American Bank. 35 million documents. No organization. 275 different document types mixed together. Manual classification would take years. AI did it in 2 weeks. THE DOCUMENT NIGHTMARE: Decades of files: - Loan applications - Bank statements - Tax returns - Asset verification - Compliance filings - Historical records All in shared drives. No naming convention. No searchable index. Compliance audits = nightmare. "Find all 2018 commercial loan docs" = weeks of manual searching. THE 4-NODE WORKFLOW: 1. Scan document folders 2. Convert PDFs and images to text 3. Classify by document type (loan app, tax return, etc.) 4. Extract key metadata (date, account number, dollar amount) 5. Build searchable database THE CHALLENGE: 35 million documents = expensive if you process everything. Solution: Process in batches, prioritize by business need: - Regulatory compliance docs first (immediate audit risk) - Active account documents second - Historical archives last Total processing: 2 weeks for critical docs, 3 months for full archive. THE IMPACT: Before: - Audit request: "All 2020 mortgage applications" - Time to comply: 2-3 weeks manual search - Cost: $18,000 in staff time After: - Same request: 15 minutes database query - Cost: $0 incremental - Audit compliance time: 94% reduction THE MORTGAGE PROCESSING USE CASE: Once classified, built automated loan processing: - Applicant uploads docs - System pulls income, employment, assets - Pre-fills underwriting system - Flags missing documents Loan processing: 30 days → 3 days. THE SALES ANGLE: Don't sell "document classification." Sell "you have 35 million documents you can't find when auditors ask. I make them searchable in 2 weeks." Compliance fear > efficiency desire. 📚 All templates library in Github What business has years of documents they can't search when they need them?

Hey guys, I've spent the last 7 days building this system. I helps you reverse engineer the strategy of any LinkedIn profile. So you can take a top creator from your niche, and have and get a super detailed report on how to replicate their success. Both their content strategy and sales strategy 💰 And I'm sharing this tool 100% free. I hope it helps on your personal branding journey. Use it here: https://www.buildauthority.ai/profile-analysis

Hey friends! As many you you might now, for the past 5 months I've been focused on building AI automations for content, and specifically for LinkedIn. So I just dropped an in-depth tutorial about how to use AI to grow on this platform. Spoiler: 100% automated approach doesn't work. This video gives concrete tactics and actionable systems that you can start using TODAY. Hope you enjoy 🙌🏻 Btw, is there anyone actively growing LinkedIn? IMO it's the best B2B social media platform and many people really underestimate its' potential.

Hey everyone 👋 I’m doing a bit of research around n8n usage and real-world pain points, and I’d love your input. If you could add one new n8n node (or significantly improve an existing one), what would you choose and why? Is there something you constantly have to hack around with HTTP requests, custom code, or external tools? No right or wrong answers here — I’m genuinely trying to understand where the biggest gaps are for people building automations daily. Looking forward to your thoughts 👀