Imagine this 👇 A potential buyer calls your real estate business at 11:47 PM — and instead of missing that lead, an AI Voice Agent answers instantly. 💬 It greets them professionally. 🏡 Answers their questions about the property. 📝 Collects their details (Name, Phone, Address, Inquiry). 📊 Then automatically saves everything straight into your Google Sheet — ready for your sales follow-up. All of this happens 24/7, no missed calls, no human needed. I just finished building a working demo, and honestly… it feels like the future of client communication for real estate. 🎥 Watch the demo here:👉 https://youtu.be/IQXmnUfYbTA?si=ZwVhF4Cza9N-wydC 💭 If you’re in real estate (or know someone who is), imagine how many more clients you could convert when no call goes unanswered. Would love your thoughts — what features should I add next?

Seedance 2.0 is a new AI video model from the Dreamina/CapCut side of ByteDance that’s focused on one thing most video models struggle with consistency across shots Instead of only text-to-video, it supports multimodal references • text • images • video clips • audio clips Dreamina says you can stack up to 12 clips in one project (9 images, 3 videos, 3 audio) and video/audio refs can be up to 15 seconds so you can guide the model with real examples, not vibes What this unlocks for creators • the same character staying stable across multiple shots • smoother scene transitions and camera switches • better audio + visuals lining up like an edited sequence Check out the video I've attached👇

My co-founder Royse one day described a common paint point in the residential construction industry. Many builders find themselves getting screwed over by their change order process. A client asks them, "Hey can you move that electrical outlet over 2 feet?" and contractors either verbally agree without getting anything in writing, OR they actively try to downs-sell customers out of it, simply because of the paperwork headache. This is a problem for two reasons 1) If the contractors only get a verbal agreement 8 times out of 10, the customer will not agree to pay for the work they did on that change order because it was never written down. Clients just assume that it was just a "small change", something minor that didn't require extra payment. 2) A huge loss in extra margin on their jobs, All because the headache of creating these change orders after a long day of work is to much to bear. So I built this solution with all of that in mind, This automation allows contractors to: - Upload and analyze contracts from projects, & store them - Speak messy notes into the app and choose which contract and project the change order is being written for - Instantly generate change orders that automatically apply the relevant tax and material rates to the cost - Once approved send the change order straight to their clients inbox for signature approval, OR let the client sign it their on the spot. I made a SUPER short video showing it off, go ahead and check it out! https://youtube.com/shorts/t7pFgK9Gf_g?si=g-aBaydMbeaaavfH

Closed another client this Sunday for my AI transformation agency! NOW BACK TO WORK BABY!

Mortgage processing. 240 applications annually. Manual qualification consuming 180 hours. Built n8n workflow. Zero manual calculations. Systematic validation. THE MORTGAGE PROBLEM: Every application manual. Loan officer reading documents. Calculating housing payments. Computing DTI ratios. Checking credit. Verifying employment. 45 minutes per application. 240 annually = 180 hours. Audit revealed errors - 34 incorrect DTI calculations. 67 missing credit verifications. 89 inconsistent qualification decisions. 14.2% error rate. Manual process breaking down. Same borrower calculated differently by same loan officer week to week. Different officers applying different standards. No systematic criteria application. THE n8n AUTOMATION: 6-node workflow with 5-path credit routing: Node 1 - Gmail Trigger: Monitors applications Node 2 - Get Email: Downloads with attachment Node 3 - Prepare Binary: Formats document Node 4 - Extract Data: Pulls borrower/income/assets/liabilities/property/loan Node 5 - Calculate & Validate: Computes DTI/LTV/reserves, validates criteria Node 6 - Log Database: Updates tracking Node 7 - Credit Router: Routes by tier (Excellent/Good/Fair/Poor/None) EXTRACTION: Borrower - name, email, employment, income Assets - checking, savings, retirement, investments Liabilities - debts with monthly payments Property - address, type, purchase price Loan - amount, down payment, term, rate CALCULATIONS: ```javascript // Housing payment const payment = (loan * rate) / (1 - Math.pow(1 + rate, -months)); const tax = (price * 0.012) / 12; const insurance = (price * 0.006) / 12; const housing = payment + tax + insurance; // DTI ratios const frontDTI = (housing / income) * 100; const backDTI = ((housing + debt) / income) * 100; // Other metrics const ltv = (loan / value) * 100; const reserves = assets / housing; ``` VALIDATION CRITERIA: Back-end DTI > 43% = Needs Review Front-end DTI > 28% = Conditional Credit < 620 = Needs Review Employment < 2 years = Conditional