Multi-Health Systems' Computer Vision Assessment Pipeline

Worked with leadership as an AI Consultant at MHS Assessments to create and help develop an AI strategy and roadmap to propel the company through their digitization age. This AI strategy directly aligns with their efforts to go from 50 mil ARR to 100 mil ARR.

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Description

Multi-Health Systems (MHS) is a globally recognized publisher of scientifically validated assessments, boasting over 30 years of experience in serving a diverse range of sectors including education, clinical, corporate, public safety, government, military, pharmaceutical, and research. MHS has evolved into an international entity, distributing products in more than 75 countries and offering translations in over 50 languages. Recently, MHS has focused on enhancing the digital user experience and extending its global reach.

Challenge

MHS faced the challenge of modernizing their existing assessment tools, which had become outdated. The primary objective was to integrate technological innovation, specifically Artificial Intelligence (AI), into their assessment offerings. This integration aimed to initiate a new phase in their roadmap, minimize barriers for client adoption, and enhance the overall efficiency of their assessments. The goal was to leverage AI to revolutionize their assessment process, making it more streamlined and effective.

Solution

Over a period of 1.5 years, we collaborated with MHS to develop a strategic AI integration roadmap and successfully implemented several AI-based solutions. A key project involved the creation of a Computer Vision-based web application. This application was designed to instantly grade pre-existing assessments by processing images of these assessments. The solution employed advanced technologies such as:

  • Object Detection: To accurately identify and categorize different elements within the assessment images.
  • Optical Character Recognition (OCR): To convert various types of printed text from the images into machine-encoded text.
  • Handwriting Recognition: To interpret and digitize handwritten responses and marks on the assessments.

These technologies were integrated into a scalable AI pipeline, which significantly reduced the reliance on manual grading by administrators. The impact of this solution was profound:

  • Reduced Time for Assessment: The AI pipeline cut down the time required for assessment marking by over 50%, streamlining the entire process.
  • Increased Efficiency: By automating the grading process, MHS was able to provide quicker and more consistent results, enhancing the overall efficiency of the assessment process
  • Scalability and Adaptability: The AI solution was designed to be scalable, allowing MHS to handle a larger volume of assessments without additional resource allocation. It also ensured adaptability to various types of assessments.

In summary, the collaboration with MHS led to the successful integration of AI into their assessment processes. This technological advancement not only modernized MHS’s assessment tools but also set a new standard in the efficiency and effectiveness of educational and professional assessments.