Testing solutions for AI applications Using Selenium | Quality Engineering Services

Technology Stack

Problem Statement


Quality Assurance: AI service providers want to ensure that their software meets high-quality standards and is reliable. Testing helps identify and fix issues before release, ensuring that the software is of good quality.


Cost Reduction: Fixing software bugs after release can be costly. Testing helps identify issues before release, reducing the cost of fixing them later.


Meeting Requirements: AI service providers need to ensure that their software meets the specific requirements of their end clients. Testing helps ensure that the software meets the expected functionalities, performance, and security requirements.


User Experience Improvement: AI service providers want their end clients to have a positive experience using their software. Testing helps identify any potential issues that could negatively impact the user experience and fix them before release.


Trust Building: Testing helps service providers demonstrate their commitment to quality and reliability, building trust with their end clients. This can lead to long-term relationships and more business opportunities.

Solution Overview


Implemented a comprehensive testing framework to verify the functionality, performance, and security of the web and mobile solution.


Conducted automated regression testing on every build release to ensure that new changes did not introduce any bugs or issues to the existing functionality.


Reported any bugs identified during the testing phase using Azure DevOps, providing visibility to the development team and facilitating timely issue resolution.


Developed new automated test scripts for testing new features and functions, making it easier for the healthcare service provider to ensure the quality of new releases.


Utilized an on-premises device pool to simulate real-world scenarios, ensuring that the solution functioned optimally in a range of different environments.

Business Impact


Improved Application Performance:OptiSol has improved the overall performance and efficiency of the application using a testing strategy in every stage of development, resulting in up to 20% improvement in application performance.


Increased Efficiency: Performance testing helps to identify and resolve performance bottlenecks in the mobile application. We were able to reduce the response time by 50%, resulting in a 30% increase in user engagement and a 20% decrease in user bounce rates.


Enhanced Security: By identifying 20 possible security vulnerabilities and issues before release, software testing has improved the security of AI service provider end client solutions, protecting them from potential threats.


Greater Flexibility: Software testing has allowed AI service providers to experiment with new features and functionalities, identify issues, and make changes before release, leading to greater flexibility and agility in product development.


Cost Savings:OptiSol's implementation of testing strategies helped client to reduce costs by detecting issues early in the development cycle, resulting in a 30% decrease in overall project costs.

Testing Strategies Applied

Performance Testing

  1. Performance testing is a software testing technique that assesses the performance of an application by subjecting it to various workload scenarios.
  2. The aim of performance testing is to uncover any performance-related problems, such as slow response times, bottlenecks, or resource utilization issues, and optimize the application’s performance accordingly.
  3. This type of testing usually involves simulating multiple workload scenarios and measuring the application’s response time, throughput, and resource utilization in each case.

Security Testing

  1. Security testing is a crucial process in software development that involves identifying and mitigating potential security risks in software applications or systems.
  2.  Typically, security testing is conducted after the software has been developed and is ready for testing, as part of the software development lifecycle.
  3. This iterative process entails analyzing the software for potential security risks, creating test cases and scenarios to simulate different types of attacks, and verifying that the software can withstand such attacks.

Automated Regression Testing

  1. Automated regression testing is a technique used in software testing that automates the re-execution of previously executed test cases.
  2. The purpose of this technique is to ensure that existing functionalities of a software application still work as expected after changes or updates have been made.
  3. The primary objective of automated regression testing is to detect any regression issues that may arise from these changes or updates and ensure that the software application’s existing functionalities have not been impacted.

API Testing

  1. Automated API testing is a technique used in software testing to test the Application Programming Interfaces (APIs) of a software application.
  2.  It involves the use of automated tools and scripts to send requests to an API and verify the responses against expected results, ensuring that the API functions as expected.
  3. This testing technique employs specialized testing tools and frameworks to automate the testing process, saving time and reducing the risk of human error.

Testimonials of Our Happy Clients

Related Success Stories

Related Insights

Security Testing using OWASP ZAP for Digital Applications

Software security testing is the process of assessing and testing a system to discover security risks and vulnerabilities of the system and its data…

Top 5 advantages of Functional Test Automation

Functional Test Automation has become a necessity in today’s fast-paced software development world. It helps teams to improve the quality and efficiency…

Top 5 Best Practices for Automation Testing Reporting

Automation testing reporting is a process of generating detailed reports on the results of automated software testing. In automated testing,…

Key Outcomes


Improve test coverage and test efficiency


Faster QA Cycle with proper input data


Delivery the product within the timeline


Finding more defects in complex scenarios


More user-friendly and guarantees improved customer experience

Our Award-Winning Team

A team of young, dynamic and curious minds recognized with global awards for making a significant impact on making human lives better

Awarded as Runner-up under Cloud Solutions Category at the Express IT Awards






Projects for
reputed Clients



in Digital

Awarded as Winner among 1000 contestants at TechSHack Hackathon

Trusted and Proven Engagement Model

  • A nondisclosure agreement (NDA) is signed to not disclose any sensitive information revealed over the course of doing business together.
  • Our NDA-driven process is established to keep clients’ data and IP safe and secure.
  • The solution discovery phase is all about knowing your target audience, writing down requirements, and creating a full scope for the project.
  • This helps clarify the goals, and limitations, and deliver quality products & services.
  • Our engagement model defines the project size, project development plan, duration, concept, POC etc.
  • Based on these scenarios, clients may agree to a particular engagement model (Fixed Bid, T&M, Dedicated Team).
  • The SOW document shall list details on project requirements, project management tools, tech stacks, deliverables, milestones, timelines, team size, hourly/monthly rate cards, billable hours and invoice details.
  • On signing the SOW, an official project kick-off meeting shall be initiated.
  • Our implementation approach, ecosystem, tools, solutions modelling, sprint plan, etc. shall be discussed during this meeting.
Connect With Us!