Industries / Manufacturing

Manufacturing

Unplanned downtime is still the costliest line item on the floor, and sensor data rarely talks to ERP data. We build predictive maintenance and reporting for manufacturers who need to see problems before they happen.

Key Challenge

Unplanned downtime and disconnected sensor/ERP data.

Equal To One Package

Predictive maintenance models, Spark/Airflow data pipelines, and BI dashboards.

Value Delivered

Less downtime, lower maintenance cost, and better planning.

How We'd Work Together

From first call to production, in four stages.

01

Discovery Call

A free 30-minute conversation about your current process and where the gaps actually are.

02

Readiness Assessment

A paid, structured review of your technology, data and process maturity — output is a scoped, prioritized roadmap.

03

Delivery Sprints

Kickoff, technical discovery, then delivery sprints with regular check-ins — fixed-scope, T&M, or retainer.

04

Go-Live & Support

Transition to managed services or a staff-augmentation retainer if you need ongoing capacity, not just a handoff.

Illustrative Engagement

Anonymized · Illustrative

Industrial Equipment Manufacturer

Divisions B & C

An industrial equipment manufacturer was responding to equipment failures after they happened, with sensor data sitting in a separate system from maintenance records.

Approach: A predictive maintenance model trained on combined sensor and maintenance-log data, flagging likely failures before they occur.

Outcome pattern: Reduced unplanned downtime and more proactive maintenance scheduling.

A Note on Scoping

Built around your floor, not a generic IoT template.

Every predictive maintenance engagement starts with a Digital Transformation assessment of your actual sensor and ERP data — not an off-the-shelf model retrofitted to your equipment. That's the same scoping discipline behind 15 years of infrastructure delivery.

Let's map this against your actual sensor and maintenance data.