12 stores. 5 days to produce a sales report. Stockouts discovered only when customers walked out empty-handed. We built a cloud-native SaaS platform that made every SKU across every location visible in real time, automated demand forecasts 90 days out, and put actionable dashboards in front of every layer of the business — from store floor to executive suite.
A retail chain operating 12 locations across three cities had outgrown its manual operations by at least two years. Purchasing was driven by experience and instinct — not data. Store managers emailed stock requests to a central buyer who had no real-time picture of what was selling. Regional leadership received performance reports 5 days after the fact, by which time the decisions those reports should have driven were already late. Stockouts and overstock were estimated to be costing 8–12% of monthly revenue.
The platform didn't just digitise their spreadsheets — it replaced the decision-making process entirely.
Review how Aavya LabTech designed and built the inventory visibility, credit ledgers, and forecasting modules:
"A retail brand selling apparel online through a WooCommerce storefront and offline in physical branches needs real-time stock synchronization."
Double-selling occurs when online customers purchase items that were just sold in-store. Catalog maintenance is also doubled, requiring manual data reentry across multiple databases.
Establishes structured SKU patterns as a bridge. The webhook router (/api/woocommerce/webhook/{tenant_id}/orders) verifies HMAC signatures to receive checkout events from WooCommerce, updating inventory across locations in real-time.
"A retail manager introduces a new jacket style that comes in 8 colors and 6 sizes (48 unique variations) and needs to register them quickly."
Generic storefront platforms enforce a hard 100-variant limit and force tedious manual SKU/barcode entries for every single color and size combination.
Uses structured Product, ProductSKU, and AttributeValue models. The SKU generator (/api/sku) automatically outputs variants based on category, brand, color, and size permutations with price overrides.
"A customer wants to browse the product catalog, check stock availability, and place an order directly via WhatsApp."
Downloading large PDF catalogs is slow, and customers find mobile web checkout processes too complex on slow network connections.
The WhatsAppBotService handles messages using an FSM (IDLE -> BROWSING -> CHECKOUT). It sends interactive lists of SKUs with live stock details. B2B buyers purchase via credit, while B2C uses UPI/COD links.
"A garment manufacturer manages multiple wholesale distributors who purchase in bulk on different pricing tiers and expect credit payment terms (Udhari)."
Standard e-commerce checkouts demand upfront credit card payments and fail to support dynamic bulk discounts, credit-limit enforcement, or Net-30/Net-60 payment terms.
The B2B module (/api/b2b) tracks credit limits and tiers (Gold/Silver). The wholesale matrix applies bulk breaks, and checkout validates totals against available credit, tracking payment due dates.
"A retail buyer needs to plan purchase orders for the upcoming season without overstocking or running out of hot items."
Over-ordering leads to dead stock and tied-up capital, while under-ordering results in missed sales. Manual calculations fail to identify subtle seasonality trends.
The forecasting service (/api/ai/forecast/{sku}) applies Facebook Prophet on historical sales data to predict SKU demand 7 to 90 days out. The suggestions engine (/api/ai/reorder-suggestions) auto-drafts procurement records.
"A WhatsApp retail customer chooses online payment and needs a secure way to pay immediately."
Sharing static bank details requires manual verification of screenshots, leading to fulfillment delays and fraud risks.
On WhatsApp checkout, the bot calls RazorpayService to create a single-use payment link with a 15-minute window. Payments verify via webhook, updating payment_status and pushing orders to dispatch queues.
"A buyer searches for a popular SKU (e.g., MSHRT-NIKE-L-BLK) on WhatsApp but finds it out-of-stock."
Customers walk away from out-of-stock items, and the merchant loses sales data on lost interest.
Offering a NOTIFY option logs the user's phone and requested SKU in StockWatchlist. Once inventory replenish cycles run, the system scans logs and broadcasts WhatsApp alerts to waiting buyers.
"Store owners need cashier staff to handle checkout transactions without exposing backend financial reports or stock valuation data."
Standard shared logins leak procurement cost margins, and lack of shift cash reconciliation makes audit trails impossible.
Enforces RBAC (Owner, Manager, Cashier, Accountant). Cashiers open/close shifts with drawer verification counts. The close-shift workflow calculates drawer variance in audit logs, supporting quick PIN-based shared terminals.
Every module below was scoped, built, and deployed as part of a single end-to-end engagement.
A robust retail SaaS platform requires real-time inventory management across all store locations, sales analytics and reporting dashboards, demand forecasting, POS system integration, customer purchase history tracking, supplier management, and role-based access for store managers and executives. Cloud-native architecture ensures scalability during peak seasons.
Predictive demand forecasting uses machine learning models trained on historical sales data, seasonality patterns, promotional calendars, and external signals like weather or local events to predict future product demand at the SKU level. This helps retailers optimise stock levels, reduce overstock and stockouts, and plan purchasing more accurately.
Yes. Modern retail SaaS platforms can integrate with major POS systems through REST APIs, webhooks, or middleware connectors. Aavya LabTech builds custom integration layers that sync transaction data in real time, ensuring your dashboards and inventory counts always reflect the latest in-store activity.
Whether you manage 2 locations or 200, Aavya LabTech can build the inventory visibility, forecasting, and analytics platform your retail business needs to stop losing revenue to stockouts and start competing on data.
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