Data Engineering & Analytics
Data is only valuable when it is clean, structured, and actionable and increasingly, when it feeds a predictive model. We build robust ETL pipelines, statistical process control (SPC) math engines for factory floors, and layer machine learning forecasting and anomaly detection on top so dashboards don't just report what happened, they flag what's about to.
What you get with
Data Engineering & Analytics
From kickoff to production in four steps
Discover
A discovery sprint to scope the problem, audit existing systems, and agree on the metric that defines success.
Design
Architecture, data models, and UI/UX decisions made before code so the build sprint has no open questions.
Build
A focused build sprint shipping working software in weekly increments, not one opaque delivery at the end.
Ship
A supervised rollout with your team, plus monitoring and drift checks so day one in production isn't a leap of faith.
Live Projects Built Under Data Engineering & Analytics
4 production applications shipped for clients worldwide.
Relatable: For Couples
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ULegal AI
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PocketWatch
PocketWatch provides plant-floor personnel with process visualization for SPC (Statistical Process Control) and OEE (Overall Equipment Efficiency). It connects manual inspection stations, line-side PCs, and PLCs into a cloud platform.
Arcann Waste Pilot
WastePilot is built specifically for dumpster rental and waste hauling operators. It combines routing, dispatching, online ordering, invoicing, and real-time analytics into one simple mobile application.