Case Study

Supplin

AI-Powered Supply Chain Assistant: Built to reduce inventory waste, streamline procurement, and empower teams with intelligent stock decisions

A mid-sized manufacturing company approached Galific with a persistent problem: chronic overstocking of slow-moving SKUs, frequent stockouts of fast movers, and procurement teams constantly firefighting emergency orders. They had years of purchase orders, sales data, and inventory records but no clear way to turn that data into predictive intelligence. We proposed a supply chain data audit to assess whether their data could support intelligent forecasting and automated reorder recommendations.

The audit revealed powerful patterns: sales velocity, lead times, and shelf life data contained clear predictive signals. 80% of their stockouts were preventable with proper lead time analysis. Their data had the intelligence needed, it just required smart algorithms to surface it. With this confirmed, we built Supplin, an AI assistant that shifts teams from reactive firefighting to proactive planning.

We helped design the platform’s:

Predictive reorder engine using real-time sales velocity and lead times Smart alerting system for stockouts, overstock, and dormant SKU identification Clean, actionable dashboard with contextualized insights Vendor performance tracking and SLA monitoring

Key Highlights

01 Helped launch Supplin, a centralized AI-driven supply chain management system
02 Designed intelligent dashboards to visualize inventory health, reorder timelines, and wastage risks
03 Integrated sales, purchase, and vendor data into a single source of truth
04 Enabled predictive stock suggestions based on seasonality, trends, and consumption velocity
05 Built automated alerts for stockouts, overstock, expired goods, and unusual purchase spikes
06 Reduced manual procurement guesswork through AI assisted order recommendations
07 Delivered up to 42% reduction in inventory related costs for early adopters
08 Prevented last-minute order rushes, leading to smoother vendor coordination and better pricing
09 Ongoing collaboration with Galific for expansion into warehouse automation and logistics intelligence

At Galific, We know that supply chain teams operate in a high stakes environment where even a single missed stock order can disrupt entire operations. Supplin was built with this urgency in mind to shift teams from reactive firefighting to proactive planning. Our role was to bring together data science, product thinking, and intuitive UI design to create a tool that’s not just smart, but simple to use

The Challenge

Procurement teams were working across siloed spreadsheets, outdated ERP reports, and manual forecasts. This led to chronic overstocking of slow-moving SKUs, stockouts of fast movers, and delayed reordering cycles. As a result, working capital was blocked, vendor relationships strained, and service levels compromised.

The Audit-First Approach

We interviewed supply chain managers, warehouse heads, and procurement leads to identify where the time sinks were. We analyzed 18 months of their purchase and sales data to identify patterns in demand cycles, lead time variability, and inventory turnover. The data proved that predictive algorithms could forecast reorder needs with 85%+ accuracy, making proactive planning not just possible, but practical.

The Solution

Predictive Reorder Intelligence

Supplin's core algorithm uses real-time sales velocity, lead times, and shelf life data to predict reorder needs before they become urgent. The system learns from past purchases and usage patterns to continuously optimize its recommendations.

Actionable Alerts

No clutter, no noise. Every alert is contextual, every chart has a purpose, and every forecast is grounded in real-time data.

Dormant SKU Detection

The platform automatically flags slow-moving or dormant inventory, helping teams reduce deadstock and free up working capital.

The Results

42% Reduction in Inventory Costs - By highlighting overstock risks and aligning procurement with demand, organizations saw significant reduction in inventory-related costs within the first quarter of use.

70% Fewer Emergency Orders - Clients reported smoother purchase cycles with significantly fewer last-minute rush orders and expedited shipping costs.

85% Improvement in Stock Availability - Stockout incidents of fast-moving SKUs dropped dramatically. Service levels improved, and customer satisfaction increased

3x Faster Procurement Planning - Procurement heads could now plan in weeks, not days. Supplin made inventory planning faster, smarter, and data-backed.

₹25L Working Capital Released - Reduction in overstocked inventory freed up significant working capital for strategic investments and operations.

Better Vendor Relationships - Predictable, planned orders improved vendor communication and negotiation power, leading to better pricing and terms.

60% Less Time on Reconciliations - Automated tracking and real-time dashboards eliminated manual spreadsheet reconciliations and data entry errors.

Improved Demand Forecasting Accuracy - Prediction accuracy improved from 60% (manual) to 85%+ (AI-driven), reducing both excess inventory and stockouts.

Key Technologies Used

Backend & Data Infrastructure

Node.js

Python

SQL

Front-End Development

ReactJS

NextJS

D3.js

Conclusion

Galific's expertise in intelligent systems, combined with a deep understanding of supply chain workflows, enabled the creation of Supplin, a digital assistant that brings calm, clarity, and control to inventory operations. The audit-first approach ensured we built recommendations the data could actually support. With Supplin, procurement teams no longer just manage stock, they master it.