The future
of compute.
Revolutionising compute with faster, scalable AI, ultra-efficient energy use.
Built for a modular world
Exponential Tensor Computing (XTC) is a modular AI framework focussed on enhancing data representation and processing efficiency, enabling a wide scope of applications, such as generation as well as processing data & content.
a leap for tensor computing
XTC redefines tensor computing with groundbreaking optimizations that deliver unmatched speed, scalability, and efficiency. By streamlining operations and minimizing energy use, XTC pushes the boundaries of what's possible in AI development, from real-time processing to edge deployments.
Dynamic Tensor Restructuring
Pathway Optimization Engine
Multi-Dimensional Data Flow
High-Throughput Data Handling
Modular AI Framework Integration
2nd wave (Q2-3)
Paving The road ahead
1st wave (Q1)
Research and Development
2nd wave (Q2-3)
Ecosystem Expansion
3rd wave (Q4+)
Global Standardization
Frequently Asked Questions
XTC introduces advanced tensor optimizations, exponential scalability, and energy-efficient algorithms, setting it apart from traditional AI frameworks by dramatically improving performance and sustainability.
Through its proprietary tensor optimization and pathway structuring, XTC scales computational gains exponentially as system complexity grows, unlike linear improvements in traditional systems.
Yes, the roadmap includes continuous enhancements, ecosystem expansion, and broader adoption, with some steps currently redacted to preserve strategic confidentiality.
The XTC token powers the ecosystem by granting access to advanced features, enabling decentralized governance, and rewarding contributions to the framework’s growth.
XTC significantly reduces energy consumption through advanced tensor computing techniques, making AI development more sustainable and environmentally friendly.
Yes, the alpha version of XTC has already been rolled out and is accessible for developers and early adopters.
Yes, XTC is designed for compatibility with resource-constrained edge devices, enabling efficient AI processing even in decentralized or low-power environments.