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ā¢ Jul 5
š Building an AI-Powered Omnichannel Platform
Excited to share one of my latest projects: TechLabID Omnichannel Platform.
This platform helps businesses manage customer conversations from multiple channels in a single dashboard, making communication faster and more efficient.
Current features include:
ā¢ Unified conversation inbox
ā¢ User & role management
ā¢ Advanced filtering
ā¢ Analytics dashboard
ā¢ Scalable backend architecture
ā¢ AI-ready foundation for automation and intelligent customer support
I'm passionate about building AI-powered software, automation tools, and scalable web applications that solve real business problems.
Feedback is always welcome!
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They said "You have to start somewhere"
Started building "StyleFlow"
The app will be live on App Store & Google Play soon.
We Need to focus on helping a local business then we do multi salon.
Interviewed real people in person to gather feedback and improve the app.
The app is live, and the salon is actively using it. They love how smooth it is and how much it has helped automate tasks for both customers and salon owners.
šÆ Just DM me to get the access code and explore the Manage Your Salon feature, since the salon is currently using the app.
Live: https://styleflow-hub.base44.app/
Thank you for those who are supporting the app.
WE INTERVIEW AND INTRODUCE OUR PRODUCT TO REAL LOCAL BARBERSHOP BUSINESS.
Yes! you read it right. We are confident with the product and show it to public....
Which AI workflow would you trust in production?
4 voted
44%
5 voted
56%
9 votes
Closed
Full Autonomy!
Hey Contra š
Two months ago I posted Promptly here as a work-in-progress and said I'd launch in about three weeks.
Then a health issue knocked me flat, and the three-week plan was gone.
I'm good now ā and as of today, the build is done. I just published the full case study as well.
Quick recap: after shipping 20+ projects as a tech lead, I kept watching the same thing break. A founder says one thing, the developer hears another, and a month in, the whole build is based on a misunderstanding nobody caught early.
Promptly closes that gap. You describe your idea in plain English; the AI interviews you, pushes back on the vague parts, and writes a developer-ready spec while you chat.
But the chat is the easy part. The real engineering is everything that stops the AI from being trusted too much:
ā It never touches the database. 16 agents can only propose changes through typed tool calls; backend code checks each one, and invalid calls get rejected and logged.
ā Nothing ever gets lost. It snapshots before anything risky, so you can roll back a single module or the whole project.
ā Spend is capped, always. Every AI call passes four checks before it fires, and each one is logged with its exact cost.
One line sums up the architecture:
The AI proposes. The code decides.
The model gets to be creative. It never gets to be in charge.
Full case study is on my profile, and the product is live if you want to poke at it.
One question:
Shipped anything with LLMs in production? What guardrail saved you ā or what missing one burned you?
Every comment on the last post shaped what got built. Thank you for that š
building solo, in public
