#@aitesting

[edutech-brijesh]

Emerging trends in software testing include AI-driven testing, shift-left testing for early defect detection, and increased adoption of automation and DevOps practices.

[gqattech]

Transforming Software Testing with AI: Discover GQAT Tech’s AI Testing Services

Software problems like bugs, missed deadlines, and poor user experiences are not acceptable in today's digital economy. GQAT Tech is disrupting Quality Assurance itself with an awesome suite of the latest AI-enabled testing services that will allow you to make your Agile and DevOps process intelligent, automated, and fast.

👉 Visit: GQAT Tech – AI Testing Services

Why AI in Software Testing?

Conventional testing approaches no longer suffice for the complexities of contemporary applications. Artificial Intelligence provides smarter, more predictive, and autonomous testing solutions.

Here’s how GQAT Tech uses AI to elevate software testing:

Key Features of GQAT Tech’s AI Testing Services

1. Test Automation with AI

Our automation frameworks use machine learning to create, maintain, and execute the test cases, which greatly minimizes human intervention. If we can minimize the three phases of creating, maintaining, and executing test cases with minimal human intervention, we can achieve faster releases and fewer defects.

2. Intelligent Test Case Generators

The AI models will also create test cases to maximise coverage, like historical data, user behaviour patterns, and known defects.

3. Defect Prediction

We are using predictive AI algorithms to identify and forecast defects before they affect the users. This takes the testing phases ahead, reducing downtime and increasing the quality of the software.

4. Natural Language QA

Our Application uses NLP to turn the business requirements and user stories into automated test scripts, simplifying the whole QA process.

5. Continuous AI/ML Model Testing

AI testing is not just for regular applications; we also test the AI models themselves, including bias testing, performance drift modelling, and prediction validation.

Benefits of Choosing GQAT Tech

Smarter Testing:

AI will adjust and optimize the QA Process dynamically in real-time.

Faster Time-to-Market:

Automated cycles mean releases come quicker instead of sacrificing quality.

Reduced Costs:

Say goodbye to manual errors and wasted testing effort.

Real-Time Insights:

AI dashboards allow insights that guide decision making and actionability.

Self-Healing Scripts:

Our tooling can recognize UI changes and self-correct broken test cases.

Application Examples by Industry

AI Testing Services offered by GQAT Tech cover many different industries:

Finance: Verify that your banking applications are safe from security threats and bugs!

Health: Verify that your systems are legitimate for sensitive patient data management

E-Commerce: create an engaging customer experience

SaaS products: ensure you get the right experience on your platform, no matter how it runs and updates

Why Partner with GQAT Tech?

At GQAT Tech, we don't just automate; we transform your QA Strategy intelligently with our end-to-end AI testing solutions to increase test accuracy and customer satisfaction. 

“With GQAT Tech, you’re not just testing — you’re evolving.”

[capitalnumbers]

What Is AI in Software Testing? Here's Why It Matters

AI in software testing uses smart technologies like machine learning and data analysis to make testing faster, easier, and more accurate. Instead of doing everything by hand, AI can automatically create and run tests, find bugs early, and even predict problems before they happen. It helps reduce errors, saves time, and cuts down on costs. 

AI testing tools are useful in many areas like performance, security, usability, and even ethical testing. They learn from past tests, adapt to changes in the software, and improve over time. Unlike manual testing, which is slower and can miss issues, AI works faster and covers more ground. But AI won’t replace testers—it will support them by handling routine tasks so they can focus on complex issues. Businesses using AI in testing can launch better products faster, with fewer bugs and a better user experience. AI is the future of smart, efficient software testing.

[jacelynsia]

The role of QA engineers is evolving rapidly—are you keeping up? 🚀 As we step into 2025, new technologies, AI-driven testing, and automation are redefining software quality assurance. From coding expertise to soft skills like critical thinking, discover the must-have skills to stay ahead in this dynamic field. Whether you're an aspiring QA professional or a seasoned expert, this guide will help you master the future of software testing.

[sudarshannarwade]

How to Use AI Tools for Manual Testing: A Beginner’s Guide to Smart Testing

If you have experience with software testing, you are aware of how important it is to make sure the product you are testing functions flawlessly before it is delivered to the customer. Quality assurance has traditionally been achieved by manual testing, but as technology advances, artificial intelligence (AI) techniques are starting to gain traction in this area. read more

[ianmccloudofficial]

Short AI Test

In this video, I experimented with AI-generated visuals. I entered the first lines of my song lyrics into the input field, and the AI automatically generated images based on them.

I then combined these images into a short video and added my song to complete the atmosphere.

Here’s how it turned out – let me know what you think of the AI’s interpretation!

[kani-2br]

Artificial intelligence in testing drives precision, speed, and adaptability, allowing teams to uncover issues faster while ensuring higher-quality software. AI can learn from past data, predict outcomes, and continuously improve testing strategies, making it a game-changer in modern software development.

[brewteams]

How to Start Building AI Software Without Getting Overwhelmed

Artificial Intelligence (AI) is transforming industries, driving automation, enhancing productivity, and making businesses more competitive. From personalized recommendations to predictive maintenance, AI technologies offer numerous benefits. However, many small and medium-sized enterprises (SMBs) often perceive building AI software as an expensive endeavor, only achievable by large corporations. The reality is that with the right approach and planning, you can make AI software on a budget and still harness the power of this revolutionary technology.

In this blog, we will discuss how to build AI software affordably, the role of custom software development services in UAE, and how to strategically create a solution that aligns with your business goals. We’ll also explore critical aspects like using AI in software testing, understanding AI software costs, and how AI differs from other software.

1. Understanding AI Software Development

Before diving into the step-by-step guide on how to build AI software on a budget, it’s essential to understand what AI software is and how it differs from traditional software.

How Is AI Software Different from Other Software?

Traditional software follows predefined rules, executing tasks based on algorithms written by developers. AI software, on the other hand, uses data to “learn” and adapt over time. Instead of following strict rules, AI systems use machine learning (ML) models and neural networks to process and analyze data, improving their performance based on patterns and trends.

For example, a traditional inventory management system will track stock based on programmed thresholds, while an AI-driven system will forecast demand, optimize inventory levels, and predict future trends based on historical data.

This difference in operation fundamentally changes the way AI software is developed. While traditional software development involves coding based on specific user inputs, AI software relies heavily on data collection, model training, and ongoing optimization.

Now that we have a basic understanding of AI, let’s explore how to build AI software, even with budget constraints.

2. How to Build AI Software on a Budget: Step-by-Step Guide

a. Identify a Business Problem AI Can Solve

The first step in building AI software is identifying a specific problem in your business that AI can address. This could be anything from automating customer service to improving inventory management, streamlining operations, or optimizing marketing efforts.

Start by asking yourself:

What manual processes can AI automate?

How can AI enhance decision-making within your business?

Are there areas where data can be leveraged to improve outcomes?

For example, AI can help automate repetitive tasks such as sorting customer emails, processing invoices, or providing product recommendations based on past purchase behavior.

Once you identify the problem, it’s easier to focus on building a solution with a clear goal in mind, helping you save costs on unnecessary development efforts.

b. Leverage Pre-Built AI Tools and Platforms

One of the most cost-effective ways to start building AI software is to leverage pre-built AI tools and platforms. Instead of building AI models from scratch, which can be costly and time-consuming, use readily available AI tools that allow you to customize them for your needs.

Popular AI platforms such as Google Cloud AI, IBM Watson, and Microsoft Azure offer a range of pre-trained models and APIs that can be integrated into your software. These platforms provide AI capabilities like natural language processing (NLP), image recognition, and sentiment analysis without requiring extensive knowledge of data science or machine learning.

By using these tools, you can quickly and affordably add AI features to your software while focusing your resources on customizing the software to suit your business needs.

c. Partner with a Custom Software Development Company

Partnering with a custom software development company can save you both time and money when building AI software. Instead of hiring an in-house development team, which can be costly and require ongoing salaries and benefits, outsourcing your project to a company that specializes in custom software development services allows you to tap into expertise on a project-by-project basis.

When working with a custom software development partner, make sure they have experience in AI and machine learning. This ensures that they can help you design and develop a solution that meets your goals while staying within your budget. The company will handle all aspects of the development process, from model selection to software integration, freeing you to focus on running your business.

d. Start Small with a Minimum Viable Product (MVP)

Building an MVP is a great strategy to stay on budget when developing AI software. Instead of trying to build a fully-featured AI solution from the outset, focus on creating a minimum viable product—a version of the software with only the essential AI features necessary to solve your identified business problem.

For example, if you want to use AI to improve customer support, start by implementing a basic chatbot that can answer frequently asked questions. As you gather user feedback and data, you can gradually enhance the chatbot with more advanced AI features, such as sentiment analysis or personalized responses.

Starting with an MVP allows you to test your solution in the real world, gather valuable feedback, and make improvements—all while keeping development costs low.

e. Use Open-Source AI Frameworks

Another way to reduce the cost of building AI software is to use open-source AI frameworks and libraries. Many powerful machine learning libraries, such as TensorFlow, PyTorch, and Scikit-learn, are open-source and free to use. These libraries offer robust tools and resources for training AI models, processing data, and deploying AI solutions.

By leveraging open-source frameworks, you can avoid the licensing fees and costs associated with proprietary AI software, making it easier to build AI solutions on a budget. Additionally, the active open-source community provides a wealth of resources, tutorials, and support, making it easier for your development team to overcome challenges without incurring additional costs.

f. Consider Cloud AI Services

Cloud-based AI services are another budget-friendly option for building AI software. Instead of investing in expensive hardware to train and deploy AI models, cloud platforms like AWS, Microsoft Azure, and Google Cloud provide scalable, pay-as-you-go solutions.

With cloud AI services, you only pay for the computing power and storage you use, helping you control costs. These platforms also offer pre-built AI models and tools that can be customized to meet your business needs, reducing the complexity and cost of development.

3. How to Use AI in Software Testing

AI can significantly enhance the software testing process by automating repetitive tasks, identifying patterns in large datasets, and improving test accuracy. In traditional testing methods, developers manually write test cases and execute them to ensure software quality. However, AI-driven testing tools can automatically generate and execute test cases based on historical data, significantly reducing the time and effort required.

AI can be used in:

Regression Testing: AI can automatically retest software after updates, ensuring that new code doesn’t break existing functionality.

Bug Detection: AI algorithms can analyze code to detect bugs and vulnerabilities, often before they impact the user experience.

Test Optimization: AI can predict which test cases are most likely to fail, allowing teams to prioritize them and optimize the testing process.

By using AI in software testing, businesses can reduce the time to market, minimize human error, and lower testing costs—all while ensuring high-quality software.

4. How Much Does AI Software Cost?

The cost of developing AI software can vary widely depending on several factors, such as the complexity of the solution, the amount of data required, and the level of customization needed. A simple AI chatbot, for instance, may cost between $10,000 to $50,000 to develop, while more complex AI solutions like predictive analytics systems or image recognition platforms can range from $100,000 to $500,000 or more.

Factors that influence the cost of AI software development include:

Data Collection: AI software requires large datasets for training. If you need to collect or purchase data, this can add to the overall cost.

Model Complexity: More complex AI models, such as deep learning models, require significant computational resources, which can increase development costs.

Custom Features: Adding unique or custom AI features will also raise costs compared to using pre-built models and solutions.

To keep costs under control, focus on building an MVP with essential features and scaling as needed. Additionally, working with a custom software development company that specializes in AI can help you optimize costs while delivering a solution that meets your business needs.

5. The Role of Custom Software Development Services in AI Projects

Custom software development services play a critical role in AI projects, particularly when it comes to tailoring the software to meet specific business goals. Off-the-shelf AI solutions may not address your unique needs, and custom development allows you to create software that is optimized for your operations, workflows, and customer base.

A custom software development company can:

Help you define the problem and scope of the AI solution.

Identify the best machine learning models and AI algorithms for your project.

Customize pre-built AI tools or develop proprietary AI software.

Ensure seamless integration with existing systems, such as ERP, CRM, or other enterprise solutions.

Custom development ensures that the AI solution is designed specifically for your business, helping you achieve higher ROI and competitive advantage.

6. The Future of AI in Custom Software Development

AI is not just transforming the way software is used but also how it is developed. Increasingly, AI is being integrated into the software development process itself, making it faster and more efficient. From writing code snippets to testing, AI can assist developers in creating better software with fewer errors.

For example, AI-driven development tools can automatically generate code based on high-level specifications, reducing the amount of manual coding required. This makes the development process faster and more cost-effective, especially for SMBs looking to create customized software on a budget.

Conclusion

Building AI software on a budget is possible and achievable with the right approach. By leveraging pre-built AI platforms, using open-source frameworks, working with a custom software development company, and starting with an MVP, you can create a cost-effective solution tailored to your business needs. AI offers transformative capabilities, and with strategic planning, businesses of all sizes can benefit from this cutting-edge technology.

Whether you're using AI in software testing, enhancing customer experiences, or optimizing operations, the future of AI in business is bright. Take the first step today by identifying the problem you want AI to solve and finding a development partner who can help you build a solution without breaking the bank. To read more about how to build an app like dubainow step by step guide

[aitest-tools]

How a Unified QA Platform Can Streamline Your Software Testing Process

A unified QA platform is a software solution that integrates various testing tools

In today's fast-paced software development landscape, delivering high-quality releases quickly is crucial for success.  However, traditional testing methods can be time-consuming and expensive. This is where a unified QA platform can be a game-changer.

A unified QA platform is a software solution that integrates various testing tools and functionalities into a single, centralized platform. This eliminates the need to manage multiple disparate tools and streamlines the entire testing process.

Here are some of the key benefits of using a unified QA platform for your software testing needs:

Improved Efficiency:  A unified platform automates many manual testing tasks, freeing up your team's time to focus on more strategic initiatives.

Enhanced Quality: By providing a comprehensive overview of your testing process, a unified platform helps you identify and fix bugs early in the development cycle.

Reduced Costs: By eliminating the need for multiple tools and subscriptions, a unified platform can help you save money on your software testing budget.

Faster Releases: With streamlined testing processes and automated tasks, a unified platform can help you get your software to market faster.

How aiTest can be your Unified QA Platform?

aiTest is a powerful AI-powered testing platform that can serve as your one-stop shop for all your software testing needs. aiTest offers a variety of features that can help you improve the quality of your software releases, including:

Cross-device testing: aiTest can automate tests across a wide range of devices, ensuring that your software works flawlessly on all platforms.

Synthetic data generation: aiTest can generate synthetic data for your machine learning models, helping you train them more effectively.

Integration with existing tools: aiTest integrates seamlessly with your existing development and testing tools, so you don't have to disrupt your current workflow.

Reporting and analytics: aiTest provides comprehensive reporting and analytics that give you valuable insights into your testing process.

https://app.aitest.qualityx.io/auth/signup

By using aiTest as your unified QA platform, you can experience the many benefits outlined above and streamline your software testing process for improved efficiency, quality, and speed.

[webomates]

Strengthening National Security: The Role of AI Testing in Defense Technology

The fusion of human ingenuity and AI

Gone are the days when you could only rely on traditional methods for safeguarding nations. Today’s defense forces carry out challenging and intricate tasks under erratic and dynamic conditions resulting in an urgent need for modern development and testing strategies.

To succeed, the defense needs to build human intelligence which is aided, enhanced, and augmented with AI and ML capabilities. AI can enhance the testing and quality assurance (QA) processes to ensure improved reliability, precision, and security of crucial defense operations.

Let’s explore the value of AI testing for defense and understand why a strong QA plan is necessary for more intelligent defense solutions.

A Quick Look at the Failures in Defense Due to Lack of Quality Testing

There are numerous examples of potential consequences of insufficient application testing in the U.S. military.

All these errors could have been avoided if the systems were properly tested and validated. According to the Artificial Intelligence in Military Market report, AI in the military market is estimated to be USD 9.2 billion in 2023 and is projected to reach USD 38.8 billion by 2028, at a CAGR of 33.3%.

Priority Outcomes through AI

How can testing solutions help defense? Our objectives and priority outcomes are to:

Unleash defense potential with the power of AI

Through the adoption of AI-enabled testing, our Armed Forces can modernize and rapidly transition into an agile and intelligent force.

Surveillance and threat monitoring

Defense forces capture massive amounts of surveillance data and confidential intelligence from a variety of sources and IoT-connected equipment, such as satellites, drones, radars, and cyberspace. By integrating IoT automated testing into such surveillance and threat monitoring systems, defense forces can validate the reliability of these systems, identify any patterns and monitor potential threats. This allows for effective and proactive defense tactics and increased threat response capabilities.

Enhancing Defense Communications

The defense sector relies heavily on effective communication for successful mission execution, coordination among forces, and ensuring real-time situational awareness.

Testing an ecosystem of intelligently connected devices poses significant challenges.

Functional Testing, which includes Performance testing, Cross-browser testing, and cross-device testing allows the defense systems to undergo extensive testing, minimizing the risk of catastrophic failures during mission-critical operations.

For functional and Usability testing, Webomates has an IoT lab setup for intensive testing of the functionality, usability, accessibility of heterogeneous devices, and networks of these IoT devices.

Accelerating Application Efficiency

Time is of the essence in the defense sector. AI-powered Intelligent Automation Testing solutions will empower the entire force since they will reduce redundant workloads. Defense forces can deploy new systems and updates faster, and also ensure timely response and adaptation to new threats and challenges.

Shift Left Testing speeds up software releases by testing frequently and early in the development process. This method finds issues faster and reduces unexpected outcomes at the end of development.

Mitigating Cybersecurity Risks

One of the critical defense applications for AI technology is cybersecurity, as these attacks can lead to the loss of highly sensitive and confidential data. By leveraging AI testing, defense forces can strengthen their cybersecurity and protect their assets, ensuring that sensitive data is secure and the organization is not compromised

You can take the help of Webomates’ penetration testing, Security testing, Exploratory Testing, and Performance Testing and prevent such cyber attacks.

Strategic Decision Making

Decision making especially in high-stress situations is difficult. And defense forces rely on systems that use AI and ML algorithms to analyze historical and real-time information and interpret data.

These systems need to undergo extensive testing to be able to evaluate risks and help the forces make informed decisions.

Optimizing Resource Allocation

The defense sector works with the motto — ‘Do more with less’ as it operates under strict timelines along with budgetary constraints and must make optimal use of limited resources.

Depending on the requirements of the application, Regression testing along with Exploratory testing can be done on various scales. By pinpointing bottlenecks and highlighting potential improvement areas, they offer valuable test insights into system performance. As a result, defense organizations can optimize their operations, reduce costs, and ensure the most efficient use of resources.

Preventative maintenance of warfare systems

With AI-powered testing techniques, defense forces can switch from reactive to proactive maintenance strategies.

AI testing techniques like defect prediction and self-healing testing can be used by warfare systems including weapons, sensors, navigation, aviation support, and surveillance to identify deviations from expected behavior and take immediate remedial actions. This proactive approach enables teams to handle problems in advance, which reduces downtime and helps them avoid costly consequences.

Secure Software Development and Testing

By automating code validation, deployment validation, and test execution, AI testing can decrease manual effort and improve system resilience as a whole. Continuous testing is an integral part of the CI/CD pipeline, that can be integrated into the defense application’s development lifecycle. Combined with Shift Left Testing, it ensures that the functionality, performance, and security of warfare systems are continuously validated.

Success Story

With our exemplary work with the esteemed US Air Force, we have demonstrated our ability to help organizations achieve scalability and agility while overcoming the typical traditional testing bottlenecks. Webomates has successfully completed SBIR Phase 1 and Phase 2 with the US Airforce.

Webomates’ Testing as a Service (TaaS) — also known as On-Demand testing service — helps you get clear visibility into your testing data, outcomes, and valuable insights by combining applications and data into a single platform.

We work with unwavering dedication to understand your unique needs and provide customized solutions to ensure the success of your application. Take a look at this animation and know the three easy steps you can take to AI automate your application.

To find out more about what Webomates Intelligent Testing services can do for your business, get In touch with us today.

[gqattech]

http://www.gqattech.com/

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https://x.com/GQATTECH

[avisys]

Emerging Technologies in App Testing for Telcos: What to Expect in 2024

The future of App Testing in Telecom is here! AI, ML, RPA, IoT, Blockchain, and the rise of DevOps and Agile testing are transforming the testing game for telcos worldwide.

Read our latest blog post to learn more about what to expect in 2024 and beyond: https://www.avisysservices.com/blog/emerging-technologies-in-app-testing-for-telcos-what-to-expect-in-2024/

[jacelynsia]

5 Ways AI Is Revolutionizing Software Testing—Are You Keeping Up?

AI is transforming software testing, making it faster, smarter, and more reliable. But how exactly? From intelligent test automation to predictive defect analysis, discover five game-changing ways AI is reshaping quality assurance. Are you ready to embrace the future of testing?

[odiware]

Step into the World of Software Investigation: odiware - Your Trusted Testing Detectives.💻

Know how Odiware can transform your testing process. 👇

📌 Check it out- https://www.odiware.com/it-services/software-testing/

📲 Contact us at: https://www.odiware.com/contact-us/

For Regular Updates: 👇 ➤ Facebook: https://lnkd.in/djeWgSHq ➤ LinkedIn: https://lnkd.in/dKUyHsxq ➤ Twitter: https://lnkd.in/g2HePPk4 ➤ YouTube: https://lnkd.in/dbk_aA6R

[thekfams]

A.I Scanned Our Noses..You Won’t Believe The Results👀🌍🤯 #shorts Think AI can’t read your noses? Think again! 👀🤖 We took on the latest viral TikTok challenge and scanned our noses using AI—and the results were WILD. From shockingly inaccurate readings to hilarious family reactions, this video blends tech, fun. Whether you’re into AI trends, family fun, or just love quirky internet experiments, you’re about to be entertained and amazed. Hit play and see what your eyes might be hiding! #AITest #ViralChallenge #noseScan #FamilyFun #AIChallenge #TikTokTrend #CrazyAIResults #TechMeetsFun #QuirkyContent #AIReacts #FamilyReactions #SurprisingResults #ExploreWithAI #Shorts https://www.youtube.com/shorts/Ni_VjfzSFN4 via The K-FAMS https://www.youtube.com/channel/UC8zRjUNtGKpw8DZ04nWKOTg June 13, 2025 at 05:00AM