Case Studies
Proof, not promises.
Production deployments running today.
From legacy chaos to a four-tier data operating system.
In production since December 2024 · legacy stack fully retired October 2025.
Where they were
A multi-channel retail group with data fragmented across six systems — eCommerce, ERP, OMS, marketing automation, marketplaces, paid ads. The legacy stack ran on aging on-prem infrastructure. Over 100 dashboards had been built over the years, most of them stale or contradicting each other. Every board meeting turned into a debate about which number was right. Leadership had stopped trusting the dashboards.
What we built — the four tiers
Modern warehouse, legacy retired
Cloud warehouse + transformation layer in production since Dec 2024. Six sources unified. Legacy on-prem ETL fully retired by Oct 2025.
Decision-grade dashboards
Customer, Wholesale, Procurement, Outbound, and Inventory dashboards live. ~70% of legacy dashboards retired after audit.
Self-running ops with tiered alerts
Pipeline + dashboard refresh monitoring with critical / warning / healthy states. Automated weekly commercial reports running since March 2026. Anomaly + threshold alerts to ops channels.
Foundation built, agentic insights piloted
11 million market-basket pairs modeled — the feature base for recommendations. Insight agent prototype running on weekly merchandising data. ML models scheduled for Q1 2027.
Impact
1.6M
AED revenue blind-spot identified (off-channel orders)
3M
AED BI vs ERP inventory gap quantified
41%
customer base flagged at-risk via cohort analysis
100→30
dashboards rationalized after audit
Leadership now trusts a single number. Finance, commercial, and ops all run on the same governed platform. The team owns every line of code in their Git org and every account on their cloud bill — if 8020 stopped tomorrow, the platform keeps running.
Your data could be next.
A fixed-price Diagnostic is the entry point. We’ll tell you exactly where your data is broken — and what to fix first.