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End to End client onboarding automation with contracts, invoices, and emails
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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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would actually use this lol. the customizable part is what runners care about
Business owners: you get one AI automation free this month. Which one do you take?
A. AI support inbox. Every customer email gets a drafted reply in your tone. You read it, click approve, done. Nothing goes out without you.
B. AI lead qualifier. Every new lead is scored, summarised and dropped into your CRM with the next step, so you only call the ones worth calling.
Both run on n8n + OpenAI, connect to the tools you already use (Gmail, HubSpot, Slack, Sheets) and take me about a day to set up.
Vote below. Then comment with what is eating most of your week right now. The 3 most painful answers get it built for free and I will post the before and after here.
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The one day setup estimate holds only if your existing Gmail and HubSpot data is already clean. Most businesses spend longer fixing inconsistent tags or messy history before the AI can actually qualify leads accurately.
Agri Guard is a full-stack web application that helps farmers identify plant diseases instantly using AI. Users can upload a photo of an affected plant or describe symptoms in text, and the app returns a diagnosis along with a verified treatment plan.
What I built:
A clean, dark-themed landing page with a hero section, trust badges, feature highlights and clear call-to-action buttons (Get Started, Login to Dashboard)
A Node.js and TypeScript backend with REST API routes, utility modules and environment-based configuration
AI integration for image analysis and text-based diagnosis through the OpenRouter API
A disease database with treatment recommendations, plus scripts to extend it with new diseases
Login and dashboard flow for returning users
My focus: a clear, conversion-friendly landing page, readable typography, consistent spacing and a responsive layout that works on both desktop and mobile.
How do you connect the model's diagnosis to the treatment database? Does it have to match a known disease entry before showing a treatment, or can the model generate recommendations outside that list?