Machine Learning / Deep Learning Optimization
Machine Learning / Deep Learning Optimization

What if you could push your AI models to be 10 times faster?

Nikolas Markou

Nikolas Markou

Machine Learning Engineer | Managing Partner @ Electi Consulting

Modern Machine Learning (ML) and especially Deep Learning (DL) have become deceptively easy. It is almost trivial to have something up and running with presentable results as the the tools hide most of the complexity and hard decisions.

Machine Learning is Deceptively easy

Top-performing ML systems can be expensive to store, slow to evaluate and hard to integrate into larger systems.

Most companies employ off-the-shelf open source R&D models that are highly inefficient and very power hungry when deployed at scale.

Many CXO’s and seniors managers find themselves trapped into sub-par solutions that cannot be used effectively because they lack the technical know-how to productionalize them.

At ELECTI we have that knowledge and we can help you go that extra mile from POC / MVP / Demo to full scale product.

We replace such cumbersome models with simpler ones that perform equally well, making them more efficient thus saving you time and resources.

We work with GPU high performance environments such as Nvidias’s TensorRT than can cut the inference time and resources needed by a huge margin thus saving infrastructure costs.

  • You want to scale but you don’t know how ?
  • Your python scripts are dragging you down ?
  • Infrastructure cost too high ?
  • Clients unhappy with slow responsiveness ?