Ripcord
Ripcord, Inc. is a robotic digitization company founded in 2014 and headquartered in Los Angeles, California. The company specializes in creating a platform for paperless document management, utilizing advanced technologies such as artificial intelligence, machine learning, and vision-guided robotics. Their primary product, Canopy, employs automation software to capture, enrich, and organize essential content, effectively creating a digital twin of information. By integrating sensors and software automation, Ripcord enables enterprises to enhance their business processes, improving speed, quality, and accuracy in managing important documents. The company, originally known as Ripcord Digital, Inc., rebranded in June 2017 to reflect its focus on innovative digitization solutions.
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’s leading AI-based enterprise solution digitizes countless paper documents to well-structured data swiftly and accurately. To save your time right from the start, any templates and any handwriting styles are allowed for your paper documents with LearningPal’s cutting-edge handwriting recognition technology. LearningPal strongly believes repetitive office work should be automated to unleash the potential of your best assets - employees. LearningPal’s next generation enterprise software always devotes to providing maximum output at minimal cost.
Engine ML solves your biggest pain point in deep learning by training 50x faster so you can reduce training time to gain a competitive advantage and develop the best models. Deep learning can solve the most challenging problems in computer vision, natural language processing, speech, and robotics. Training deep learning models is time consuming and manual. Building your own infrastructure is expensive and risky. Off-the-shelf solutions don’t solve the most important problem in deep learning—distributed training. Efficiently allocate your most expensive and rarest resource—your deep learning engineers—with Engine ML.
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