HORSHAM, PA — Augmentir announced that its patented True Productivity™ algorithm has surpassed 5 million AI-optimized time and motion studies, marking a milestone in industrial performance analytics. The technology, first introduced in 2019, has become a leading platform for understanding frontline workforce efficiency and enabling automated improvement through artificial intelligence.
Now deployed across more than 30,000 processes in 70 countries, True Productivity performs over 150,000 digital studies each month. The system analyzes how work is performed on the factory floor, helping manufacturers pinpoint inefficiencies and standardize best practices through data-backed insights.
Unlike conventional time and motion studies that often produce inconsistent or unreliable data, Augmentir’s approach filters out noise — as much as 30 percent of what’s typically collected — to reveal a precise picture of how processes actually function. The result, according to the company, is an objective understanding of performance, highlighting where improvements in productivity, training, and consistency can yield the greatest returns.
“True Productivity combines the precision of AI-optimized analytics with the power of agentic automation,” said Russ Fadel, CEO of Augmentir. “It’s not just about measuring productivity — it’s about using AI agents to continuously improve it, across every process, every worker, and every site.”
The system’s latest evolution integrates with Augmentir’s AI Agent Studio, allowing manufacturers to deploy custom AI agents that act directly on data insights. These agents can recommend targeted training when skill gaps are identified, flag deviations from standard work, or suggest efficiency improvements — effectively creating a self-correcting production environment.
By merging predictive analytics with autonomous action, Augmentir’s True Productivity represents a shift from manual, reactive optimization to intelligent, continuous improvement — a transformation that could redefine operational efficiency across global manufacturing.
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