Imagine the following scenario on an assembly line. A critical equipment component is about to fail. A traditional sensor misses it. But a multimodal AI sees a microscopic crack in the camera feed, hears the faint, anomalous whine in the audio stream, and feels the subtle vibration in the sensor data. It doesn’t just flag an alert—it diagnoses the problem, pinpoints the machine, and halts the line. A catastrophic shutdown and a million-dollar recall are averted not by hours,

Artificial intelligence (AI) has shifted from a bold experiment to a strategic necessity. Recent studies show that 88% of C-level decision-makers want to accelerate AI adoption in 2025. Yet, just a fraction of AI initiatives delivers the expected results.

Artificial intelligence is capable of many things—from taking your customers’ calls to figuring out why your equipment is consuming way more energy than it used to.