The Challenge

A major industrial manufacturing group needed to reduce energy waste across multiple factories, but current monitoring systems were cloud-based and reactive, detecting leaks after losses occurred. The leadership needed to bring real-time AI intelligence directly to their production lines—to detect anomalies, optimize performance, and ensure predictive maintenance, without relying on cloud-based AI systems introducing unacceptable latency and bandwidth constraints.

While edge AI held promise, building ASIC-ready models was a complex, slow, and costly journey often taking months and limiting innovation speed.

The Client asked:

• Can we detect micro-leaks and inefficiencies in real time, directly on-site?
• Can we compress AI models to run on chips at the sensor level, without losing performance?
• How fast can we prototype, optimize, and move to ASIC-ready deployment?

The Good Data Factory Solution

We built a custom ultra-efficient Edge AI model that is ASIC-ready, enabling real-time detection of energy inefficiencies at the source, to be embedded directly at the sensor level. The model is capable of learning “normal” machine energy signatures and detecting deviations instantly.

Our proprietary Agentic Edge AI framework, fully automating AI models compression pipeline, allowed for rapid prototyping, fast iteration cycles with the client’s hardware team, and significant cost savings in ASIC development.

The Results

• 75% model compression – with no performance compromise compared to the original cloud-based AI model.
• Enabling lightweight, high-performing, and low-power consumption ASIC-ready model optimized for critical manufacturing environment deployment.

For our client, every second of undetected energy leakage is wasted profit and wasted potential. The Good Data Factory’s ASIC-ready Edge AI brings intelligence at the exact point of action, helping industrial leaders to act in real time and cut costs.