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In this case study I show you how I built a full Voice AI SaaS from the ground up using n8n Retell AI, SuiteDash and custom automations.
I will show you how the system works together:
SuiteDash → n8n → Retell AI → AI Phone Calls → n8n → SuiteDash
This platform takes care of everything. It handles how clients join, how the voice AI agents work, the automated workflows, the phone calls and how I manage every client.
Tech Stack
n8n – Workflow Automation
Retell AI – Voice AI Agents
SuiteDash – CRM & Client Portal
AI & Custom APIs
Automated Integrations
If you want to learn about AI automation, AI agents, n8n workflows or building AI SaaS products this case study shows you how all these parts fit together in life.
#VoiceAI #AIAgents #AISaaS #n8n #RetellAI #SuiteDash #AIAutomation #AIAutomationAgency #VoiceBot #AIWorkflows #SaaS #Automation #AIDevelopment #NoCode #LowCode
The 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
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That is not a prompting problem. It is a routing and authority problem.
How I can help you:
I build project routers for teams using multiple AI workflows, agents, or specialist assistants so that they work with each other as a team.
I design source-of-truth resolutions so your agents retrieve the current rules instead of improvising or relying on assumptions or stale chat data.
I create reusable skill registries and specialist handoff logic hardened by determined and dedicated flow states reducing the need for model reliance on its own internal and displaced memory context.
I separate project states with individualized canonical states bound by rules living under essential model instructions and routed properly so unrelated workflows do not contaminate one another, but exist with awareness of the role each project plays, enabling a persistently growing ecosystem to develop organically.
I add governance wrappers, escalation hooks, and recovery mirrors around existing AI stacks so that trust is designed at the root, and variance is eliminated with rule based source archiving and implementation.
Trust means closing your eyes at night and sleeping soundly because your agents got your back. And I can put it all together for you, precision results sourced and undisputed because I got tired of doing things the hard way.
Phillip, agree that routing is where it breaks. In our builds the worst bugs came from an agent pulling an old rule from chat history instead of the current source. Pinning one source of truth per project fixed more than any prompt change did.
Turning complex AI workflows into a calm, monochrome experience, brought to life with motion. We'd love to hear your thoughts!
A good landing page shouldn’t make you work to understand it.
Been working on a new project where the goal was simple:
Make a complex product feel simple, clear, and easy to explore.
Less explaining. Less clutter. More visual hierarchy. A clearer path to the next step.
Still working through the details, but this one is coming together nicely.
Full case study soon.
This pairs well with the Hire Hangar screenshot because the design itself demonstrates the point—you don't need to reveal the whole project yet.
This is nice 👌
