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Ripcord + Engine ML: What’s new and next in deep learning

Ripcord has acquired deep learning and ML company Engine ML. Engine ML builds distributed deep-learning infrastructure designed to scale. The Ripcord integrated solution enables leading brands in finance, insurance, retail and energy to quickly and easily unlock the power of their data and turn it into actionable insight in hours instead of days.

The business value of semi-structured and unstructured data has been somewhat limited as extracting its intelligence remains a roadblock. Combining Ripcord’s AI and robotics-powered solution with Engine ML’s accelerated machine learning infrastructure eliminates these challenges in a way that has never been done before. Organizations will be able to drive quick and seamless next-generation digital transformation across an organization, speeding up return on investment and operational results from their business content.

What’s in it for our Customers?

When Ripcord invests and innovates on its platform we aim to help our customers deliver:

  • Improved customer experiences via smarter data
  • Accelerated time to actionable insight
  • Greater profitability
  • Productive employee experiences

Learn more

FAQs

  • When was the transaction completed?

    The transaction was completed in late November and the team are collaborating and settling in nicely as members of team Ripcord.

  • When will customers be able to take advantage of Engine MLs technology via Ripcord?

    Engine ML technology creates an immediate benefit within Ripcord. Our customers will reap the indirect benefits almost immediately. In terms of customer facing impact, we anticipate customers will recognize the benefits of the deep learning model enhancements in early Q2 of 2021.

  • How will Ripcord customers benefit from this acquisition?

    What normally took months and weeks to build out will now take a fraction of that time. Ripcord will now accelerate the delivery and absorption of information into models delivering the capability to handle more output with increased intelligence. The evolution of deep learning within the platform will allow for customers to utilize out-of-the-box models as well as provide tooling and infrastructure for customers to train using their datasets.

  • What are questions companies should be asking about the data they place in their models?

    As companies continue to make more effective use of machine learning and AI within their businesses key questions they should be answering on a regular basis include:

    1. Is the data clean?
    2. Do I have enough data?
    3. Is it easy to refresh?
    4. How is it structured?
    5. Does the data exist for the model/question we are trying to answer?

  • Who can I talk to to learn more about what this means for my company?

    The Ripcord team is happy to share more information about what this means for its customers and partners. Drop us an email at Marketing@ripcord.com to set up some time to talk further.

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