lives. Not a chatbot in the corner, but a step people already do by hand: summarising a ticket, drafting a reply, tagging an upload, pulling fields out of a PDF.
Here's the order I follow when a founder asks me to add AI to an existing SaaS:
1. Pick one workflow, not "AI everywhere." Watch where users leave your app to paste something into ChatGPT and come back. That round trip is your feature.
2. Keep the model behind your own API. One service owns prompts, retries, logging and cost limits, so you can switch providers without touching the frontend.
3. Make it tenant-aware from day one. Each customer's data, prompts and usage stay scoped to their account, or the first enterprise security review will stop you.
4. Ship a draft, not a decision. Let the AI suggest and the user approve. You earn trust and get real feedback before you automate anything.
5. Measure accepted output, not tokens. If users rewrite most of what it produces, the prompt or the context is wrong, and that's your real roadmap.
Most AI features that flop didn't fail because of the model. They were bolted onto the wrong step.
What's the one task your users still copy into ChatGPT?
Watching where users paste into ChatGPT and come back is such a practical way to find the real feature. Most teams start with the chatbot instead.
