Inventory Management

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  •   Project Title

    AI‑Powered Inventory Management Software

  •   Timeline:

    6–8 Months

  •   Tech Stack:

    Python, FastAPI, React, PostgreSQL, Redis, Kafka, RFID (GS1), REST APIs, Cloud (Azure)

  •   Demo Link:

    Contact Us

  •   Client Name:

    Enterprise & SMB

Contact Our Team

Project Detail:

Our inventory management software gives you real‑time stock control across warehouses, stores, and channels. Track every SKU with barcode or RFID, automate reordering with dynamic reorder points, and forecast demand using machine learning. The result: fewer stockouts, lower carrying costs, and faster fulfillment—globally.

Problem Statement:

Growing brands juggle multiple sales channels, long vendor lead times, and volatile demand. Without accurate, centralized visibility, teams oversell, tie up cash in slow‑moving stock, and struggle with batch & expiry compliance. Legacy tools lack integrations and analytics, making decisions reactive instead of data‑driven.

Solution:

S.T.R.In.G delivers a modern inventory management system that unifies purchasing, warehousing, and order fulfillment. With multi‑warehouse visibility, mobile scanning, and AI forecasting, you’ll optimize safety stock, set smart reorder points, and keep service levels high—without overstock.

Features:

  • Real‑Time Stock Tracking: Centralized SKU ledger with multi‑warehouse visibility and audit trails.
  • Barcode & RFID: GS1‑compliant labels, mobile scanning, and cycle counts with variance reconciliation.
  • Automated Reordering: Dynamic reorder point + safety stock based on demand and lead time.
  • Demand Forecasting: ML‑based forecasts (seasonality, promotions, trends) for purchase planning.
  • Batch/Lot & Expiry Tracking: FEFO/FIFO support, recalls, and compliance reporting.
  • Multi‑Channel Sync: Integrations for Shopify, WooCommerce, Amazon, POS, and marketplaces.
  • Purchasing & Vendor Management: Lead‑time modeling, ASN support, and automated PO recommendations.
  • Warehouse Operations: Put‑away, picking (single/batch/wave), packing, and shipping labels.
  • Analytics & Dashboards: ABC/XYZ analysis, stock aging, dead stock, and service‑level KPIs.
  • Role‑Based Access: Granular permissions, SSO, and detailed activity logs.

Use Cases:

  • Retail & eCommerce: Prevent overselling, sync orders, and accelerate fulfillment.
  • Manufacturing: Track raw materials, WIP, BOM consumption, and finished goods.
  • Pharma & FMCG: Lot/expiry compliance, FEFO picking, and cold‑chain checks.
  • Food & Beverage: Recipe/pack size variants, waste control, and batch traceability.
  • Automotive & Spares: Multi‑location parts stocking and demand seasonality.

Data Science Specific Points:

  • Forecasting: Hierarchical time‑series models (SKU‑store‑channel) with seasonality and event modeling.
  • Inventory Optimization: Service‑level targets drive safety stock and reorder point per SKU.
  • ABC/XYZ Segmentation: Prioritize replenishment and cycle counts for high‑impact SKUs.
  • Anomaly & Fraud Detection: Spot shrinkage, mis‑picks, and unusual movement patterns.
  • Lead‑Time Learning: Bayesian updates on supplier lead‑time variance to reduce late POs.
  • What‑If Planning: Simulate promotions, MOQ changes, and new‑product ramps.
  • BI Dashboards: Executive, planner, and warehouse views with drill‑downs.

Technologies Used:

  • Platform: Django/FastAPI, React, PostgreSQL, Redis, Kafka.
  • Scanning: Barcode/RFID (Zebra, GS1), mobile apps (PWA/Android).
  • AI/ML: Forecasting, optimization, and anomaly detection pipelines.
  • Integrations: Shopify, WooCommerce, Amazon, QuickBooks/Tally, courier APIs.
  • Cloud & Security: AWS/Azure, IAM/SSO, encryption at rest & in transit.