Designing and delivering modern data and AI platforms
that drive measurable enterprise growth.

From data engineering and cloud architecture to AI, analytics, and governance — we deliver end-to-end data platforms built for scale, reliability, and performance. Our expertise spans Microsoft Fabric, Azure, AWS, and GCP, helping enterprises modernise their data stack, enable real-time insights, and deploy production-grade AI solutions with confidence. Operating from London and Islamabad, we partner with global organisations that demand precision, scalability, and results.

47+

Projects Delivered

30+

Clients Globally

$500M+

Data Under Management

99.9%

Pipeline Uptime SLA

Technology Ecosystem

The platforms our practice is built on

We recommend only what we've shipped in production. Every platform here has live client deployments behind it.

Microsoft Fabric

Core Platform

Microsoft Azure

Advanced Specialist

Databricks

Ecosystem

Amazon AWS

Advanced Specialist

Snowflake

Ecosystem

Google Cloud

Ecosystem

Power BI

BI & Analytics

Terraform

Infrastructure

What We Deliver

Six practice areas. One standard of delivery.

Every engagement ends with production-running code, tested and documented. We don't hand off architectural diagrams and leave.

Selected Work

Projects defined by measurable outcomes

We measure success by business impact — latency reduced, revenue generated, costs cut — not by deliverables shipped or hours billed.

View all 47 projects
Data EngineeringManufacturing

Microsoft Fabric Enterprise Data Platform

A global manufacturer operated 12 disparate data systems with no unified analytics layer, causing 48-hour reporting delays and an inability to correlate production, supply chain, and financial data.

95% reduction in reporting latency (48 h → 2 h)

$2.3M annual operational savings

Microsoft FabricOneLakeApache SparkPower BI+2
Data EngineeringRetail

Azure Data Factory ETL Modernization

A Fortune 500 retailer ran 340 overnight batch ETL jobs with 200+ manual intervention points per week. Data freshness lagged 24 hours, blocking same-day markdown and inventory decisions.

87% reduction in manual interventions (200 → 26/week)

Data freshness improved from 24 h to 15 min

Azure Data FactoryAzure SQLBlob StorageAzure Monitor+2
Data EngineeringE-Commerce

Real-Time Kafka Streaming Pipeline

A 50M-user e-commerce platform ran fraud detection on 4-hour batch cycles, losing an estimated $2M/month in preventable fraudulent transactions that slipped through the detection window.

Fraud detection latency: 4 h → <200 ms

$1.8M/month in prevented fraudulent charges

Apache KafkaApache FlinkAzure Event HubsAzure Stream Analytics+2
Data EngineeringRetail

Microsoft Fabric Lakehouse for Retail

A national specialty retailer with 800 stores operated disconnected POS, inventory, and e-commerce systems. No unified customer view existed, causing fragmented personalization and inventory blind spots.

Customer 360 achieved for all 18M customers

Inventory accuracy improved 23% across 800 stores

Microsoft FabricOneLakeApache SparkPower BI+2

Get Started

Your data is an asset that's probably underperforming.

Most organisations know their data is valuable. The gap is the infrastructure, governance, and engineering capability to realise that value consistently. That's what we do.

No obligation on the first call

Response within 1 business day

Microsoft Fabric Certified team

NDA available before any technical discussion