Ripcord

Ripcord, Inc. is a robotic digitization company that specializes in automating the management of paper records. Founded in 2014 and headquartered in Los Angeles, California, Ripcord develops a platform that utilizes advanced technologies, including artificial intelligence, machine learning, and vision-guided robotics, to create digital twins of physical documents. Its flagship solution, Canopy, captures, enriches, and organizes critical content, allowing enterprises to enhance their business processes with improved speed, quality, and accuracy. Formerly known as Ripcord Digital, Inc., the company rebranded in June 2017 to reflect its focus on innovative digitization solutions.

Michael Coombs

EVP of Finance

Joni Woo

SVP of Customer Success

3 past transactions

VASTEC

Acquisition in 2025
VASTEC is a small business with big capability. Headquartered in Tampa, with locations in Alexandria, VA, Dallas, and Houston, VASTEC has earned a reputation for quality of service.Founded in 2006, the VASTEC mission is to provide quality products and services utilizing its experienced and skilled personnel, ensuring accurate and timely delivery to clients,while maintaining a secure environment where client-sensitive data is protected at the highest level.

LearningPal

Acquisition in 2022
LearningPal is a developer of an AI-based enterprise platform that specializes in the digitization of paper documents into well-structured data. Utilizing advanced image and handwriting recognition technology, LearningPal can accommodate various templates and handwriting styles, significantly reducing the need for manual document processing. The company's solutions aim to streamline repetitive office tasks, allowing employees to focus on more valuable activities. By enhancing efficiency and minimizing costs, LearningPal's platform is designed to optimize operational productivity while delivering high-quality output for its clients.

Engine ML

Acquisition in 2020
Engine ML Inc. is a technology company based in San Francisco, California, specializing in distributed deep learning solutions. Founded in 2018, Engine ML addresses significant challenges in deep learning by enabling training processes to occur up to 50 times faster than conventional methods. This acceleration allows clients to reduce training times, facilitating the development of superior models in areas such as computer vision, natural language processing, speech, and robotics. The company provides infrastructure that leverages the computational power of multiple GPUs, streamlining access to machine learning engineering cycles. Engine ML aims to optimize the utilization of deep learning engineers, alleviating the burdens of building costly and complex infrastructures while tackling the critical issue of distributed training in machine learning.
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