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Computer Vision SaaS Application Development


Product Manager, UX / UI Designer, Solution Architect, Client Engagement Lead, Agile Software Development Team





Staff Augmentation



Groundlight is an innovative application that leverages Machine Learning Models and Computer Vision algorithms to analyze images. They approached Leanware in search of a reliable partner to enhance their product capabilities and transition into the SaaS phase.

Groundlight's technology enables users to ask questions about an image in a video stream (computer vision), for instance, inquiring about the status of doors, whether they are open or closed, or looking about safety measures in industries by analyzing the use of safety helmets. It has widespread applicability across various domains and use cases,

With Leanware as their partner, Groundlight successfully improved its product, gaining traction by enhancing features and functionality in its Computer Vision product.

This partnership resulted in acquiring new users, creating a more user-friendly interface, streamlining business processes, and an overall improvement in the application's performance and reliability.

Python, React.js, Amazon Web Services, Kubernetes, Django, Github Actions

Tech Stack Involved

Our software development team's contributions to Groundlight included:

Human Intervention Integration: 

When the algorithm fails to provide correct answers, we implemented a system for human intervention and disagreements. This feedback is used to train and refine the machine learning model, enhancing its future performance.

User Interface and Experience Improvements: 

Significant efforts were made to improve the platform's UI and UX, making it more intuitive and user-friendly for clients in the manufacturing sector.

Feature Implementation: 

Implementation of features like signups, designing bounding boxes on images, and account metrics usage by user, adding to the functionality and usability of the application.

Overall Code Enhancement: 

We focused on refining and optimizing the overall code base to ensure better performance, scalability, and maintainability of the application.


Before Our Intervention:

  • Groundlight's initial MVP needed enhancements in various areas, including accuracy, user interaction, and interface design.

After Implementing Leanware:

  • Improved Algorithm Accuracy: The Computer Vision algorithm became more accurate and reliable in image analysis and responding to safety-related queries.

  • Enhanced User Experience: The improvements in UI and UX made the platform more accessible and easier to use for manufacturing industry personnel.

  • Effective Human-AI Collaboration: The integration of human intervention in the learning loop of the ML model greatly improved its accuracy and adaptability.

  • Streamlined Business Processes: The development of business flows and additional features like bounding box design and user metrics enhanced the overall functionality of the platform.

  • Safer Manufacturing Environments: The application now effectively aids in monitoring safety compliance, contributing to safer working conditions on the shop floor.

Through these developments, Groundlight has transformed into a more efficient, user-friendly, and accurate tool for ensuring safety compliance in the manufacturing industry.

From Blueprint to Delivery



Understanding the need for a seamless and user-friendly interface, we focused on enhancing the usability and functionality of Groundlight’s innovative image analysis platform.

  • User-Centric Design: We prioritized creating an intuitive interface tailored to users in the manufacturing sector. Our design ensures that even non-technical personnel can easily navigate the platform to monitor safety compliance and analyze image data effectively.

  • Interactive Visual Elements: The UI includes interactive elements such as dynamically designed bounding boxes on images, enabling users to highlight and focus on specific areas within a video stream.

  • Enhanced Analytics and Metrics: Our redesign incorporated comprehensive analytics and user metrics dashboards, offering users detailed insights into their usage patterns and the platform’s performance. This helps users track safety compliance and identify potential areas for improvement.

  • Human-AI Collaboration: We integrated a human intervention system to complement the machine learning model. When the algorithm encounters uncertainties, users can step in to provide feedback, which in turn trains and refines the model, ensuring continuous improvement in accuracy and reliability.

By focusing on these critical aspects of UX and UI, Groundlight has successfully transitioned into a more efficient, user-friendly, and reliable SaaS product, driving safer manufacturing environments and enhancing overall business processes.

Looking for a World-Class App Development? 

Let's chat about it.

Tailored components, crafted with detailed precision.

Designed components can be easily scalable following clients needs.”

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