Groundup.ai has unveiled the Global Machine Benchmark (GMB) launching the first universal standard designed to make global machinery fleets measurable, comparable and transparent.
The GMB, integrated into the enhanced GINA AI v2 platform, aims to close a long‑standing gap in industrial operations, where assets such as ships and plant machinery have lacked a consistent, data‑driven benchmark equivalent to credit ratings in finance or safety certifications for buildings.
From isolated maintenance to continuous intelligence
The GMB goes beyond basic anomaly detection by ingesting multi‑modal data—vibration, temperature, usage patterns and more—and normalising machine behaviour across different operating environments.
GINA AI v2 then distils machine health into four key components, producing a single, balanced score that lets operators see how their assets stack up against global peers for the first time.
“In high‑stakes environments like naval defence, failure is not an option. Yet most industrial operators have no clear way to know how their machines are actually performing relative to the rest of the world,” said Leon Lim, CEO and founder of Groundup.ai.
“The GMB is the shared brain for the fleet. It’s not just a dashboard. It’s a standard that shows leaders exactly where they stand and what it takes to close the gap.” Leon Lim
Hard‑dollar impact on uptime and cost
Groundup.ai frames the GMB as a hard‑ROI tool, not just a visualisation. The company claims that moving a vessel’s health score up by just four percentage points can recover 352 operational hours and approximately US$220,000 in value per vessel per year by cutting unplanned downtime, avoiding costly repairs and extending asset life.
In live naval‑defence deployments, teams using GINA AI v2 achieved 22 consecutive months of zero unplanned downtime, shifting from reactive “firefighting” to predictable, performance‑driven operations. The GMB provides a continuous improvement loop—Benchmark, Diagnose, Decide, Act, and Improve—so that every machine is assessed, acted on and refined over time, with recommendations tailored to each asset’s risk profile and operational context.
A global data flywheel for fleets
Unlike traditional solutions that focus on single vessels, GINA AI v2 operates across entire fleets, with the GMB score improving as more assets connect. The more data that flow into the system, the sharper the benchmarks and the more precise the prescriptive guidance, creating a self‑reinforcing data flywheel. “This is a shift from isolated maintenance to a global standard of excellence,” said Alex Wong, COO and co‑founder.
“We are giving maritime leaders the power to own their ground truth; to prioritise what matters most and compete on a level of transparency this industry has never had before.” Alex Wong
For the IoT and asset‑management community, the GMB represents one of the first attempts to treat fleets as connected, scoreable entities, bringing the language of finance and benchmarking into the physical, machine‑driven world.
