Three sectors, one operating language.
We focus on Manufacturing, Automotive Suppliers and Logistics — the industries where data, processes and physical operations have to line up day after day.
Specialized, not generalist.
Each sector has its own vocabulary, systems and reporting cadence. We've chosen three where we can speak the language fluently.
Protect OEE. Reduce unplanned downtime.
MES, SCADA, sensor and quality data turned into models that hold the line on yield, scrap and uptime — integrated into the systems your operators already use.
OEM-grade analytics for ppm targets.
Quality, traceability and process analytics built to OEM audit standards — supporting warranty exposure, ppm escape rates and supplier reporting cycles.
Forecast demand. Plan every route.
Hierarchical forecasting, network optimization and end-to-end visibility for warehouse, distribution and last-mile teams — so plans match what actually happens.
Five use cases, five scales of impact.
From a focused two-week diagnostic to a multi-month prescriptive rollout — engagements spanning the full spectrum of analytics maturity, with the kind of impact each one is designed to deliver.
- 01Small · 2-week sprintDiagnostic analytics
Scrap-rate root cause analysis on a single line
Pull six to twelve months of production, quality and parameter data for one line, identify the top three drivers of scrap, and quantify the size of the prize before committing to a build.
MES exportsQuality logsSetpoint historyPotential savingsTarget impact: 8–15% scrap reduction on the analyzed line.
- 02Small · 3–4 weeksDescriptive analytics
Plant KPI cockpit for daily shift reviews
Consolidate OEE, downtime reasons, scrap and throughput across lines into a single governed dashboard, replacing manual Excel reports that take hours each morning.
MES / HistorianERP order dataManual downtime logsPotential savingsTarget impact: 4–6 hours / shift / plant of reporting effort removed.
- 03Medium · 8–12 weeksPredictive analytics
Predictive maintenance on critical assets
Failure-signature models on torque, vibration and thermal streams for a fleet of high-criticality machines, with alerts integrated into the existing CMMS workflow.
Sensor telemetryCMMS work ordersMaintenance historyPotential savingsTarget impact: 20–40% reduction in unplanned downtime on covered assets.
- 04Medium · 10–14 weeksPredictive analytics
SKU-level demand forecasting for S&OP
Hierarchical forecasting reconciled across SKU, region and channel, feeding the existing S&OP cadence with weekly horizons and confidence bands instead of point estimates.
Sales historyPromotionsExternal demand signalsPotential savingsTarget impact: 10–25% lower forecast error and 5–10% inventory reduction.
- 05Large · 4–6 monthsPrescriptive analytics
Network-wide route & load optimization
A prescriptive engine that plans routes and loads across the distribution network, balancing SLA priorities, driver constraints and live traffic — operated by planning teams, not data scientists.
TMS dataOrder bookFleet & driver constraintsPotential savingsTarget impact: 8–15% fuel cost per route and material SLA uplift.
One sector. One metric. One conversation.
Tell us your sector and the operational number you'd most like to move. We'll come back within two business days with a plan on how to tackle your specific problem.