Traditional Al accelerators (specialized hardware devices engineered to enhance the speed and efficiency of Al applications like Neural Networks and Computer Vision) rely on electronic circuits that are constrained by heat, bandwidth, and energy efficiency.

The problem

The solution

Qyras's photonic processors utilize light, allowing them to operate at optical wavelengths. This results in dramatically higher speeds and far more energy-efficient computation.

Chips are becoming physically larger and more power hungry due to fundamental, physical limitations of transistors. Compute performance roadmaps are now defined by silicon-area-per-package and the number of processors tightly linked in a high bandwidth scale-up domain. The quest for AGI is driving this trend at warp speed.

SILICON AREA PER CHIP (MM)

10Х

CHIP SCALE OVER TIME

2000

2010

2020

2030

We enable the silicon-area-per-package scaling roadmap, shatter the concept
of "beachfront" and bring networking radices to new highs with our breakthrough interconnect and packaging technology platform - Optalink. We sell the photonic chips that will make building AGI possible (and the lasers that power them). From single reticle to wafer-scale, the world's fastest (and first) 3D-stacked photonic chips.

A bright foundation for big chips

SynapticAl Suite

SynapticAl Suite is a comprehensive software suite designed for seamless Al model development, deployment, and optimization specifically tailored for Qyras's photonic hardware.

At the core of Qyras's photonic processors are MZIs. These devices manipulate light by splitting and recombining it through phase shifts, enabling them to perform fast matrix multiplications-critical for deep learning and Al computations.

The Mach-Zehnder interferometer (MZI)

Technology

Research facilities that require cutting-edge computational power for Al model training, particularly in fields like natural language processing (NLP), computer vision, and robotics.

Al Research Labs and Universities

Hospitals and clinics focusing on Al-driven diagnostics, such as pathology analysis and medical imaging. Qyras's technology enables quicker Al-based diagnostics, improving patient outcomes.

Healthcare and Medical Imaging

Companies developing self-driving technology that demand low-latency, real-time processing for autonomous navigation. Qyras's photonic processors can handle vast amounts of sensor data with minimal delay.

Autonomous Vehicle Manufacturers

Companies that manage massive Al workloads requiring efficient, high-speed processing. Qyras's technology can drastically reduce energy consumption and data latency, optimizing the cost and performance of Al operations.

Data Centers and Cloud Providers

Firms conducting high-frequency trading, fraud detection, and risk management benefit from Qyras's rapid data analysis capabilities. Real-time data processing with low energy consumption is critical for financial operations.

Financial Institutions

Batyr Bekiyev

Nikolay Razakov

Rufat Aidaraliev

Chief Technical Director (CTO)

Chief Marketing Officer (CMO)

Chief Scientific Officer (CSO)

Chief Executive Officer (CEO)

Dmitry Polivin

People