AI finally solved real estate’s biggest time waster. For months, I’ve been hacking together automations with Make.com, N8N, GPT, and Claude to extract numbers from broker packages. Frustrating doesn’t cover it. Yesterday I saw a demo from Nethanel Lasri at Siftt.ai that—if it works as advertised—is a breakthrough. What they claim to do: → Takes any broker package → Extracts every number with 99% accuracy  → Drops it straight into YOUR Excel model for download → Scores deals against your buy box before you analyze The bottleneck in underwriting isn’t just thinking. It’s typing. Here’s the reality: You get 100 deals from brokers. Maybe 20 fit your criteria- unit count, geography, asset class. Many platforms make you dig through everything. Siftt.ai scores them upfront based on your parameters. Three things that separate this from every failed “AI underwriting” demo: 1. Accuracy without hallucinations Clean number extraction. No GPT-style made-up figures. 2. Enterprise security Data stays in siloed environments. Critical for NDA work. 3. Smart expense mapping AI learns how you classify line items and codes correctly to your model. Biggest takeaway:After emailing the broker package, you download extracted data (T12s, rent rolls, everything) directly into your own Excel model. Your model. Your formulas. Your assumptions. Reality check: I only saw the demo. This doesn’t replace judgment. It won’t catch suspicious expenses or question broker “comps.” And smooth demos don’t always mean smooth reality. But if it works? Game changer for high-volume shops. Worth watching.