proteanTecs Gains Momentum as the Trusted Choice for Lifecycle Monitoring of AI Hardware

Haifa, Israel – June 10, 2025 – proteanTecs, a global leader in deep data monitoring for advanced electronics, is gaining significant traction as the partner of choice for AI chipmakers, delivering a dedicated suite of embedded solutions purpose-built for AI chips across cloud and edge environments. Responding to the explosive growth in AI workloads, the company offers applications engineered to meet the rigorous demands of training and inference at scale - tailored specifically for the performance, power, and reliability demands of AI systems.  To learn more, download the white paper here.

Tackling GenAI’s Infrastructure Crisis

The rise of generative AI has dramatically reshaped semiconductor requirements. Training large-scale foundation models can now cost over $1 billion, consume upwards of 50 GWh of energy, and require tens of thousands of GPUs operating continuously for weeks or months. Inference workloads are similarly intense, with massive query volumes driving infrastructure costs into the hundreds of thousands of dollars per day. These growing demands underscore a critical industry-wide challenge: existing compute infrastructure is being pushed to its limits, and scaling efficiently has become a strategic imperative.

AI chipmakers now face triple pressure:
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• Power reduction to stay within power budgets and operational constraints
• Latency and throughput optimization to ensure user responsiveness
• Resilience and reliability to avoid functional failures or silent errors that corrupt complex compute clusters

“Traditional static guard bands, conservative frequency settings, and limited in-field visibility leave performance untapped and increase the risk of avoidable failures,” said Evelyn Landman, CTO of proteanTecs. “Our deep data solutions directly address these unpredictable, systemic inefficiencies with a workload-aware, in-situ approach to monitoring and optimization.”

Purpose-Built Capabilities for AI Compute

proteanTecs’ suite of solutions for AI includes embedded runtime monitoring and insights that allow chipmakers and hyperscalers to:

• Reduce dynamic and static power consumption with workload-aware voltage scaling, increasing performance-per-watt (PPW)
• Improve throughput and reduce latency by dynamically reclaiming frequency headroom during high-load inference
• Enhance system reliability and prevent silent data corruption (SDC) by predictively monitoring chip health in-situ
• Extend chip and system lifetime by reducing voltage stress and enabling predictive maintenance
• Support co-design strategies by tracking detailed usage and degradation profiles across diverse AI workloads

This monitoring runs per chip, in real time, under real conditions - capturing performance-limiting paths, available guard bands, software stress, and aging indicators that static design models can’t reach.  

In addition to optimizing individual chips during runtime operation, proteanTecs enables system-wide offline orchestration. Operators can proactively shift workloads across servers based on chip health and predicted performance degradation, balancing stress to offload devices nearing failure. This allows for smarter load balancing, early intervention, and improved fleet reliability, before performance issues or faults occur.

“The figures highlight a sobering reality: without significant efficiency improvements, AI scalability is unsustainable,” added Uzi Baruch, Chief Strategy Officer. “proteanTecs addresses this head-on, delivering our most advanced capabilities into a unified, targeted suite – so that every watt, FLOP, and dollar is maximized.”

Availability and Next Steps

proteanTecs’ suite of AI-tuned applications is production-ready and already delivering value at scale in real-world deployments. The company is working with major cloud vendors, as well as cutting-edge AI innovators, providing real-time monitoring solutions that are proven across hyperscale infrastructures. The technology supports advanced process nodes down to 2nm, and is also designed for heterogeneous, chiplet-based architectures that power the next generation of AI systems.

proteanTecs invites interested customers and partners to explore how design-aware on-chip monitoring can unlock performance, power savings, and resilient deployment for their AI chips.