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Developed a comprehensive SaaS analytics system to track MRR dynamics and Unit Economics.
Backend: Wrote complex SQL scripts (Window functions, CTEs) to transform raw payment data into monthly cohorts.
Frontend: Built a Tableau dashboard for monitoring LTV, Churn Rate, and Revenue expansion/contraction.
Result: Business can now identify exactly why revenue is changing and track customer lifetime value in real-time.
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Crypto Portfolio Dashboard
Blue means one thing here: the range you are looking at.
The value chart is a row of thin gray bars, and only the selected date range fills in blue. You read the period that matters and keep the months around it as context.
The phone carries the same chart above the holdings list. Each coin gets its own small bar chart between the name and the amount, so you can scan the whole portfolio for movement without opening a single coin.
Trading screens get busy fast. This one stays light and calm, so the numbers lead: total value, realized and unrealized P&L and open positions, all on one screen.
Designed by the Hue & Machine team.
#Crypto #Fintech #DashboardDesign #TradingPlatform #DataVisualization #UIDesign #ProductDesign #WebApp #MobileDesign #FigmaDesign
Nice Ui Dmytro
Quote Follow-Up Automation for HVAC & Plumbing
Most home-service quotes don’t get rejected, they just go quiet. I built a system that follows up on them automatically.
What it does
Takes each quote through a simple form
Schedules up to 8 timed texts over 30 days
Stops instantly on a reply, a STOP, or a booked/lost update
Uses AI to draft replies to objections, with a human approving every one
Built with safety first
No duplicate texts, even when processes overlap
Only contractor-approved wording is sent
Texts go out only during local business hours
Opt-outs are honored immediately
Stack: n8n, Postgres, Groq, Docker, Twilio
Status: built and tested end to end, ready to pilot.
I build automation systems like this for service businesses. Message me if you’d like one for yours😊 .
Your Logistics Team Shouldn't Have to Chase Every Shipment Manually. 🚢
A shipment is delayed. Your customer wants an update. Your operations team is checking carrier portals, copying tracking numbers into spreadsheets, and sending the same status emails repeatedly.
By the time everyone has the right information, the next shipment needs attention.
The problem isn't a lack of effort. It's disconnected logistics operations.
Common challenges:
Shipment updates scattered across multiple carrier systems.
Delayed shipments discovered too late.
Manual customer status emails.
Tracking spreadsheets that quickly become outdated.
Repetitive follow-ups between operations and customer service.
Limited visibility into shipment exceptions.
The solution: An automated logistics operations workflow built with n8n.
I can design an automation that connects carrier tracking APIs, your shipment database, and customer communication channels.
Instead of manually checking every shipment, your team receives structured updates when something actually needs attention.
What the automation handles:
📦 Shipment Tracking — Retrieve updates from supported carrier APIs.
🚨 Exception Detection — Identify delays, customs holds, and missed milestones.
🤖 AI-Assisted Updates — Convert complex tracking events into clear, customer-friendly messages.
📧 Customer Notifications — Send relevant shipment updates automatically.
📊 Operations Visibility — Maintain synchronized shipment records and exception histories.
🔁 Escalation Management — Notify the responsible team when an exception requires action.
The goal: Less repetitive tracking work, faster exception awareness, and more consistent customer communication.
Two ways we can work together:
Option 1: Already have carrier APIs, a TMS, or a defined tracking workflow? Share your requirements, and I'll help design the integration.
Option 2: Not sure which logistics tasks should be automated? We can map your shipment lifecycle and identify the highest-value starting point.
Make your logistics operations easier to manage as shipment volume grows.
Workflow architecture
Scheduled Trigger → Carrier API Request → Normalize Tracking Events → Match Shipment Records → Detect Status Changes → Route Exceptions → AI Summary → Customer Email / Operations Alert → Database Update
Implementation: Authenticate carrier integrations, normalize differing event codes, compare timestamps and event IDs, prevent duplicate alerts, route exceptions by severity, and log delivery failures for retry.
Benefits: Reduced manual tracking, clearer exception ownership, more timely customer updates, and an auditable shipment history.
Result: A centralized shipment monitoring workflow that allows operations teams to focus on resolving exceptions instead of repeatedly checking tracking portals.
SEO Keywords
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Hashtags
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The customs-hold exception is the one I'd find hardest to route, since it needs a different owner than a plain delay. Do you map each exception type to its own team in the escalation step, or is it one shared alert queue?