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Testing Platform for izDox AI Platform

Project associated with:



Testing the izDox AI Platform, designed for document processing and extraction, presented significant challenges due to the complexity of verifying model outputs manually. This manual verification process was time-consuming and impacted testing performance, requiring testers to spend substantial time on documentation and report generation. To address these challenges, an automated testing platform was designed and developed to expedite and enhance the accuracy of product testing, reducing testing times by 85%. This system streamlined operations by automating repetitive tasks, allowing testers to focus on refining testing strategies and ensuring continuous improvement through integrated data analytics.


Reduction in Testing Time:Automate repetitive testing tasks to significantly reduce the time required for product testing.

Accuracy and Efficiency:Enhance the accuracy of testing by minimizing manual errors.
Improve operational efficiency by allowing testers to focus on strategy refinement.

Automated Reporting:Automatically generate relevant reports to eliminate the need for manual documentation.

Integration with Existing Systems:Ensure seamless integration with the izDox backend and database.

Data Analytics:Integrate data analytics capabilities to provide insights into model performance over time, enabling continuous improvement.


Requirement Analysis:

  1. Engaging with testers and stakeholders to understand the specific challenges and needs in the current testing process.

  2. Identifying key features and functionalities required for the automated platform.

Design and Architecture:

  1. Designing the architecture of the automated testing platform, focusing on automation, accuracy, and integration.

  2. Planning the development of a user interface (UI) for testers and a robust backend system.


  • Frontend Development

  1. Developing a user-friendly UI using Angular to facilitate easy interaction for testers.

  • Backend Development:

  1. Implementing the backend using the Django framework to handle logic and data processing.

  2. Integrating the platform with the izDox backend and database for seamless data flow.

Automation Features:

  1. Automating repetitive testing tasks, such as data input and result verification.

  2. Implementing automated report generation based on testing outcomes.

Testing and Validation:

  1. Conducting extensive testing to ensure the platform accurately automates tasks and integrates with existing systems.

  2. Validating the reduction in testing time and improvement in testing accuracy.

Deployment and Monitoring:

  1. Deploying the automated testing platform within the izDox AI Platform infrastructure.

  2. Implementing monitoring and logging to track performance and identify any issues for prompt resolution.

Technologies Used


  • Languages: TypeScript, JavaScript

  • Libraries/Frameworks: Angular

  • Purpose: Developing a user-friendly and interactive UI for testers, facilitating easy interaction and efficient management of testing tasks.

Django Framework:

  • Languages: Python

  • Frameworks: Django

  • Purpose: Implemented for backend development to handle logic, data processing, and integration with the izDox backend and database. Provided a robust and scalable backend infrastructure.

Data Analytics Tools:

  • Languages: Python, SQL

  • Libraries/Frameworks: Pandas, NumPy, Matplotlib, Seaborn

  • Purpose: Integrated data analytics capabilities to provide insights into model performance over time. Enabled continuous improvement by tracking and analyzing testing outcomes.

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