Unlock the Potential
of Quantum Technologies for Practical Business Applications

80%

Model Size Reduction on Average

10x

Inference Acceleration on Average

70%

Cost Reduction

Quantum Computing

Faster

High Privacy

Forecasting

Energy Efficient

Simulation

Artificial Intelligence

Accurate

Machine Learning

Calculations

Simple Quanta

The enormous size of current LLMs restricts their use in environments with limited memory & processing power. By applying tensorization to these models, identifying and compressing the critical & non-critical components, Simple Quanta can significantly reduce their size without substantial performance loss.

Large Language Model Compressor

Lucid Quanta

Lucid Quanta employs an innovative methodology by utilizing hidden data structures to achieve faster convergence compared to traditional algorithms. This groundbreaking approach holds significant promise, particularly for optimization challenges with numerous variables that require rapid solutions.

Optimization of problem solving

Laquanta products for delivering our AI &
Optimization proprietary algorithms

Bridging AI Challenges

Transforming AI Sustainability

Laquanta's AI solutions are precisely aligned with the current challenges in AI. Without intervention, AI's unchecked growth will lead to unsustainable energy consumption levels that could have devastating environmental impacts.

Quantum-Inspired tensor Networks

The computational demands of deep learning are rapidly escalating, with the latest training sessions for large language models (LLMs) costing upwards of millions dollars. Forecasts suggest that, without a transformative shift in technology, we will soon be unable to feasibly train AI models, even if ample data is available for training.

Enhancing ai efficiency

Quantum-Inspired Laquanta’s Tensor Networks revolutionize AI by enabling faster training, reduced data requirements, and significantly lower power consumption. Demonstrated accelerations exceed 10x, transforming high-power applications like machine vision and large language models. These advancements are crucial for deploying AI technologies at the edge, making tensorized AI indispensable for autonomous vehicles.

Quantization

graph compilers

TPU

GPU

Edge

Our Clients

Energy

Aerospace

Manufacturing

Cybersecurity

Health & Life Sciences

Defense

Finance

Engineering

Earn Additional Value to the Enterprise

achieve LLM independence

optimize performance & cost

future proof applications

customize freely

Free yourself from any single model, model provider, cloud, or hardware setup.

Run SQ & LQ inference at the lowest price & latency on our optimized serving layer.

Rapidly iterate with new models & infrastructure without rearchitecting anything.

Mix & match models, fine tunes, and LLM assets at the model serving layer.

Core Technologies

Quantum algorithms

Laquanta designs unique algorithms that harness contemporary quantum platforms to address complex optimization challenges and advance interpretable machine learning.

Economic value

Despite the promising future of quantum computing power, its immediate applications remain limited. Laquanta prioritizes strategically deploying quantum solutions that deliver concrete economic benefits, steering clear of purely exploratory projects.

Flexible Hardware

Laqaunta embraces a platform-independent strategy, acknowledging the diversity of quantum hardware technologies, including superconducting qubits, photonic systems, neutral atoms, & ion traps. Collaborations have been established with leading quantum hardware producer.

Expertise in quantum solution Flexible Hardware

There are several types of quantum-inspired computing, including Tensor Networks, Digital Annealing, Parallel Tempering, Population Annealing, and Quantum-Inspired Monte Carlo methods.