Put Your Data to Work

We deliver customized applied machine learning and artificial intelligence solutions to automate, understand and grow your business.

    Your data is collected for the sole purpose of contacting you. We will not use your data for any other purpose. Please see our privacy policy for more details.

      Your data is collected for the sole purpose of contacting you. We will not use your data for any other purpose. Please see our privacy policy for more details.

      Our Mission

      Being on the forefront of applying machine learning and artificial intelligence to solve real-world business problems

      Our team consists of a handpicked mix of data scientists, machine learning researchers, and software engineers in order to deliver the best solution using state-of-the-art technology

      Case Studies

      Teaching Computers to See

      Computer Vision: Tags, bounding boxes, masks
      Computer Vision - Bounding boxes
      Computer vision example

      Computer vision gives computers the ability to locate and identify objects on images/video and allows for the automation of a number of manual processes.  Some examples of ready to use models include identifying changes on satellite images, recognizing people and objects on security camera images and/or video, or the automatic indexing of images and videos.

      The technologies we use are based on deep learning neural networks and can be executed with high performance on GPUs and other acceleration hardware.

      Product Recognition

      Brands: vans, iPhone, Raybans, shoes, watch, phone, shirt Brands: vans, iPhone, Raybans, shoes, watch, phone, shirt
      Identify well-known brands, products, and people on images (e.g. social media) and in videos (e.g. live television)

      Satellite Imagery

      parking lot used for satellite imagery parking lot used for satellite imagery
      Track changes on satellite and real time images in addition to collecting statistics on the amount of objects (e.g. trucks, parking spaces, etc) in an area.

      Manufacturing Defects

      manufacturing-defects pill, yellow, blue manufacturing-defects pill, yellow, blue
      Improve the automated detection of production errors and damage to delivered and produced parts as well as assessing the quality of products produced.

      Predicting the Future

      The prediction of future developments, based on historical data, can be applied to a large variety of business areas. We help you to identify and understand past data to create complex relationships which are then used for the modeling of high-performance prediction models.

      Slide Slide Slide PAST DATA FUTURE PREDICTION

      Google was founded in September 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University in California. Together they own about 14 percent of its shares and control 56 percent of the stockholder voting power through supervoting stock. The domain name for Google was registered on September 15, 1997 and they incorporated Google as a California privately held company on September 4, 1998, in California. An initial public offering took place on August 19, 2004. Sundar Pichai was appointed CEO of Google, replacing Larry Page who became the CEO of Alphabet. Google indexes billions of web pages to allow users to search for the information they desire through the use of keywords.

      The Eiffel Tower is a wrought-iron lattice tower on the Champ de Mars in Paris, France. It is named after the engineer Gustave Eiffel, whose company designed and built the tower. Constructed from 1887 to 1889 as the entrance to the 1889 World's Fair, it was initially criticised by some of France's leading artists and intellectuals for its design, but it has become a global cultural icon of France and one of the most recognisable structures on Earth. The Eiffel Tower is the most-visited paid monument in the world; 6.91 million people ascended it in 2015. During its construction, the Eiffel Tower surpassed the Washington Monument to become the tallest man-made structure.

      Google was founded in September 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University in California. Together they own about 14 percent of its shares and control 56 percent of the stockholder voting power through supervoting stock. The domain name for Google was registered on September 15, 1997 and they incorporated Google as a California privately held company on September 4, 1998, in California. An initial public offering took place on August 19, 2004. Sundar Pichai was appointed CEO of Google, replacing Larry Page who became the CEO of Alphabet. Google indexes billions of web pages to allow users to search for the information they desire through the use of keywords.

      Geoffrey Everest Hinton is an English Canadian cognitive psychologist and computer scientist, most noted for his work on artificial neural networks. In 2013 he divided his time working for Google and the University of Toronto. In 2017, he cofounded and became the Chief Scientific Advisor of the Vector Institute in Toronto. He with David E. Rumelhart and Ronald J. Williams, Hinton was co-author of a highly cited paper published in 1986 that popularized the backpropagation algorithm for training multi-layer neural networks. The dramatic image-recognition milestone of the AlexNet designed by his student Alex Krizhevsky for the ImageNet challenge 2012 helped to revolutionize the field of computer vision.

      Understanding Language

      Unstructured data in the form of business documents, product reviews, and social media posts contain invaluable information that can be used to better understand and optimize your business. In order to access and use this data, we employ natural language processing techniques based on deep neural networks that generate new insights and enable advanced use cases.

      Solutions

      Image Similarity Search

      Our image similarity search database can index billions of images and identify similar images within milliseconds. This search engine can be easily integrated into processes and websites via our REST API. Use our image similarity search databases for similar images, objects, places, known people, or people who appear together within an image. 

      Slide Target Image 94% Similarity 90% Similarity 88% Similarity 79% Similarity 85% Similarity 76% Similarity Slide Slide Target Image 93% Similarity 89% Similarity 82% Similarity 68% Similarity 71% Similarity 79% Similarity

      Rocketloop AI Hub

      Integrating machine learning models into your existing business infrastructure can be a major challenge. With the Rocketloop AI Hub, we offer an integrated run-time environment for your customized machine learning solutions, that takes care of running, deploying and exposing your models to your existing IT infrastructure. In addition, our visual editor allows non-technical domain experts to design, control and improve your personalized AI solutions.
       
      Pipeline View Browser as described by Rocketloop AI Hub
      Brian, colored, integration into applications, documentation, release processes and versioning
      For integration into existing applications, we expose each model via a REST API, thus avoiding isolated applications. Furthermore, we provide tools for documentation, release processes, and versioning of your future models.
      Browser, colored, scalable runtime environment ensuring compliance
      We offer you a scalable runtime environment for the operation of machine learning solutions from within your infrastructure. In contrast to classic Big Data solutions, the Rocketloop AI Hub allows the use-case related connection of data sources from other systems and thus avoids unnecessary investments in infrastructure.
      File combination, colored, versioned, documented and released
      Machine learning solutions must be versioned, documented, and released similar to software products. Our AI Hub combines all these tasks on a single platform. Intelligent sets of rules ensure compliance with your internal policies at all times.

      Workshops

      Lean Data Science

      Evaluate the added value of predictive analytics and machine learning use cases without having to make large investments in infrastructure in advance. We develop lean proofs-of-concept for your individualized use cases, enabling you to quickly and cost-effectively evaluate the feasibility as well as actually added value. Successful prototypes can be quickly and cost-efficiently transferred to productive operation by using the Rocketloop AI Hub.

      Slide
      Our workshop “Lean Data Science for Decision Makers” offers you the ideal introduction to establish the necessary expertise within your organization by identifying and prioritizing possible use cases according to proven methodologies.
      Get in Contact

      Testimonials

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          Your data is collected for the sole purpose of contacting you. We will not use your data for any other purpose. Please see our privacy policy for more details.