Drishti Technologies Inc.: Managing Operations through Computer Vision, AI and Video Analytics

by: M.S. Krishnan

Publication Date: January 5, 2024
Length: 14 pages
Product ID#: 5-071-980

Core Disciplines: Entrepreneurship & Innovation, Information - Technology & Management, Strategy & Management

Partner Collection:

Available Documents

Click on any button below to view the available document.

Don't see the document you need? Don't See the Document You Need?
Make sure you are registered and/or logged in to our site to view product documents. Once registered & approved, faculty, staff, & course aggregators will have access to full inspection copies and teaching notes for any of our materials.


Need to make copies?

If you need to make copies, you MUST purchase the corresponding number of permissions, and you must own a single copy of the product.

Electronic Downloads are available immediately after purchase. "Quantity" reflects the number of copies you intend to use. Unauthorized distribution of these files is prohibited pursuant to term of use of this website.

Teaching Note

This product has a teaching note available. Available only to Registered Educators. Please login to view it.


The case follows innovations by Drishti, a start-up company that uses artificial intelligence (AI) and computer vision to provide manufacturers with granular process data on manual assembly, giving them a system-wide view into their manufacturing operations. The firm was founded in 2016 by Dr. Prasad Akella, Dr. Krishnendu Chaudhury, and Dr. Ashish Gupta, who all had extensive experience in industrial process automation. They prioritized the value of enhancing human potential in an increasingly automated world.

Noting the limitations of traditional manufacturing line performance evaluation and process improvement, Drishti Technologies presented new capabilities for real-time monitoring and performance improvements. This case is about entrepreneurs creating a new software in an established industry. The case also describes the core functionality and solutions developed from the new software, value provided to customers, and the strategic business model choices faced by the leadership in moving from start-up to scale.

Teaching Objectives

After reading and discussing the material, students should:

  • Express how entrepreneurs can lift customer companies past the limitations and assumptions of traditional approaches to manufacturing process improvement.
  • Illustrate how emerging technology (e.g., computer vision, AI) can be meshed with existing processes and technology to improve the operational performance of businesses (in this case, manufacturing factories).
  • Identify the pros and cons of any technology-inducing change in an organization, and the challenges of driving behavioral changes with new technologies.
  • Understand the benefits and challenges of having unbiased performance data through video analytics.
  • Analyze the trade-offs faced by software companies in the business model, and pricing decisions with a product vs. a service.