Real Results for Real Businesses

Detailed breakdowns of how we've helped leading organizations across India solve complex challenges and achieve measurable outcomes.

150+
Projects Done
₹200Cr+
Value Created
3.2x
Avg ROI
97%
Retention
FinTech · AI & ML
AI-Powered Fraud Detection Saved ₹50Cr for Leading NBFC

IndiaFirst Finance was losing ₹80Cr+ annually to sophisticated fraud rings exploiting gaps in their rule-based detection system. Transaction volumes were growing 40% YoY, making manual review impossible at scale.

The Challenge

2M+ daily transactions, 15-minute review windows, legacy rule engine with 34% false positive rate causing legitimate customer friction, and increasingly sophisticated synthetic identity fraud.

82%
Fraud Reduction
₹50Cr
Losses Prevented
6 mo
Time to Value
Our Solution
Real-time ML scoring engine processing 2M+ transactions/day with sub-100ms latency
Ensemble model combining GBM, neural network, and graph analytics for synthetic identity detection
Behavioral biometrics layer analyzing device fingerprinting, typing patterns, and session behavior
Human-in-the-loop review queue for borderline cases, reducing analyst review by 70%
Automated model retraining pipeline with drift detection and shadow deployment
Client Outcome

"Datawind's fraud detection system is the best investment we've made in 5 years. The ROI in year one alone was over 12x." — CTO, IndiaFirst Finance

PythonApache KafkaXGBoostPyTorchRedisAWSKubernetes
Healthcare · Data Analytics
Predictive Analytics Platform Reduces Readmissions by 34% Across 15 Hospitals

MedPlus Hospitals faced high 30-day readmission rates (18.4%) due to inconsistent discharge protocols and limited visibility into post-discharge patient risk across their hospital network.

The Challenge

Fragmented EHR systems across 15 hospitals, no unified patient data model, clinical staff resistant to algorithmic tools, and strict HIPAA-equivalent data governance requirements under Indian health data laws.

34%
Readmission Drop
15
Hospitals
₹18Cr
Cost Saved/Year
Our Solution
Unified patient data lakehouse integrating 15 different EHR systems via HL7 FHIR APIs
ML risk scoring model identifying high-risk discharge patients with 87% accuracy
Clinical dashboard with explainable AI alerts integrated into nurse workflows
Automated post-discharge follow-up trigger system with SMS and WhatsApp integration
DPDP Act compliant data governance framework with audit trails
Client Outcome

"For the first time, our clinical teams have real-time visibility across all 15 hospitals. The system has materially improved patient outcomes." — Director IT, MedPlus Hospitals

PythonDatabricksdbtPower BIFHIR APIsAzure
Retail · Cloud Infrastructure
Cloud Migration Enables 3x Growth for Leading Retail Platform

RetailMax's aging on-premise infrastructure was buckling under Diwali sale load spikes, causing cart abandonment losses of ₹4Cr during their biggest sales events. Their monolithic architecture made deployments risky and slow.

The Challenge

15-year-old monolithic Java application, 6-week release cycles, inability to scale beyond 50K concurrent users, and a 4-hour planned downtime window each deployment — unacceptable for a 24/7 retail platform.

3x
Scale Capacity
99.99%
Uptime
40%
Infra Cost Saved
Our Solution
Strangler Fig pattern migration — incrementally replacing monolith with microservices
Event-driven architecture on AWS with SQS, SNS, and EventBridge
Auto-scaling EKS clusters handling 200K+ concurrent users during peak sales
Zero-downtime blue/green deployments reducing release cycle from 6 weeks to 2 days
Comprehensive observability with OpenTelemetry, Grafana, and PagerDuty
Client Outcome

"Last Diwali was our best sale ever — 3x the volume with zero downtime. Datawind delivered what seemed impossible." — VP Technology, RetailMax

AWS EKSTerraformJava/SpringPostgreSQLRedisGitHub Actions
Logistics · AI & Optimization
Route Optimization AI Cuts Delivery Costs by 28% for LogiFlow

LogiFlow Technologies was operating 2,000+ delivery vehicles across 12 Indian cities with static routing — leaving massive efficiency gains on the table as fuel costs soared and customer delivery expectations tightened.

The Challenge

Manual route planning taking 3+ hours each morning, 22% of deliveries missing SLAs, fuel costs growing 18% YoY, and no real-time re-routing capability when traffic or delivery exceptions occurred.

28%
Cost Reduction
94%
SLA Attainment
18 min
Route Planning Time
Our Solution
Reinforcement learning route optimizer considering 40+ variables including traffic, time windows, and vehicle capacity
Real-time re-routing engine processing live traffic data from Google Maps and Ola Maps APIs
Driver app with turn-by-turn navigation and exception reporting (Flutter, offline-first)
Demand forecasting model predicting next-day delivery volumes by zone with 91% accuracy
Operations dashboard with live fleet tracking and KPI monitoring
Client Outcome

"The Datawind route optimizer has transformed our operations. We went from 78% to 94% SLA attainment in 3 months." — CEO, LogiFlow Technologies

PythonOR-ToolsReact NativeFastAPIPostgreSQLGCP
Manufacturing · IoT & AI
Predictive Maintenance Platform Reduces Downtime by 67% for Auto Parts Manufacturer

BharatAuto Components was experiencing ₹12Cr in annual losses from unexpected machine downtime at their 3 plants. Reactive maintenance meant production disruptions lasting 4-8 hours per incident.

The Challenge

400+ CNC machines with no sensor instrumentation, legacy PLCs with no data connectivity, maintenance teams relying on manual inspection schedules, and zero visibility into machine health trends.

67%
Downtime Reduction
₹8.5Cr
Annual Savings
400+
Machines Monitored
Our Solution
IoT sensor retrofit kit deployed on 400+ CNC machines capturing vibration, temperature, and current draw
Edge computing layer with NVIDIA Jetson processing sensor streams locally for low-latency alerts
Anomaly detection ML models trained on 18 months of historical failure data
Maintenance work order automation integrated with SAP PM module
Digital twin visualization of factory floor with real-time health heatmap
Client Outcome

"We predicted and prevented 23 major machine failures in the first year. The system paid for itself in 4 months." — Plant Head, BharatAuto Components

PythonMQTTInfluxDBGrafanaTensorFlowAWS IoT Core

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