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Most CRMs just store your leads. The good ones work them for you.
This is a concept design based on the CRM work I do (like Knit, my multi-tenant CRM): a dashboard with an AI assistant built in. You type "send follow-ups to warm leads who haven't replied in 3 days" and it drafts, sends and logs everything in the pipeline.
How I'd build it:
- Next.js / React dashboard + React Native mobile app
- NestJS or Laravel API with PostgreSQL
- OpenAI / Claude / Gemini with automatic failover, so the assistant never goes down
- Automations, email, Stripe and webhook integrations
Need a CRM, AI chatbot or internal tool like this for your business, web or mobile? Hire me here on Contra. Send me a message or check my services.
What's the first thing you'd want an AI assistant inside your CRM to do?
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Shopify Abandoned Cart Recovery Automation 🛒
Ever wondered how many potential orders an online store could miss when customers add products to their cart but leave without completing checkout?
I built an abandoned cart automation workflow using Activepieces, Shopify, Google Gemini, Gmail, and WhatsApp Business.
⚙️ How It Works
🛒 Cart Trigger: Detects an abandoned checkout event from Shopify.
🔀 Conditional Routing: Routes the workflow based on configured conditions.
🤖 AI-Powered Messaging: Gemini generates a personalized reminder message.
💬 WhatsApp Reminder: Sends a cart reminder through WhatsApp Business.
📧 Email Reminder: Sends a follow-up email to encourage the customer to complete checkout.
💡 How It Can Help E-commerce Businesses
Remind customers about products left in their carts.
Reduce repetitive manual follow-up work.
Make customer communication more consistent.
Create an opportunity to recover potentially lost sales.
Tools Used: Activepieces | Shopify | Google Gemini | Gmail | WhatsApp Business
Project Type: Personal Automation Project
I built this workflow to demonstrate how automation can support abandoned cart recovery for Shopify and D2C businesses.
Interested in automating your store's customer follow-ups? Let's connect.
The 30–60 minute delay then 24-hour follow-up is a sensible cadence. The part I would harden next is the stop conditions: once the cart converts or the customer replies, every channel should cancel, and WhatsApp especially needs a clear opt-in trail before the first send....
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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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?
This is officially my first interface designed not with my hands, but with my voice.
We talk a lot about AI changing our workflows, but experiencing it firsthand shifts your entire perspective. I wanted to see how far I could push a pure AI-to-UI pipeline for a complex digital asset management workspace, prioritizing LLM logic and voice commands over manual pixel manipulation.
Here is how this hybrid process actually played out:
01 / The Logic: Instead of sketching, I started by mapping out the structural architecture and edge cases in Claude, generating a solid low-fidelity blueprint.
02 / The Voice: This was the wild part. Armed with detailed usability specs and moodboards, I used voice prompts in Figma AI to establish the high-fidelity visual foundation. I literally spoke the core UI into existence.
03 / The Human Touch: I processed the raw output through Claude again to adjust specific UI parameters, and then finally stepped in for a strict manual polish. Perfect grid alignment and sharp visual hierarchy still require a designer's eye.
04 / The System: To wrap it up, I reverse-engineered the polished interface back through Claude to automatically construct a fully scalable atomic design system, complete with defined components and local variables.
The role of a product designer is fundamentally shifting. We are spending less time executing and more time directing architectural logic and curating systems.
I would love to hear how you all are integrating these new AI pipelines into your daily sprints. Let's discuss in the comments.
#ProductDesign #Claude
