Unlocking Efficient AI with Smaller, Smarter Neural Networks
Reduce model size while maintaining accuracy. Our neural network pruning techniques improve AI efficiency, lower computational costs, and speed up inference—making machine learning models more lightweight and effective.
Contact UsOur Services
Smarter, not just bigger – We can reduce model size by 50% or more while maintaining performance.
LLM Optimization
We specialize in optimizing large language models by significantly reducing their size — often by 50-90% — with minimal perplexity degradation. This makes powerful AI models more efficient, affordable, and easier to deploy across a wide range of platforms. This translates to 50-80% inference cost reduction.
Mobile deployment
We enable AI models to run efficiently on mobile and edge devices by reducing their memory and storage footprint. Our solutions ensure that even resource-constrained environments can benefit from advanced neural networks.
Other
Not seeing what you need? If your use case doesn’t fit neatly into these categories, reach out anyway. We’re always open to exploring new challenges and tailoring solutions to fit unique AI needs.
Our Results
LLM Optimization
Pruned Llama2-70B from 140GB to 26GB (with small perplexity degradation from 3.12 to 3.76).
Mobile Deployment
Pruned a 120MB base model to 6.2MB.
Meet the Team
Vladimír Macko
Founder
Vladimír Boža
Chief Scientific Officer
Let’s Talk!
Optimizing neural networks isn’t just a technical improvement—it’s a business imperative.
Contact UsAbout our company
At GrizzlyTech, we specialize in optimizing machine learning models through advanced neural network pruning techniques. Our mission is to help businesses create faster, more efficient AI solutions by reducing model size without sacrificing accuracy. With our cutting-edge methods, we improve computational efficiency, lower operational costs, and accelerate inference times, making AI models more lightweight and powerful. Led by a team of top machine learning experts, we’re dedicated to pushing the boundaries of AI optimization for a smarter, more sustainable future.