Efficient Deep Learning

in Automotive and IoT

Our Mission

We help customers build extraordinary
Deep Learning based products.

Accelerated
Time-to-Market

improved Product margins

Better Product Specifications

Value Added Partnership

product

Technology

Our award winning Deep Learning Optimization Engine optimizes your Deep Learning model for deployment (inference) to meet your requirements of:

  • Execution Time (Latency)
  • Throughput
  • Runtime Memory Usage
  • Power Consumption

EmbeDL enables you to deploy Deep Learning on less expensive hardware, using less energy and shorten the product development cycle.

EmbeDL interfaces with the commonly used Deep Learning development frameworks, e.g. Tensorflow and Pytorch. EmbeDL also have world leading support for hardware targets including CPUs, GPUs, FPGAs and ASICs from vendors like Nvidia, ARM, Intel and Xilinx.

We are happy to answer any questions and/or demonstrate EmbeDL on your Deep Learning model(s)!  

Want to learn more?

benefits

FASTER
EXECUTION

By using state-of-the-art methods for optimizing Deep Neural Networks, we can achieve a significant decrease in execution time and help you reach your real time requirements. 

SMALLER
FOOTPRINT IN DEVICE

The EmbeDL Optimization Engine automatically reduces the number of weights , and thus size of the model, to make it suitable to be deployed to resource constraint environments such as embedded systems

SHORTER
TIME-TO-MARKET

The tools are fully automatic, which reduces the need for time consuming experimentation and thus shorter time-to-market. It also frees up your data scientists to focus on their core problems.

LESS
ENERGY USAGE

Energy is a scarce resource in embedded systems and our optimizer can achieve an order of magnitude reduction in energy consumption for the Deep Learning model execution.

IMPROVED
PRODUCT MARGINS

By optimizing the Deep Learning model, cheaper hardware can be sourced that still meets your system requirements leading to improved product margins.

DECREASED
PROJECT RISK

Optimizing and deploying our customers’ Deep Learning models to embedded systems is what we do. By outsourcing this to us, your team can then focus on your core problems. 

ecosystem

Partners and customers

Zenseact
(Volvo Cars)

Veoneer

Chalmers University

Bielefeld University

Technion – Israel Institute  of Technology

Siemens

Christmann Informationstechnik

Barcelona Supercomputing Center

Osnabrück University

Research Institutes of Sweden

Antmicro

Maxeler Technologies

Gothenburg University

Neuchatel University

Technisch Universität Dresden

Networks

We are humbled to have been accepted into the following networks bringing together industry, academia and startups.

AWARDS

The EmbeDL Optimization Engine has received several awards for its technology and implementation.

press

We are always flattered when our technology finds itself into media. To reach out with experience from our experimentation, we regularly post findings in our blog. Sign up for our newsletter below to not miss out!

Latest News

Science meetup with Butterfly Ventures and Horisont

Science meetup with Butterfly Ventures and Horisont

Join us for this session tomorrow with focus on the innovations of today's industries. You will meet Tanya Marvin-Horowtiz, Partner at Butterfly Ventures, Sandor Albrecht, Senior Project Manager at RISE and EmbeDL CEO and co-founder Hans Salomonsson.  More info and...

Latest Blog

Amazon releases AZ1 Neural Edge Processor

Amazon releases AZ1 Neural Edge Processor

On September 24th, Amazon held its annual hardware event, introducing their new generation of  smart home hubs, speakers and other gadgets. Perhaps one of the most striking, yet precedented, announcements was Amazon’s first Neural Edge Processor*, AZ1.  * A Neural...

Stay up to date with our newsletter

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 780681.