Case Studies
Real deployments with measurable results. See how teams in finance, telecom, energy and logistics use DataSense to cut risk and decide faster.
Showing 1–9 of 13 case studies
How an NBFC Cut Credit Defaults by 34% with Risk Plus
CapitalBridge Finance is an NBFC with a medium-scale business in East and North India. It is particularly strong in Tier-2 and Tier-3 cities. When the number of loan applications increased, setting loan terms and approving credit facilities became inconsistent and difficult.
From Quarterly Guesswork to Daily Foresight: How Meridian Connect Networks Cut Capex Over-Provisioning by 31% with DataSense Insight+
AI-driven demand forecasting and business intelligence help telecom operators identify high-growth regions, optimize network expansion, and make faster infrastructure decision-making.
How Operations Teams Reduce Waste with Unified Performance Metrics
Prior to understanding the sources of waste within organizations, it is essential to consider how all areas of an organization operate under different metric systems or work on different versions of reality. As a result, excess inventory, idle time, defects, rework, and inefficiencies quietly diminish margins.
How Delivery Networks Prevent Delays with Predictive Routing Data
Every day in modern delivery networks, millions of shipments are moved through warehouses, sorting hubs, transport fleets, and last-mile delivery agents. As it is such a complex system, delays do not usually occur due to one single failure; they often happen due to critical operational signals located across so many different systems that the teams cannot see.
How Warehouses Reduce Errors with Real-Time Inventory Intelligence
Modern warehouses have the expectation to provide speed, accuracy and efficiency all at the same time. However, there are still billions of dollars lost by businesses each year due to inventory inaccuracies, picking mistakes and misplaced inventory.
How Retailers Predict Demand Using Unified Sales and Inventory Data
n today’s competitive retail environment, just responding to demand is no longer sufficient. The most successful retailers leverage integrated sales and inventory data to predict their consumers' demands
How Omnichannel Brands Build a Single View of the Shopper
The reality is that in today’s retail environment, consumers are interacting with brands in many different interaction points, including mobile apps, the web, social media, call centers, and marketplaces. In each interaction, a huge set of data is created such as browser history, transactions, loyalty activities, payment options, returns, and reviews. While each data set is telling part of the story alone, in order for brands to get the complete picture, they have to aggregate all the data.
How BFSI Companies Detect Fraud Earlier With Integrated Signal Monitoring
The BFSI industry is producing an enormous amount of data every second from mobile banking applications right up to banking transactions at the branches and ATMs. Although it has introduced advanced financial services into the industry, it has also raised the risk of fraud.
How Logistics and Supply Chain Companies Achieve Visibility
Logistics and supply chains run on one critical question: “Where is everything right now?” As delivery networks scale, that question becomes harder to answer. Orders flow through warehouses, trucks, hubs, partners, and cities. Each generates more data that is often stored in disconnected systems.