We build the systems that show you where bottlenecks form, where inventory ages, and where SLAs slip — before they hit your P&L.
What We Deliver
We don't count lines of code or hours billed. We track whether your ops team can answer questions faster, catch problems earlier, and stop reconciling spreadsheets.
01
Live WIP, TAT, Yield, and Aging — with alerts when a station, vendor, or flow backs up.
02
Finance and Ops see the same numbers. No more reconciliation meetings.
03
Forecasting and anomaly detection deployed reliably, with measurable accuracy and monitored drift.
04
Your team owns what we build. Documentation, training, and maintainable code.
Services
Each engagement is scoped to your specific challenges. Here's where we focus.
Real-time dashboards that unify WIP, TAT, Yield, Aging, and Discrepancies across your operational systems. Catch problems before they become crises.
Cloud data warehouses and pipelines on BigQuery, Snowflake, Redshift, or Azure Fabric — with tested dbt models, orchestration (Dagster, Airflow, Step Functions), and documentation your team can maintain.
Demand forecasting, anomaly detection, and automated decision workflows that deploy in weeks — with measurable ROI and your team trained to maintain them.
Experienced data leadership without the 6-month search and $300K+ commitment. Strategy, roadmap, team mentorship, and hands-on execution.
The Reality
These problems aren't unique to you. They're structural — and they're solvable.
Data lives in WMS, ERP, spreadsheets, legacy systems. When leadership asks for a number, it takes three people and two days. By the time anyone sees a report, it's outdated.
Engineers spend 70% of time on data plumbing. Analysts are stuck in report-factory mode. Everyone's underwater, so infrastructure never improves.
SLA breaches, inventory aging, quality escapes — discovered when customers complain. By then, the damage is done.
Tools that became shelfware. People who left. Projects that stalled. The organization has tried to fix this before — and here you are, still making decisions on spreadsheets you can't fully trust.
Evidence
Anonymized results from recent engagements.
Context: Global repair partner processing 2M+ units annually. Visibility gap was causing inventory aging undetected until P&L impact. Operations Control Tower deployed in 6 weeks.
Context: European railway operator with 500+ stations. Previous data warehouse project had failed twice. Full platform rebuild delivered in 10 weeks with zero data incidents since.
Context: Multinational brand with inventory discrepancies blocking automated replenishment. Unified platform enabled automation within 8 weeks of deployment.
Context: Staffing agency managing placements across multiple clients. Ops team was spending 30+ hours/week on manual reporting. Proactive alerting now catches issues before client impact.
Context: Refurbishment operation. Demand forecasting model deployed in 8 weeks. Anomaly detection identified fraud pattern that would have run another month undetected.
Context: Mid-market company with data team but no leadership. Fractional engagement established strategy, rationalized stack, and defined hiring profile for permanent Head of Data.
Context: Player analytics platform processing match event data across 20+ football leagues. Built full AWS pipeline (Step Functions, Glue, ECS) with ML models predicting performance metrics weekly. Platform serves scouting and squad analysis tools.
Context: Subscription-based health and wellness brand. Built cohort-based renewal and churn analysis across billing cycles, prescription renewals, and plan upgrades. Monthly reporting on retention funnels by product category and dose package.
The Shift
Before
Monday ops meetings start with 45 minutes reconciling different spreadsheets. TAT reports are 3 days old. The inventory aging problem showed up on the P&L — nobody saw it coming.
After
Dashboards are on screen before the meeting starts. Same numbers everywhere. Last week, an alert caught WIP backing up before it became a problem. Fixed in two hours.
Before
Data everywhere — SAP, two WMS systems, 50 Google Sheets, databases nobody understands. Finance says inventory is $2M. Ops says $2.4M. Nobody knows who's right.
After
All data flows into one warehouse through automated pipelines. 200+ tested, documented models. Finance and Ops see the same number — because it comes from the same source.
Approach
A structured process that delivers production systems in weeks.
We map your current state — systems, data sources, pain points, organizational constraints. No generic assessments. We identify what's broken, what's working, and what matters most.
Deliverable
Clear picture of current state and prioritized roadmap for what to build.
We build production-ready systems fast. Dashboards, data platforms, AI models — tested, documented, and designed to scale. First value delivered in weeks.
Deliverable
Working systems in production with documented architecture and runbooks.
We transfer knowledge systematically. Documentation, training sessions, pair programming. When we step back, your team owns what we built and can extend it.
Deliverable
Your team trained to maintain, operate, and extend what we built — no dependency on us.
30-minute discovery call. No pitch deck. We'll discuss what's broken, what you've tried, and whether we're the right fit. If we're not, we'll tell you.