Technology

ATHLAZ is developing a transformative approach to energy management through its proprietary Zeus ACM platform.

At the heart of ATHLAZ’s innovation is a modular, AIpowered system capable of dynamically controlling electrical parameters including current type, voltage, frequency, and waveform in real time.

This enables precision power delivery tailored to the specific needs of each device or load, unlocking significant gains in energy efficiency, reliability, and cost-effectiveness. Where precision medicine is revolutionising healthcare, Athlaz’s innovation will provide revolutionary precision powerdelivery.

The company’s core technology, Adaptive Current Modulation (ACM), represents a fundamental shift in how electricity is delivered and managed. By integrating predictive algorithms and historical usage data, ATHLAZ can anticipate energy demand and optimise power delivery before inefficiencies arise.

A key differentiator is ATHLAZ’s Digital Signature System, which identifies the unique harmonic fingerprint of each connected device or energy source. This allows for decentralised energy trading, granular control, and intelligent routing of power across smart grids, data centres, EV charging networks, and even satellite systems.

ATHLAZ’s architecture is designed to scale across multiple layers, from chip-level implementations to rack-level orchestration and full grid-level deployments. This hierarchical design supports both edge and cloud-based configurations, making the technology highly adaptable to diverse infrastructure environments.

The company is currently preparing for a Seed or Series A funding round within the next 6 to 12 months and is exploring strategic partnerships with industry leaders such as Nvidia, Siemens, and Schneider Electric. ATHLAZ has filed a South African provisional patent and a UK patent application, with a PCT application planned for February 2026.

ATHLAZ’s vision is to become the global standard for intelligent energy management, setting the benchmark for how electricity is distributed, consumed, and monetised in the age of AI and decentralised infrastructure.

Adaptive Current Modulation

This is the first system to dynamically switch between AC, DC, and Pulsed DC based on real-time load analysis, using AI to determine the optimal current type for each microsecond with seamless transitions and no power interruption. This is non-obvious because electrical systems have been historically fixed to either AC or DC for over 140 years.

Key Differentiators

Real-time intelligent control

ATHLAZ’s approach is fundamentally different to that of Utilidata. Rather than focusing solely on measurement and visibility, ATHLAZ is developing a real-time control system that actively modulates electrical parameters to optimise energy delivery.

Active modulation and dynamic adjustment of power

ATHLAZ’s system is designed not just to observe but to act, using predictive algorithms and digital signatures to dynamically adjust power flows across a wide range of applications.

AI-Driven Waveform Synthesis

The system generates custom waveforms using neural networks, rather than predetermined patterns, with each waveform uniquely optimized for specific load conditions and capable of learning and improving over time. No existing system creates entirely new waveforms using AI, combining LSTM, DQN, and PPO for this purpose.

Multi-Objective Optimisation Engine:

This engine simultaneously optimizes 7+ parameters in real-time, including energy efficiency, power factor, harmonic distortion, component temperature, grid stability, equipment longevity, and cost optimization. Existing systems typically optimize only single parameters, making ATHLAZ's holistic approach novel.

Electrical Fingerprinting

Every device creates unique harmonic signatures that AI identifies, enabling authentication and security through power analysis. This provides completely new security implications and powerfull aplications troughout the entire supply chain.

Predictive Load Management

ATHLAZ's system predicts power requirements 100-1000ms before they occur, pre-adjusting power delivery to prevent quality issues using ensemble ML models specifically designed for power systems. Traditional systems are reactive, responding after load changes, whereas ACM offers anticipatory control.

ATHLAZ COMBINED

These inventions combine to create a “frequency-native control algorithm” that operates directly on harmonic components, reducing computational overhead and supporting real-time modulation with high precision and low latency. The ACM ecosystem creates new fields and possibilities, redefining what we thought we knew about energy, efficiency, and human ingenuity.

Distinction from Prior Art

AthlaZ's ACM technology significantly differentiates from existing solutions, which often address single parameters or modify existing power, while ACM "reinvents the current itself":

vs. Intel/AMD Dynamic Voltage Frequency Scaling (DVFS): DVFS only adjusts voltage and frequency for processors, whereas ACM changes the current type entirely and works with any electrical load, utilizing multi-objective optimization.

vs. ABB/Siemens Variable Frequency Drives (VFDs): VFDs are fixed to AC output with frequency control for motors, while ACM offers AC, DC, or Pulsed DC output with universal application and continuous learning.

vs. Solar Inverters (SMA, Enphase): Inverters convert DC to AC with fixed algorithms. ACM is bidirectional, provides any-to-any conversion, and is AI-driven and load-aware.

vs. Self-Adaptive Current Control (EP3625885B1): This closest prior art lacks dynamic current type selection, AI-driven waveform synthesis, predictive capabilities, multi-objective optimization, and learning from deployments.

The innovation stems from addressing "the artificial limitation of fixed current types," a problem no one knew existed, by envisioning AI controlling analog power.