Hey you all! 🍄 Just finished putting together a case study on this document/order management system I built for a steel business I'm working with. It's been pretty wild - the thing is saving them 5+ hours daily and about $31k annually with a 4:1 ROI. I posted this in my other community but figured some of you might find it interesting to see how it all came together, so I threw together a Loom video walking through the whole process. Happy to share it as a free resource! https://www.loom.com/share/efeb0d336656438b9e44ffa257124bd3?sid=cfd98bd6-b349-4e62-a7df-11ab997c0559

🚀 Project Overview: Designing a contract analysis system for a multi-portfolio family office with 15,000+ vendor agreements spanning 200+ companies. Building an intelligent RAG system that needs to: - Auto-process contracts from existing Google Drive infrastructure - Stream new documents via N8N automation pipelines - Support complex legal queries across the full document corpus - Enable secure client access to the knowledge base 🛠️ Current Tech Stack: - Document Storage: Google Drive (client's existing setup) - Workflow Engine: N8N for document processing automation - Vector Database: Pinecone for semantic search capabilities - Parsing Engine: Evaluating Llama Index Cloud vs Dockling (on-premise) ⚖️ Architecture Decision: Favoring Llama Index Cloud due to superior legal document understanding and managed infrastructure, though client security policies may require on-premise parsing with Dockling. 📈 Scale Considerations: At 15K+ legal documents, I'm prioritizing architecture validation over rapid prototyping to avoid performance bottlenecks during production. 🎯 Seeking Community Input: 1. Pinecone Performance: Real-world experience with 10K+ document collections? Latency/cost insights? 2. Document Pipeline: Google Drive → N8N → Vector DB optimization strategies? 3. Legal Parsing: Comparative experiences with Llama Index vs Dockling on contract documents? 4. Access Control: Implementing secure multi-client access patterns with Pinecone? 🔧 Implementation Scope: Beyond vendor contracts, integrating internal policies and corporate agreements for comprehensive legal intelligence. Target use case: "Find all contracts with auto-renewal clauses expiring in Q3." 🧠 Learning from Veterans: If you were architecting a legal document RAG system today, what would be your non-negotiable design principles? Where did previous implementations hit unexpected complexity?

🎯 The Situation: Just wrapped a discovery call with a family office's general counsel - this could be my biggest project yet. Here's what I'm dealing with: 📊 Client Overview: - Mid-size family office (36 staff) - Managing 200+ investment vehicles - Processing ~10 vendor contracts weekly - 15K+ vendor relationships needing data cleanup - 45+ insurance policies with scattered renewal dates - Heavy manual processes across 7 departments ⚠️ Current Pain Points: - Legal counsel burning 30-60 min per contract review - Assistant playing telephone between departments, vendors, and C-suite - Using basic AI (Gemini) but everything downstream is manual - Clear workflow bottlenecks causing delays and frustration 💡 My Proposed Solution: Start with Phase 1 focused on vendor contract automation, integrating their existing stack (HubSpot, PandaDoc, Asana). Goal is workflow optimization, not just throwing more AI at the problem. 🤔 Where I Need Your Brain: 1. Scope Strategy: Better to laser-focus Phase 1 on vendor contracts only, or present a broader multi-phase roadmap covering their other workflow issues? 2. ROI Math: They won't share counsel's hourly rate. I'm thinking $400-500/hr industry benchmark for family office legal work - does that track? 3. Pricing Structure: Given their scale and $200K+ annual AI spend, should I stick with my usual approach or pivot to project-based pricing? 🛠️ Tech Stack Context: They're not tech-phobic - already using Gemini, HubSpot, PandaDoc, Asana, Google Drive (migrating to SharePoint). The foundation's there, just needs intelligent connecting. 💭 Looking for honest takes on strategy, pricing reality checks, or blind spots I might be missing. This could be a major breakthrough client but I want to nail the approach. What would you do?

Context: Building automation for steel supply company - need to trigger workflows instantly when Excel files are uploaded to Drive subfolders. Current Setup: - Main Drive folder with 20+ vendor subfolders - Files get uploaded to subfolders (not main folder) - Need to trigger n8n webhook immediately on file upload - Currently using 10-minute polling (too slow for business needs) What I've Tried: 1. Google Cloud Pub/Sub + Drive API: Watch registered but no notifications received 2. Google Apps Script Drive triggers: Can't access "From Drive" triggers in UI despite enabling Drive API v3 3. Apps Script → n8n webhook: This part works perfectly when manually triggered The Question: What's the most reliable way to get real-time trigger when files are added to Drive subfolders? Requirements: - Must work with subfolders (not just parent folder) - Sub-second to few-minute response time - Reliable (99%+ success rate) - Integrates with existing n8n workflow

Going live tomorrow with an AI order management system I built for my father's steel distribution business. What we're handling: - Customer POs → auto-processing → QuickBooks - 20-60 orders/day, $400-2000 each - Vendor invoice matching & delivery confirmations - Built with n8n, Airtable, AI matching logic The implementation: - New Airtable workspace where 2 employees can see all orders organized by status - n8n workflows that watch Google Drive folders and auto-process new files - AI parsing for customer POs, vendor invoices, and delivery tickets - Automatic matching and data entry (replacing 5-6 hours of manual work daily) - Telegram notifications to keep everyone in sync Running parallel with the old system for safety, but still... real orders = real money = real consequences if something breaks. [ For those who've deployed client systems: ] What ends up on your testing checklist that we always forget? Already covering the obvious (backups, rollback plan, monitoring). What's the non-obvious stuff that bit you on day 1?