Automate Inventory Management with a Custom AI System

Many small warehouses run on a combination of their WMS and spreadsheets. A system like SkuVault or Fishbowl is excellent for tracking current on-hand quantities and locations. But their forecasting capabilities are often limited to simple sell-through rates. These tools cannot distinguish a one-time promotional spike from a genuine trend in demand, leading to expensive ordering mistakes.

Consider a 15-person 3PL managing inventory for multiple e-commerce clients. They run a successful Black Friday sale for one client. Their WMS forecasting module sees the massive sales volume in November and recommends a huge reorder in December. The system cannot incorporate the external context that this was a marketing-driven event. The warehouse now holds excess seasonal inventory, tying up thousands in capital and valuable shelf space.

To compensate, managers export data to Excel for manual analysis. This process is slow and error-prone. A single copy-paste error or broken VLOOKUP can corrupt an entire forecast. The manager spends hours manipulating data instead of making strategic purchasing decisions. The fundamental issue is that these off-the-shelf systems are built to be a system of record for what you have, not a predictive engine for what you will need.

The first step is a data audit. Syntora would connect to your WMS and sales platforms like Shopify or Amazon Seller Central to extract at least 12 months of sales and inventory data. This process identifies the signal quality for forecasting and surfaces any data gaps. You would receive a brief report outlining data readiness and a clear plan before any development begins.

The technical approach would involve a Python-based time-series forecasting model. The model is wrapped in a FastAPI service, deployed on AWS Lambda for cost-effective, serverless operation. This service runs on a daily schedule, pulling the latest sales data, updating forecasts for every SKU, and calculating optimal reorder points based on supplier lead times and desired safety stock levels. A daily job could process 10,000 SKUs in under 15 minutes for less than $50 per month in hosting fees.

The delivered system integrates with your current workflow. It can send a daily CSV to your purchasing manager, push recommendations to a Google Sheet, or make a direct API call to your WMS if it supports it. The output is not a black box; it is a clear list of SKUs to order, suggested quantities, and flags for slow-moving stock that may need to be discounted. The goal is a 4-week build cycle from kickoff to a deployed, working system.