Quality Automation and Testing | Applied AI Consulting

Transforming QA Efficiency: Achieving 80% Regression Time Reduction through Automation

Wed, 16 Oct 2024 12:19:33 +0000

Transforming QA Efficiency: Achieving 80% Regression Time Reduction through Automation

Streamlining Quality Assurance with Automated Testing for Faster Results

Company Overview

A leading sales and marketing tech organization partnered with Applied AI Consulting to enhance the quality assurance of their campaign analytics application. The analytics application provides users with comprehensive insights into campaign performance. Its core functionality revolves around generating reports based on selected instructions, enabling users to gain valuable data-driven insights to optimize their campaigns. The application is organized into several key modules, each playing a critical role in delivering a complete analytics experience.

Dashboard: Displays campaign data visually through charts and graphs, offering an overview of campaign performance. It also provides key information on campaign assets and leads.

Campaigns: Lists all current and past campaigns, showing important metrics like assets, leads, and total campaign value. This module helps users track and analyze the performance of individual campaigns.

Report Module: Allows users to generate reports based on campaign data by selecting specific FAQs. These reports offer detailed insights into campaign outcomes, customized to the user’s needs.

Templates: Provides pre-built templates that users can apply to generate reports across different campaigns, saving time and ensuring consistency in report creation.

FAQs (Frequently Asked Questions): For each FAQ, report generation instructions are crafted using ChatGPT prompts. Based on these predefined instructions, the system generates corresponding reports. When a user selects an option from the FAQ list, the system utilizes the instruction linked to that selection to generate the report automatically.

User Management: This module enables administrators to manage user accounts, assign roles, and define access levels, ensuring secure and efficient use of the platform.

This modular structure offers flexibility and scalability, allowing users to quickly generate customized reports and gain actionable insights from their campaign data.

Challenges

Dependency on Manual Testing

Manual testing was the primary method for testing new features, causing delays and limiting scalability as it consumed significant time and resources for each release.

Incomplete Automation Framework

Although an external expert had initiated the automation framework (Cucumber Selenium with Java), it required further completion and alignment with the development team to be fully functional.

Framework Instability & Resource Strain

Frequent failures in the automation framework during daily pipeline executions led to unreliability, forcing the QA team to rely on manual testing for around 40-50% of the process, especially as new features were continuously added.

Coordination Challenges

The team struggled to synchronize manual and automation testing efforts with developers, particularly due to the division of responsibilities between the two testing methods.

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Operations Conducted

Completion and Stabilization of Automation Framework

The team completed and stabilized the Cucumber Selenium framework (Java-based) that had been left incomplete by an external expert. By addressing failures, they ensured reliable automation execution, significantly reducing manual intervention.

Introduction of Structured Test Packs

Three key test packs were automated:

Sanity Test Pack (25 test cases across all environments)
Regression Test Pack (100+ daily tests via Jenkins)
Post-Deployment Sanity Checks to monitor application health after each deployment

Enhanced Automation Across Environments and Reduced Manual Effort

Automation was expanded across Develop, Staging, and Production environments, ensuring thorough sanity and regression testing. This reduced manual testing efforts by 40-50%, allowing the team to focus on testing new features and improving overall efficiency.

Strategic Approach

Stabilization of Automation Framework for Reliable Deployment

The QA team successfully stabilized the Cucumber Selenium framework, integrating it into the deployment process. This resulted in reliable daily test executions, with failure rates dropping to 5-10%, and ensured no major bugs reached production.

Implementation of Structured Test Packs for Efficiency

Introducing structured test packs—Sanity, Regression, and Post-Deployment Sanity Checks—optimized the testing process, saving 70% of the time previously spent on manual testing. Automation provided accurate and timely reports, enhancing QA efficiency.

Enhanced Time and Cost Efficiency

Automation saved approximately 70% of the time previously required for manual testing and reduced QA costs by 50-60%, especially during the development phase. This efficiency accelerated production releases and reduced overall expenses

Positive Influence

Enhanced Time and Cost Efficiency

Automation achieved a remarkable 70% reduction in time previously spent on manual testing and cut QA costs by 50-60%, particularly during the development phase. This boost in efficiency facilitated quicker production releases and lowered overall expenses.

Improved Accuracy and Reliability

By minimizing human errors, automation enhanced testing accuracy by 70%, leading to more consistent outcomes and higher-quality production deployments. This improvement ensured that the software met stringent quality standards with every release.

Continuous Stability Assurance

Daily automated test runs and post-deployment sanity checks ensured ongoing application stability. This approach enabled regular updates without jeopardizing core functionalities, while Jenkins pipelines and Slack notifications provided swift issue resolution.

Long-term Scalability

Continuous Expansion of Automation Coverage

As new features and functionalities are introduced, the automation framework can be continuously expanded. By regularly integrating new test cases into the existing test packs (e.g., sanity and regression), the framework will be able to handle future product updates efficiently, further reducing manual testing efforts.

Cross-Environment Automation

The current setup, which supports automation across Develop, Staging, and Production environments, is scalable to additional environments if needed. Automation can also be extended to handle complex integration tests, performance tests, and end-to-end scenarios.

Advanced Reporting and Analytics

Integrating advanced analytics into the testing pipeline will provide deeper insights into trends, failure patterns, and performance, helping to predict issues earlier in the development cycle. This can lead to smarter decisions for future releases and improved test case management.

CI/CD Pipeline Optimization

As the CI/CD process is further streamlined with tools like Jenkins, there is room to optimize the pipeline with more frequent releases, quicker feedback loops, and integration of newer DevOps tools to enhance automation efficiency.

Key Takeaways

The shift towards automation in the project has greatly improved the quality assurance process, reducing both time and cost while delivering more reliable, accurate test results. Automation helped resolve 70-80% of the issues and stabilized the testing framework, contributing to faster production releases with minimal failures. The introduction of structured test packs for sanity, regression, and post-deployment checks ensured consistent validation across all environments. With the successful integration of automation, the project is well-positioned to scale its testing process as new features are introduced, ultimately providing ongoing business value through time savings, cost reductions, and improved accuracy. Continuous improvements in the automation framework and CI/CD pipeline will further enhance its capability to support rapid and reliable software deployments in the future.

Customer Testimonials

AAIC's continuous and instrumental support in QA has been exceptional. Their ability to take charge of manual testing and swiftly transform it into automated processes has greatly improved the overall efficiency. The implementation of regression and sanity test automation across all environments has ensured seamless and reliable QA validation post-deployment. Their thorough and diligent approach has been recognized as a key factor in enhancing the testing process, contributing to faster, more robust deployments.
Head of QA Engineer

Revolutionizing QA Testing: Reducing Regression Time by 80% Through Advanced Automation

Tue, 08 Oct 2024 11:16:51 +0000

Revolutionizing QA Testing: Reducing Regression Time by 80% Through Advanced Automation

Transforming Software Quality Assurance for Faster and More Reliable Releases

Company Overview

A leading software development firm partnered with Applied AI Consulting to enhance the quality assurance of their web application. The project involved comprehensive performance testing to evaluate the solution’s ability to handle large data sets and assess the API’s performance under high user loads.

The application integrates with platforms like LinkedIn to provide users with detailed, up-to-date information about companies and individuals. Key features of the application include:

Data Retrieval: Fetches comprehensive data on employees, branches, and companies from LinkedIn.

Search Functionality: Enables users to search for companies or employees, delivering relevant data quickly.

Credit System: Users spend credits to unlock specific information such as contact details.

Team Management: Managers can oversee credits, control team access, and share data among team members.

Bulk Updates: The application performs regular data updates, typically monthly, to reflect changes such as employee shifts or new company branches.

Admin Portal: An internal tool used by the product owners to manage credits and access control, ensuring smooth operations.

Application’s robust features and Applied AI Consulting’s performance testing helped ensure the platform could efficiently scale, delivering accurate, timely data under heavy user demands.

Issue

Manual to Automated Testing: Transitioning from manual to automated testing reduced regression time from 8 hours to 1.5 hours, saving 6.5 hours per run, improving speed and reliability in the QA process.

Testing Environment Issues: Local testing environments were unreliable and lacked visibility, prompting a shift to centralized, accessible systems for better test management.

Random Test Failures: Random failures occurred due to shared resources during parallel testing, resolved by using separate test environments and accounts.

Performance Testing: Automated stress tests (25-50 users over 12-24 hours) ensured application stability under load, integrated into the release pipeline for continuous performance assurance.

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Actions Taken

Automated Testing with Selenium and Cucumber

The team automated over 320 test cases using a Selenium Java Cucumber framework, reducing testing time and eliminating human error. The suite runs independently, improving efficiency.

Jenkins & GitHub Integration

The automation suite was integrated with Jenkins for continuous testing and GitHub for version control, allowing tests to be scheduled and results to be shared, boosting collaboration.

Performance Testing & Failure Resolution

JMeter simulated 50 concurrent users to ensure stability under load, while private accounts and dedicated environments resolved random test failures caused by concurrent testing conflicts.

Solution

Reduced Regression Test Time

Shortened Sprints: Faster testing enables quicker completion of sprints, allowing for rapid feature iterations.

Quicker Go-to-Market Timelines: Accelerated testing facilitates faster transitions from development to production, helping the organization launch new features ahead of competitors.

Improved Testing Reliability

Enhancements led to fewer random test failures, creating a more reliable and stable testing environment.

Business Value of the Outcome

Cost Reduction: The reduced testing time significantly lowered AWS usage costs, achieving around 80% savings in overall expenses.

Faster Delivery Cycles: Streamlined processes enabled quicker transitions from staging to production, enhancing responsiveness to market demand.

Value Stream

Automated Testing Improvement: The effectiveness of the automated testing framework was enhanced, yielding more accurate and timely results.

Faster Decision-Making: The improved testing process provided quicker insights into application readiness, allowing clients to make informed decisions promptly and facilitating faster go-to-market strategies.

This diagram illustrates the integration of CI/CD pipelines for code development and testing, alongside an automated test framework using BDD practices, Jenkins for execution, and TestRail for tracking.

Impact

Increased Efficiency

Automation and parallel processing significantly reduced manual overhead, leading to a 50% increase in testing throughput. Regression testing time dropped from over 8 hours to just 1 hour and 30 minutes, yielding substantial cost savings for the client.

Enhanced Application Stability

Continuous performance testing has built confidence in the application's reliability during real-world usage. This proactive approach has led to a 30% reduction in post-deployment incidents, minimizing critical failures and improving overall application performance for users.

Improved Client Satisfaction

Faster testing cycles deliver accurate results, enhancing client trust and satisfaction. With quicker insights, clients can make informed decisions more rapidly, improving their overall experience and fostering stronger relationships with the testing team.

Customer Testimonials

Collaborating with Applied AI Consulting has revolutionized our QA processes for our application. By implementing an automated testing framework with Selenium, Java, and Cucumber, we reduced our regression testing time from over eight hours to just 1 hour and 30 minutes--an 80% reduction. This efficiency has allowed us to shorten sprints and launch new features faster than ever, giving us a competitive edge. The integration with Jenkins for continuous testing has also enhanced reliability, decreasing random test failures significantly. Moreover, we've achieved approximately 80% savings in AWS costs and a 30% drop in post-deployment incidents, greatly improving our client satisfaction. Thanks to Applied AI Consulting, we're now better positioned for sustainable growth and success.
Head of Engineer

Enhancing System Scalability and User Experience: A Performance Testing Case Study

Thu, 26 Sep 2024 18:40:11 +0000

Enhancing System Scalability and User Experience: A Performance Testing Case Study

Ensuring Scalability and Reliability Through High-Volume Data Processing and Stress Testing

Company Overview

A client using Applied AI Consulting’s services required performance testing for their application. The aim was to assess the application’s performance by uploading large data sets and determining how long the system takes to validate a batch file. Additionally, it was crucial to test how the API handles high user load and stress scenarios to ensure reliability, scalability, and responsiveness during real-world operations.

Issue

Ensuring the application operates smoothly under heavy load, preventing costly outages and disruptions.

Quick and efficient data validation to keep end users satisfied and avoid delays in critical business operations.

Ensuring the system can manage larger data sets to support business growth and seasonal traffic spikes.

Maintaining high performance levels to accommodate expanding user bases without compromising system efficiency.

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Actions Taken

Batch File Uploading and Validation

Tested the system’s ability to handle substantial data uploads and efficiently validate large datasets without performance degradation.

Checking Batch Status & Exporting Completed Files

This tested the system’s ability to report on and export data without affecting ongoing operations.

Credit Validation

We also tested how credit checks are performed under different user loads.

Solution

Scalability Assurance

With data showing the system could handle up to 10M records, the client gained confidence that they could scale their operations without worrying about performance issues

Operational Efficiency

Identifying and addressing bottlenecks early ensured the system could handle high traffic without slowing down, leading to fewer disruptions and better user experiences.

Improved Decision-Making

The insights from the tests allowed the client to make informed decisions about where to optimize infrastructure for better performance.

Impact

Scalability

The application’s ability to manage up to 10 million records and scale with growing user demands gave the client confidence in their platform’s future growth potential.

Optimized User Experience

Performance improvements led to faster system responses, resulting in higher user satisfaction and better customer retention.

Informed Decision-Making

Detailed reports enabled the client to prioritize investments in infrastructure and optimizations, ensuring resources were allocated effectively for maximum return on investment.

Customer Testimonials

Working with Applied AI Consulting has significantly improved the performance of our application. Their thorough testing helped us identify critical bottlenecks, allowing us to scale effectively while maintaining system stability and delivering a seamless user experience under heavy load.
Head of Engineer

Quality, Application Performance: How to Enhanced Scalability and Reliability Through Comprehensive Load Testing

Thu, 26 Sep 2024 17:00:09 +0000

Quality, Application Performance: How to Enhanced Scalability and Reliability Through Comprehensive Load Testing

Achieving Seamless User Experience and System Stability Through Targeted Load Testing

Company Overview

A client of Applied AI Consulting, sought performance testing for their reviews and ratings application, which is utilized by major e-commerce platforms like Flipkart. The goal was to evaluate how the API performs under high user load and stress conditions to ensure the platform’s reliability, scalability, and responsiveness during peak usage in real-world scenarios.

Issue

Ensured the application could handle increased user loads, supporting future growth and preventing service interruptions. (Tools: Apache JMeter, aiTest)

Prepared the platform for handling peak traffic and business expansion.
Prevented system failures and downtime during high-demand periods.

Identified and fixed performance issues in critical functionalities to maintain consistent service delivery. (Tools: Apache JMeter, aiTest)

Ensured uninterrupted service availability for users.
Maintained low error rates and fast response times.

Measured the impact of user loads on application performance to guide system improvements. (Tools: Apache JMeter, aiTest)

Improved system efficiency and user satisfaction.
Enhanced responsiveness for a smoother user experience.

Utilized Apache JMeter and aiTest to simulate user interactions and evaluate performance across various API endpoints, ensuring comprehensive functionality coverage.

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Actions Taken

Implemented Load Testing Tools

Applied Apache JMeter and aiTest to simulate user interactions and assess performance across various API endpoints, ensuring a thorough evaluation of critical functionalities.

Conducted Gradual Load Testing

Tested the platform with user loads ranging from 100 to 5000 to assess system performance and identify potential areas for optimization.

Analyzed Performance Data

Reviewed data to detect performance degradation and bottlenecks, providing actionable insights for system improvements.

Solution

Response Time Insights

 Identified significant performance slowdowns with increased user loads, highlighting areas needing improvement to ensure faster user interactions. (Tools: Apache JMeter)

Revealed performance issues that needed addressing to maintain efficiency. Guided optimizations to improve response times and service quality.

Failure Rate Identification

 Found high failure rates in critical processes under heavy loads, pointing out where reliability enhancements were necessary. (Tools: aiTest)

Highlighted reliability issues affecting user experience. Enabled focused improvements to prevent system failures.

Bottleneck Detection

Pinpointed key bottlenecks in processes, allowing for targeted enhancements to improve system performance and user satisfaction. (Tools: Apache JMeter, aiTest) Identified specific performance issues causing delays. Enabled precise optimizations to enhance overall system reliability.

Customer Testimonials

Applied AI Consulting's performance load testing was crucial in helping us identify and resolve bottlenecks in our application. They tested our system under heavy user loads, pinpointing areas for improvement, which enhanced our platform's scalability and reliability. Their insights allowed us to optimize performance, ensuring a better user experience even during peak demand. We highly recommend their expertise
Head of Engineer

Quality – Performance and Reliability: How to Leveraged Automation Testing to Handle 30,000 Concurrent Users

Thu, 26 Sep 2024 16:29:33 +0000

Quality - Performance and Reliability: How to Leveraged Automation Testing to Handle 30,000 Concurrent Users

Enhancing Scalability and User Experience Through Advanced Automation Solutions

Company Overview

An education technology platform that helps small and medium-sized businesses launch and manage online training products. It provides a comprehensive suite of tools for managing training businesses, including services like course creation, event management, and payment integration. The system architecture is based on microservices and Kubernetes.

Issue

Validate the system’s capability to manage up to 30,000 concurrent users without performance issues, essential for supporting large-scale online training events.

Test critical workflows, including event and course checkouts, to ensure reliability under high user demand.

Automate complex workflows across microservices to validate resilience and maintain system integrity during peak usage periods.

Ensure seamless user interactions and maintain high service quality through rigorous testing and performance optimization.

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Actions Taken

Implemented Automation Tools

Utilized advanced automation tools to streamline testing processes, ensuring comprehensive coverage and efficiency.

Progressive Load Testing

Gradually tested the platform’s capacity from 1,000 to 30,000 users, allowing for precise performance tuning a

Optimized Performance and Reporting

Addressed bottlenecks, enhancing system speed and reliability, while delivering detailed reports to boost stakeholder confidence.

Solution

Scalable Performance

Successfully supported up to 30,000 concurrent users, demonstrating the platform’s capability to handle high demand without compromising performance.

Improved System Reliability

Resolved key issues, leading to a robust system that operates reliably under peak conditions.

Enhanced User Experience

Achieved a 2-second page load time, significantly improving user satisfaction and engagement.

Informed Decision-Making

Provided stakeholders with comprehensive performance reports, facilitating better strategic decisions and reinforcing trust in the platform.

Impact

Enhanced Scalability

Efficiently managed thousands of concurrent users, ensuring the platform can handle peak demands.
Increased capacity for high user volumes.
Prepared for future growth and expansion.

Cost Savings

Reduced the need for manual testing, saving time and resources.
Lowered testing costs.
Decreased labor and resource expenditures.

Improved Reliability

Boosted platform stability by resolving performance issues, leading to consistent service quality.
Increased system dependability.
Minimized downtime and disruptions.

Customer Testimonials

Our client's ed-tech platform, faced challenges with reliability and scalability. Before aiTest, we manually tested our complex microservices architecture, but it didn’t provide the confidence we needed. Working with aiTest, we scaled our load testing from 1,000 to 30,000 users, identified key issues, and resolved them efficiently.

Their all-in-one solution helped us meet our SLA of two seconds per page load, and the detailed reports boosted client confidence. aiTest has been invaluable in ensuring our platform can scale and perform reliably, and I highly recommend their services.
Makarand Bhatamrekar

Enhancing Deployment Success with Python Selenium Automation for a Leading Content Marketing Platform

Fri, 23 Aug 2024 15:50:57 +0000

Enhancing Deployment Success with Python Selenium Automation for a Leading Content Marketing Platform

Company Overview

A leading company in the content marketing domain, this organization helps brands and their customers connect through high-quality, relevant content. The platform enables companies to produce and disseminate their own content, improving customer acquisition, building brand loyalty, and sustaining interest in their offerings. Known for its innovative approach and commitment to quality, the company serves a diverse clientele, including top brands and enterprises, ensuring their content marketing strategies are effective and impactful.

Issue

Ensuring consistent and reliable deployments across multiple environments.

Reducing manual testing efforts and increasing the efficiency of the QA process.

Automating repetitive tasks to free up resources for more strategic activities.

Enhancing the overall quality and performance of their content marketing platform.

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Solution

Streamlined UI testingby implementing Python Selenium for automation, enhancing efficiency and reducing manual testing efforts.**

Developed automated test scriptsto validate critical functionalities across various environments, ensuring consistent performance.

Integrated automation with CI/CD pipelines** for continuous testing and deployment, along with providing training and documentation for seamless adoption by development and QA teams.

Impact

Increase in Deployment Success

Significantly reduced failed deployments and rollbacks, enhancing reliability in the deployment process.

Reduction in Manual Testing

Freed up the QA team to focus on complex tasks, driving efficiency and strategic improvements.

Enhanced Quality and Customer Satisfaction

Improved platform performance and reliability, supporting faster, more dependable releases aligned with company growth and innovation goals.

Customer Testimonials

Applied AI Consulting’s mastery in Python Selenium automation was a game-changer for us. Their ability to integrate seamlessly with our CI/CD pipeline drastically improved our deployment success rate by 50%, while cutting down manual testing by 70%. Their innovative approach and commitment to excellence have significantly elevated our platform's performance, enabling us to deliver faster and more reliable releases.
CTO marxeed.com

Driving Quality and Reliability for Modern Mobile and Web Applications

Wed, 21 Aug 2024 15:26:41 +0000

Driving Quality and Reliability for Modern Mobile and Web Applications

Building a Modern Mobile and Web Application with Robust CI/CD Automation and AI-Powered Multi-Device Testing

Company Overview

A leading start-up in the online consulting platform domain, this company focuses on connecting end-users with top industry professionals for expert consultation services. Known for its innovative approach and cutting-edge technology, the company aims to provide seamless and efficient solutions for both consultants and clients, ensuring high-quality interactions and problem-solving experiences. Applied AI Consulting has created the modern stack with payment gateway integration for this customer. This case study is focused on quality engineering.

Issue

Cross-Platform Compatibility: Building a modern application that supports both mobile and web platforms can introduce challenges in ensuring consistent functionality and user experience.

Testing Coverage: Ensuring thorough and reliable UI and API testing to cover all possible use cases and scenarios, which is crucial for maintaining application quality and reliability.

Automation Integration: Integrating automation testing into the CI/CD pipeline effectively, ensuring that automated tests run seamlessly with each deployment to catch issues early.

Performance and Reliability: Maintaining high performance and reliability of the application across multiple platforms and under varying load conditions.

Let’s discuss your use cases

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Solution

Developed and Integrated Automation Frameworks: Created a Selenium-Python-based framework for UI testing and a pyTest framework for API testing, integrating them with the CI/CD pipeline.

Executed Cross-Platform Testing: Utilized aiTest for automation across multiple devices, browsers, and versions, including API quality validation with Postman collections.

Enhanced Communication and Visibility: Provided test execution updates and analytics through Slack and email, and demonstrated automation results in end-of-iteration demos.

Impact

Enhanced Quality and User Experience

Achieved very high application quality with minimal defects and ensured a seamless user experience across devices and browsers.

Accelerated Release Cycles

Reduced testing time by 40% through CI/CD integration and automation, leading to faster feature releases and updates.

Cost Savings and Performance Improvement

Decreased testing-related costs by 30% and improved application performance, contributing to higher user retention and scalable growth.

Customer Testimonials

Applied AI Consulting has been instrumental in driving the quality and reliability of our mobile and web applications. Their expertise in building a modern stack with seamless payment gateway integration has allowed us to provide our users with a smooth and efficient experience. The team's commitment to excellence and their innovative approach have significantly enhanced our platform's performance, ensuring we meet the high standards our clients expect.
Founder Click to Connect

Ensuring Performance and Scalability for Demand Generation Tech with Advanced Automation Testing

Wed, 21 Aug 2024 14:37:36 +0000

Ensuring Performance and Scalability for Demand Generation Tech with Advanced Automation Testing

Company Overview

A leading company in the demand generation technology sector, this organization provides data-driven marketing solutions to help businesses drive revenue growth. With a comprehensive suite of services, including lead generation, data management, and analytics, the company supports its clients in enhancing their marketing effectiveness. Known for its innovative approach and robust technology infrastructure, the company continuously seeks to improve its product offerings and operational efficiency.

Issue

Create a TestNG Maven framework for UI automation and RestAssured for API automation.

Perform functional UI and API automation and performance testing (load testing) to support 25,000 concurrent users on API calls and 5,000 concurrent users on UI with 30 million plus records in the database.

Integrate automation with the CI/CD pipeline.

Maintaining high availability and reliability.

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Solution

Accelerated multi-browser testing and load testingby leveraging AAIC’s aiTest, ensuring comprehensive UI and backend performance validation.**

Developed a robust TestNG Maven frameworkwith Selenium and Java for UI automation, and RestAssured for API automation, enabling efficient and scalable testing.

Drastically reduced build qualification time** by implementing parallel test runs, cutting UI test time to 9 minutes and API test time to just 2-3 minutes.

Impact

Comprehensive Framework

Led by a QA lead, AAIC’s 5-member QA team architected and implemented a robust testing framework, covering functional UI and API automation, and enabling large-scale load testing.

High-Scale Load Testing

Successfully conducted load tests for 25,000 concurrent API users and 5,000 concurrent UI users, with a database of over 30 million records, ensuring the application’s performance and scalability under heavy load.

Seamless CI/CD Integration

Integrated automation with the CI/CD pipeline, enabling rapid and efficient build qualification tests, boosting confidence in the application’s readiness for deployment.

Building a Comprehensive Online Consulting Platform with Payment Integration for a Leading Start Up

Wed, 21 Aug 2024 12:48:08 +0000

Building a Comprehensive Online Consulting Platform with Payment Integration for a Leading Start-Up

Enhancing User Experience with Secure Payments, Real-Time Notifications, and Automated Deployments

Company Overview

Issue

Ensuring high availability and scalability of the mobile and web applications.

Integrating a reliable and secure payment gateway.

Automating the deployment processes to reduce downtime and improve efficiency.

Maintaining high performance and user experience during peak loads.

Let’s discuss your use cases

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Similar Use Cases

What Is an AI Maturity Model?

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Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Successfully deployed the ClickToConsult mobile application on both the App Store and Play Store, leveraging Firebase for push notifications and AWS Lambda for backend processes, ensuring scalability and cost efficiency.

Implemented a robust web-based interface for managing administrative activities, with integrated Razorpay payment gateway for secure transactions, providing a seamless experience for users and administrators.

Set up CI/CD pipelines for automated deployments across the mobile and web platforms, minimizing downtime and facilitating smooth, efficient updates.

Impact

Launch of a Scalable Consulting Platform

Successfully launched a scalable and high-performing online consulting platform, ensuring seamless interactions and enhanced user experience.

Secure Payments and User Trust

Integrated a secure and reliable payment gateway, boosting user trust and satisfaction through secure transactions.

Cost Efficiency with Serverless Architecture

Achieved significant cost savings and operational efficiency by utilizing serverless architecture and automated deployments.

Driving Quality and Reliability for Modern Mobile and Web Applications: A Case Study for a Leading Online Consulting Platform

Tue, 20 Aug 2024 15:53:13 +0000

Driving Quality and Reliability for Modern Mobile and Web Applications: A Case Study for a Leading Online Consulting Platform

Developed a modern app with mobile and web support, integrated automated testing using Selenium, pyTest, and aiTest, and validated API quality with Postman for consistent, reliable results.

Company Overview

A leading start-up in the online consulting platform domain, this company focuses on connecting end-users with top industry professionals for expert consultation services. Known for its innovative approach and cutting-edge technology, the company aims to provide seamless and efficient solutions for both consultants and clients, ensuring high-quality interactions and problem-solving experiences. Applied AI Consulting created the modern stack with payment gateway integration for this customer, emphasizing quality engineering to ensure reliability and performance.

Issue

Building a modern application with mobile and web support for their consulting platform.

Ensuring application reliability and quality through comprehensive UI and API testing.

Integrating automation testing into the CI/CD pipeline to streamline releases and improve efficiency.

Let’s discuss your use cases

Contact Sales

Similar Use Cases

What Is an AI Maturity Model?

A maturity model is a framework used to assess how well your organization uses a

AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

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Solution

Agile Collaboration and Automation Framework Development: Collaborated closely with the development team in an agile environment to create test cases and architect a selenium-python-based UI automation framework and a pyTest-based API automation framework.

Advanced Testing with aiTest and CI/CD Integration: Utilized aiTest for executing automated tests across various devices and browsers, integrated with CI/CD pipelines to ensure consistent testing across QA, pre-prod, and prod environments, and validated API quality using Postman.

Real-Time Communication and Iteration Demos: Provided real-time updates on test execution and analytics via Slack and email, and conducted end-of-iteration demos to showcase automation progress and results.

Impact

Email Optimization

Modern App Development with Automation Integration: Successfully built a modern application supporting both mobile and web platforms, integrating an automation suite into the CI/CD pipeline for consistent and reliable testing.

Productivity Boost

Robust Testing Frameworks: Developed a selenium-python-based UI automation framework and a pyTest framework for API automation, ensuring comprehensive and dependable test coverage.

Scalable Infrastructure

Cross-Platform Testing and API Validation: Leveraged aiTest for automated testing across multiple devices and browsers, and integrated Postman for API quality validation and scalable testing.

Customer Testimonials

Applied AI Consulting has been instrumental in transforming our development and deployment processes. Their innovative approach to integrating automation into our CI/CD pipeline has allowed us to scale efficiently while maintaining top-tier application reliability. The cost savings and operational efficiency gains we've experienced have been profound, enabling us to focus more on strategic growth. Their ability to seamlessly blend technical expertise with a deep understanding of our business needs has made them an invaluable partner.
VP of Engineering

Boosting Healthcare Application Quality with Advanced QA Automation by Applied AI Consulting

Tue, 20 Aug 2024 15:40:35 +0000

Boosting Healthcare Application Quality with Advanced QA Automation

Company Overview

A leading health tech platform for the discovery, evidence generation, and clinical delivery for precision medicine. They help doctors and drug hunters make better decisions about providing the right therapy to the right patients at the right time. Over the past 10+ years, Velsera has developed industry-leading clinical software, knowledge, and perspectives on genetic diseases, including oncology, rare, and hereditary diseases. Their customer base includes some of the largest and most prestigious biopharma/biotech companies, government agencies, non-profits, clinical institutions, AMCs, diagnostic lab groups, and partnerships with OEM lab instrument providers and diagnostic assay developers.

Issue

Automation of over 1000 test cases across various sub-products, features, and modules to ensure efficient and consistent testing.

Need for a reliable and maintainable testing framework that could support the complexity and scale of the test cases.

Requirement of seamless integration with CI/CD pipeline, enabling automated testing during nightly builds.

Let’s discuss your use cases

Contact Sales

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AAIC + Nisum Partner to Accelerate Enterprise Cloud Transformation with Agentic AI and AWS Innovation

Applied AI Consulting is proud to announce a strategic partnership with Nisum, aimed at delivering

Solution

Selected BDD Framework: Utilized Serenity for UI automation and Karate for API automation, leveraging BDD principles to enhance clarity and collaboration.

Successful Implementation: Automated the required test cases within the specified timelines, ensuring alignment with project goals.

CI/CD Integration: Integrated the automated framework with the CI/CD pipeline, enabling faster and more reliable software delivery.

Impact

Reduced Testing Cycle Time

Automation reduced testing cycle time by 50%, accelerating time-to-market for new features.

Improved Application Quality

Early detection of critical issues and increased test coverage led to fewer production issues and higher application quality.

Enhanced Customer Satisfaction

The integration of high-quality automation scripts into the CI/CD pipeline boosted customer satisfaction and retention.

Customer Testimonials

Applied AI Consulting’s expertise in building custom AI solutions with ML and NLP, along with their scalable AWS implementation, significantly enhanced our product’s performance. Their innovative approach and commitment to quality have driven tangible improvements, greatly benefiting our customers.
CTO 7Targets.ai

Boosting Marketing Campaigns with AI: Enhancing Deployment Pipelines for a Leading AI Powered Recommendation Engine

Tue, 20 Aug 2024 15:23:08 +0000

Boosting Marketing Campaigns with AI: Enhancing Deployment Pipelines for a Leading AI Powered Recommendation Engine

Enhanced release speed, automated processes, scaled performance, and improved issue resolution.

Company Overview

A leading product in AIdriven marketing solutions, this product provides innovative tools to help marketers plan campaign content and generate marketing collateral based on campaign keywords. The company’s product, Marxeed, leverages Generative AI to deliver personalized recommendations and automate content creation, significantly enhancing marketing efficiency and effectiveness.

Issue

Ensuring the deployment of new features without disrupting ongoing operations.

Improving the maturity of deployment pipelines to support frequent and reliable releases.

Maintaining high performance and scalability to handle increasing user demand.

Automating the testing and deployment processes to reduce manual intervention and errors.

Let’s discuss your use cases

Contact Sales

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What Is an AI Maturity Model?

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Solution

Implemented advanced CI/CD pipelinesusing Jenkins and AWS CodePipeline for automated build, test, and deployment processes, with automated testing frameworks like Selenium and JUnit to ensure high-quality releases.

Utilized AWS Elastic Beanstalkfor scalable application deployment and management, complemented by comprehensive monitoring and logging with AWS CloudWatch and the ELK Stack for real-time visibility and issue resolution.

Conducted regular training sessions for development and operations teams to streamline the deployment process and enforce best practices.

Impact

Increased Release Frequency

Boosted feature release rate by 46%, enabling faster delivery of new capabilities.

Enhanced Deployment Efficiency

Achieved 60% reduction in manual errors and deployment times through high automation.

Improved System Performance

Handled 35% more user load seamlessly and reduced issue resolution time by 40% with enhanced monitoring and logging.

Customer Testimonials

Partnering with Applied AI Consulting was a game-changer for us. Their expertise in automating our deployment pipelines and improving scalability has drastically reduced our time-to-market. The seamless integration of advanced CI/CD processes has not only enhanced our operational efficiency but also ensured that our platform can effortlessly handle increased user demand.
Sanju, Product Owner Marxeed

Quality Automation and Testing | Applied AI Consulting

Transforming QA Efficiency: Achieving 80% Regression Time Reduction through Automation

Transforming QA Efficiency: Achieving 80% Regression Time Reduction through Automation

Company Overview

Challenges

Dependency on Manual Testing

Incomplete Automation Framework

Framework Instability & Resource Strain

Coordination Challenges

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Operations Conducted

Strategic Approach

Positive Influence

Long-term Scalability

Key Takeaways

Customer Testimonials

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Revolutionizing QA Testing: Reducing Regression Time by 80% Through Advanced Automation

Revolutionizing QA Testing: Reducing Regression Time by 80% Through Advanced Automation

Company Overview

Issue

Actions Taken

Automated Testing with Selenium and Cucumber

Jenkins & GitHub Integration

Performance Testing & Failure Resolution

Solution

Reduced Regression Test Time

Improved Testing Reliability

Business Value of the Outcome

Value Stream

Impact

Increased Efficiency

Enhanced Application Stability

Improved Client Satisfaction

Customer Testimonials

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Enhancing System Scalability and User Experience: A Performance Testing Case Study

Enhancing System Scalability and User Experience: A Performance Testing Case Study

Company Overview

Issue

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Actions Taken

Solution

Impact

Scalability

Optimized User Experience

Informed Decision-Making

Customer Testimonials

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Quality, Application Performance: How to Enhanced Scalability and Reliability Through Comprehensive Load Testing

Quality, Application Performance: How to Enhanced Scalability and Reliability Through Comprehensive Load Testing

Company Overview

Issue

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Actions Taken

Solution

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Quality – Performance and Reliability: How to Leveraged Automation Testing to Handle 30,000 Concurrent Users

Quality - Performance and Reliability: How to Leveraged Automation Testing to Handle 30,000 Concurrent Users

Company Overview

Issue

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Actions Taken

Solution

Impact

Enhanced Scalability

Cost Savings

Improved Reliability

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Enhancing Deployment Success with Python Selenium Automation for a Leading Content Marketing Platform

Enhancing Deployment Success with Python Selenium Automation for a Leading Content Marketing Platform

Company Overview

Issue

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Solution

Impact

Increase in Deployment Success

Reduction in Manual Testing

Building a Comprehensive Online Consulting Platform with Payment Integration for a Leading Start Up