Zero-Hardware Footprint
No expensive secondary sensors required. We ingest existing PLC tags, drive currents, and gateway telemetry natively.
Your clients don't just buy durable steel—they demand guaranteed uptime. NIMBUS embeds time-series anomaly algorithms natively into your machine lines, unlocking high-margin software revenue attached to your Preventative Maintenance Plans.
Building in-house machine learning and cloud pipelines is costly and slow. NIMBUS provides the analytics engine so you can launch condition monitoring under your own brand in weeks.
No expensive secondary sensors required. We ingest existing PLC tags, drive currents, and gateway telemetry natively.
Detect operator over-speed, lubrication thermal spikes, or unaligned loads before physical damage triggers a warranty claim.
Attach high-margin (60%+) condition monitoring subscriptions to your standard Preventative Maintenance Plans (PMPs).
Our R145,000 Integration Pilot is structured in cash-flow positive milestones (R58k kickoff / R43.5k integration / R43.5k handover), ensuring your client sign-off funds the integration.
A joint technical workshop to review your machinery telemetry, PLC tags, and target failure modes.
A 6-to-8 week pilot integrating NIMBUS anomaly models onto 1 to 3 active machine lines.
Fixed per-machine monthly royalty once your white-label condition monitoring tier scales across client sites.
NIMBUS is founder-led by Sergio Matolla, combining quantitative analytics, high-throughput data engineering credentials, and industrial reliability principles.
Business & Data Engineering professional specializing in large-scale automated data pipelines, multivariate time-series anomaly detection, and cryptographic systems.