Industrial Software
Manufacturing and logistics software fails quietly — a warehouse count that's off by a few percent, a maintenance schedule based on averages instead of a machine's actual wear. We build the ERP, IoT, and analytics layer to catch that before it becomes a shutdown.
What we build
The layer that catches the discrepancy.
ERP systems
Custom ERP modules for the processes off-the-shelf systems don't model well.
Manufacturing automation
Production-line automation and monitoring integrated with the machines you already run.
Inventory & warehouse management
Stock tracking and warehouse operations software that reconciles with what's actually on the shelf.
Industrial IoT
Sensor data pipelines from the factory floor to a dashboard someone actually checks.
Fleet & logistics
Vehicle tracking, route planning, and logistics coordination for distributed fleets.
Predictive maintenance
Failure prediction models trained on your equipment's actual sensor history, not a generic maintenance schedule.
How we engage
The same process, every time.
- 01
Scope
We read what exists — code, requirements, or both — and quote a number in writing before any contract is signed.
- 02
Build
A fixed team scopes and ships it. Weekly demos, no unannounced handoffs mid-project.
- 03
Handoff
Documentation, a defined support window, and a codebase your own team can actually maintain.
Stack
What we build it with.
- Backend
- Python, Java, Go
- IoT
- MQTT, OPC-UA, Modbus gateways
- Data
- PostgreSQL, TimescaleDB, Grafana
- Infrastructure
- Kubernetes, AWS IoT, Azure IoT
If the current system's numbers don't match what's on the floor, that's usually where to start.