Cover image for Project Title:
Inventory Management Automation System

Project Title: Inventory Management Automation System : Real-Time Engine + AI Reporting + Conversational Query Layer Explore the build: Full n8n workflow JSON, database schema, SQL scripts, and architecture documentation on GitHub: https://github.com/anshudainsights3/inventory-automation.N8N/tree/main Most businesses don't lose money on inventory because of bad decisions they lose it because the data they're deciding from is already out of date. A spreadsheet updated five minutes late is enough to oversell a product, miss a reorder window, or misjudge demand. I designed and built this system to close that gap, not with a single automation, but with three independent modules working off one shared source of truth. Real-Time Inventory Engine every sale, return, damage report, or manual adjustment is processed the moment it happens. Stock is updated, the movement is logged for a full audit trail, and reorder thresholds are checked instantly. When stock runs low, the system automatically generates a purchase request, routes it for approval, and notifies the supplier no manual follow-up required. Inventory Intelligence Pipeline runs on its own schedule, completely decoupled from live operations, so reporting never slows down transactions. It calculates KPIs, generates AI-driven insights, and delivers a dashboard and PDF report automatically. Conversational Inventory AI an AI agent that answers natural-language questions about stock levels by querying PostgreSQL directly. No guessing, no stale summaries answers come straight from the live database. The architecture decision that mattered most here was keeping these three modules independent. Real-time processing, scheduled analytics, and conversational AI have different speed requirements, different failure tolerances, and different scaling needs bundling them into one workflow would make the whole system fragile and harder to extend. This way, each module can be improved, scaled, or replaced without touching the others. What this solves for a business: Stock counts that are always accurate, not "accurate as of the last manual check" Reorder decisions that happen automatically instead of being noticed too late Reporting and insights delivered without anyone having to build a report A way to ask direct questions about inventory instead of digging through spreadsheets Tech Stack: n8n · PostgreSQL · Gemini / OpenAI · JavaScript · Webhooks · HTML & PDF Reporting · Email Notifications

Anshu Rajput

n8n Automation Engineer | Helping Businesses to Automate