algoQA Reviews

My main use case for algoQA is that I have been working with it daily, and one of the most useful features is Test Authoring. I can provide a prompt there and describe the scenario, and it first executes the entire scenario based on the given prompt. After execution, it generates the test scenario for me, which is very helpful because it reduces manual effort and saves time in test case creation.

Another specific scenario where I used algoQA is with the Algo Scrapper feature. Using this feature, I can easily scrape elements from any application without any manual searching for locators or inspecting each element, which makes object identification much easier. I also use the Test Scripting feature, which is very helpful when I need to convert scripts from one language to another framework or language. For example, if I have an existing Java Selenium or C# Selenium framework script and I want to convert it into another language like Python Selenium, I can do that using Test Scripting. This saves a lot of time compared to rewriting the entire script manually.

I have worked in my current company for around the last one year, and I worked on one POC where I used the Python Test Complete framework. Automating the application was quite challenging because I was not able to identify the locators easily and some locators were not working properly. In that situation, the Auto-Heal feature was very helpful. Whenever a locator failed, this feature automatically identified the healed locator, which helped me continue with the locator. The Auto-Heal feature really helped me in that POC, and I use these features in algoQA in my day-to-day work.

algoQA has positively impacted my organization by making the testing and automation process faster, easier, and more efficient. It provides multiple features in a single platform, which helps me handle different automation requirements. Features like Test Authoring help me generate test scenarios based on prompts, reducing manual test case creation efforts. Algo Scrapper makes element identification easier by automatically scraping application elements without manually searching for locators, and Test Scripting helps me convert scripts between different languages and frameworks, saving development time.

Auto-Heal has also been very helpful, especially during challenging automation projects where locators are difficult to identify or frequently fail, as it automatically heals the locators and reduces the effort required to maintain scripts. Overall, I have seen improvements in productivity, reduced manual effort, faster automation development, and better handling of automation challenges. It also helps my team explore and work with different automation technologies more efficiently, and I believe algoQA is adding great value to my organization and helping us improve our overall testing capabilities.

Based on my testing experience, I have observed significant improvements in terms of time saving and efficiency. During testing, I generated a script for around 400 test cases in approximately 5 to 10 seconds using a C# Selenium driver for Python Selenium. Script generation for around 400 test cases was completed within a minute. I have achieved faster test case creation, where auto test case generation took approximately three minutes compared to five minutes for online recording and approximately eight minutes for offline recording. It has also reduced manual effort, as features like Algo Scrapper and Auto-Heal reduce the time spent manually identifying and fixing locators. It also enables faster script conversion, as Test Scripting helps convert existing scripts between languages and frameworks, reducing the effort required to rewrite scripts manually. Overall, these improvements help me save time and improve automation productivity.

The best features algoQA offers that stand out the most for me are Test Authoring, Algo Scrapper, Test Scripting, and Auto-Heal. The Test Authoring feature executes the complete scenario based on my prompt and then generates the test scenario, which saves a lot of manual effort. Algo Scrapper makes element identification easy by scraping application elements without manually searching for locators. Test Scripting helps me convert a script from one language to another framework, such as from Java Selenium to C#. Auto-Heal is especially useful when locators fail, as it automatically heals the locator and makes the automation easier. Overall, these features are very helpful for me, as they save time, reduce manual effort, and help me overcome real-time automation challenges.

Out of those features, I find myself relying on Test Authoring and Auto-Heal the most. During my Python Test Complete POC, I was automating an application where identifying elements and finding the correct locators was quite challenging. Some locators were not working properly, which made automation difficult. At that time, I used the Auto-Heal feature, and it automatically identified and healed the failed locators. This helped me continue with the automation without spending too much time manually finding and updating locators. Similarly, Test Authoring was also very helpful because I can provide a prompt, and it executes the complete scenario and then generates the test scenario for me. These features make automation easier, save time, and reduce manual effort.

algoQA offers multiple automation capabilities in a single platform, which is a big advantage for testers, apart from the features I mentioned. It supports different automation types and frameworks, making it useful for different project requirements. I also appreciate that new features and enhancements are continuously being introduced. Overall, algoQA is a very helpful platform that simplifies my testing process, improves productivity, and reduces manual effort, and I believe there is still a lot of potential to make it even better.

I feel algoQA can be improved further in a few areas including script generation accuracy, locator identification, and execution stability. I believe execution speed and stability can be improved, especially when handling large test suites and hundreds of test cases. Auto-Heal improvements should include enhancements to identify the correct element more accurately and handle different locator failure scenarios. Providing more meaningful error messages and debugging details would help me identify and resolve issues quickly. Overall, I feel that continuous improvements in these areas will make algoQA more reliable, user-friendly, and powerful for automation testing.

One additional area I would like to highlight is integration and scalability. I think algoQA could do better in terms of integration with other tools and technology. Better integration with tools like Jenkins, Git, and other CI/CD platforms would make it easier to include automation in the continuous testing process. I would also like to see improved support for new automation frameworks and technology, along with better handling of complex application scenarios. Another important area is reporting, where more detailed execution reports with clear failure reasons, screenshots, logs, and debugging information would help me analyze issues more quickly.

I would also highlight better end-to-end automation management as an area for improvement. It would be great to have more intelligent debugging, detailed execution insights, and suggestions to fix failures automatically. I would also appreciate improved support for complex application scenarios, better handling of dynamic elements, and more accurate AI-generated test cases and scripts. Another important improvement would be faster execution and better performance when handling large test suites. Apart from these suggestions, I feel algoQA already offers a wide range of powerful features, and continuous improvements and new innovations will make it even more useful for me and help organizations achieve better automation coverage with less manual effort.

Since I joined this company, I have been using algoQA from the start, so it is around one year that I have been using algoQA.

Overall, I would say algoQA is stable and useful in my experience. Most of its features work well and support different automation requirements.

I have worked with algoQA on projects involving large test suites. During my testing, I generated scripts for approximately 400 test cases in a single run. For example, with the C# WebDriver script, it took around approximately 10 seconds for 400 test cases, demonstrating that algoQA can handle a good number of test cases efficiently. However, I feel there is still scope to improve performance and execution stability when handling larger projects with complex test suites. Overall, my experience with its scalability has been positive.

My experience with the algoQA team has been good. Whenever I identify issues or face challenges during testing, I report them to the respective team, and they work on understanding and resolving them. I also receive support whenever I need clarification about features or functionality. I appreciate the team's efforts in addressing reported issues and continuously improving the platform.

I would rate algoQA customer support 10 out of 10 because the team is helpful and responsive whenever I report issues or need clarification.

Before using algoQA, I had experience working with individual automation tools and frameworks such as Selenium WebDriver.

I have seen improvements in terms of time savings and reduced manual effort through my testing and POC activities. For example, during script generation testing, I generated approximately 400 test cases in just approximately 10 seconds using a C# driver with Python Selenium. Generating a script for around 400 test cases took less than a minute. Features like Test Authoring also reduce the time required for manual test case creation, and Algo Scrapper saves time by automatically identifying application elements. Auto-Heal reduces the effort required to manually fix failed locators, even though I do not have exact figures for monetary savings or employee reduction. Based on my experience, algoQA helps me save development and testing time, improve productivity, and complete automation tasks more efficiently.

However, from a user perspective, the platform provides multiple automation capabilities in a single solution, which can help reduce the need for separate tools and manual effort. I believe this can provide good value to organizations depending on their requirements and usage.

However, I am familiar with tools like Selenium and other automation frameworks. What makes algoQA stand out is that it combines multiple automation capabilities into a single platform, including Test Authoring, Algo Scrapper, Test Scripting, and Auto-Heal, which makes the overall automation process easier and more efficient.

I would rate algoQA a 10 out of 10. It offers a wide range of useful automation features that save time, reduce manual effort, and support different automation technologies. There is still some scope for improvement in execution stability, script accuracy, and integration, but overall, it is a very useful platform.

I rate it 10 out of 10 because algoQA provides multiple powerful automation features in a single platform. Features like Test Authoring, Algo Scrapper, Test Scripting, and Auto-Heal solve real-time challenges that I face during automation. I have personally experienced the benefits of these features during my testing and POC activities, as they save time, reduce manual effort, and make different automation tasks much easier. Of course, there is always room for improvement, but the overall capabilities, continuous enhancements, and potential of algoQA make it stand out.

algoQA's AI capabilities should focus on maintaining strong security and governance while making automation easier. From my experience using the platform, I find the AI-powered features to be useful. However, some important areas I would like to highlight are data privacy, secure handling of application data, access control, and transparency in AI-generated test cases and scripts. It would also be helpful to have proper validation of AI-generated outputs to ensure that sensitive project information is protected. Overall, I believe strong governance, data security, and responsible AI usage are important for building trust and making algoQA more reliable for enterprise-level automation.

Overall, algoQA's AI capabilities are quite useful and have been consistent in many scenarios. Features like Test Authoring help generate test scenarios based on prompts, and Algo Scrapper helps identify application elements effectively. However, accuracy can sometimes vary depending on the complexity of the application and the prompt provided, as sometimes AI-generated steps or scripts may require minor manual corrections. Auto-Heal has also been helpful in handling locator failures. The accuracy and reliability are good overall, but there is still scope to improve script generation accuracy, locator identification, and consistency across different frameworks.

algoQA is deployed in a cloud-based environment in my organization. I access the platform through its web interface, and I use different environments such as staging, pre-prod, and production for testing and validation.

My advice would be to definitely explore algoQA if you are looking for a platform to simplify and improve your automation testing process. I recommend starting with features like Test Authoring, Algo Scrapper, Test Scripting, and Auto-Heal as they offer practical benefits and help reduce manual effort. I also recommend exploring the different automation types and frameworks supported by the platform to understand how they can fit your project requirements. Based on my experience, algoQA saves time, improves productivity, and helps solve real-time automation challenges. I suggest trying its features through real project scenarios or a POC before making a decision.

Overall, it is a very useful platform for teams looking to make their automation process faster and more efficient.

My main use case for algoQA is to generate scripts for my application. I already have a test case document, so I use algoQA to generate scripts from it.

Recently, I have been working on an application related to breast cancer. We had a huge set of manual test case documents that we were planning to move to automation, so I fed that whole document to algoQA. algoQA analyzed the whole test case document and gave me scripts. It was a simple process, so I was able to generate all the scripts easily.

algoQA has positively impacted my organization by reducing a lot of effort. Compared to what we were doing before, now that we have moved from manual testing to automation, our team size has been reduced considerably. We are seeing good benefits and good results from algoQA.

Regarding the specific benefits, when I was doing manual testing, I was able to do end-to-end workflow testing for two test cases in one day. Now, using algoQA, I can easily generate scripts, so the effort has been reduced a lot. I can now automate and execute around six to seven test cases in one day.

The best features algoQA offers, in my opinion, include the ability to convert my test case document into readily executable scripts, which is one good feature. It also has a prompting feature. I can type what I need, and based on my prompt, it analyzes the document and gives me scripts.

This prompting feature is mostly suitable for straightforward scenarios, but they recently added one more feature, a Brownfield solution or exploratory testing part. With this feature, wherever there are any test gaps, I can generate scripts using simple interactive prompts. So now it's fixed, I think. It's quite good now, and it's flexible also.

Regarding algoQA's AI capabilities, I think it's safe because it won't actually work on the application. If I want to generate scripts or test cases for any application, first I have to scrape it. Scraping means that I first create a dummy of that application, creating an offline version, and based on that offline version of the application, I get scripts and test cases. So my actual application will not change, and it won't be affected.

Most of their features are not associated with the code, so it's quite safe and secure also. They won't do white-box testing; it's completely black-box testing, so it's safe.

algoQA has been consistent and accurate for me. I get nearly 90%, and more than 95%, accurate results. Rarely, there are some minor gaps, but they can be ignored. So I get good quality, accurate scripts. The scripts generated are completely based on the offline model I have already created, so those scripts are specific to the application that I am working on.

algoQA's onboarding process has to be improved a little bit because if people are very new to algoQA, they will get lost after two or three stages. It would be better if they added good, short videos or GIFs to their onboarding process, which would guide us on how to use algoQA better. But as we got specific training on algoQA, it's quite easy for us to use.

I think the documentation is good, and their customer support is also good, so they don't need any improvements, as far as I know.

The one thing that holds it back from being a 10 is its onboarding process. For people who are new to algoQA, if they add detailed or step-by-step explanations and small GIFs, it will be easier for them to use it.

I have been using algoQA for nearly one to one and a half years.

algoQA has been stable for me; I haven't experienced any downtime or issues.

Using algoQA, I was able to automate quite a few good performance-related test cases as well, so it was good. There is no issue with performance testing either; algoQA supports it.

I reached out to their support team two times for a detailed demo on their AI agents part, and it was good. They were supportive, and it was a good session. The team was also quite engaging, so it was good.

I have not used any other tool for automation. This is the first automation tool that I have used.

In terms of effort, it has significantly reduced the effort and cut a lot of the time that we were putting into testing before. At least half of our effort has been reduced now.

I just heard that, compared to other tools, it was quite a bit cheaper.

The onboarding process was quite okay. For beginners, it can be quite challenging, but for us, it was okay.

My team explored Katalon, but they mentioned it's quite complicated to use and it has a vendor lock-in feature also, so we decided to go with algoQA when comparing it with Katalon.

On a scale of 1 to 10, I give algoQA a nine.

My main use case for algoQA is creating a project for a particular use case and scraping things in an application. I am using the test script prompting, auto-test case generation, and test-to-script conversion features in algoQA, along with execution capabilities.

In my main use case, I am using Scott and an AI agent for recording scenarios and test cases. The AI capabilities are very useful for recording scenarios and support my use cases.

algoQA has impacted my organization positively through a project I completed. The test script agent is particularly valuable. With an existing application, it will agent and recover the script, which is helpful for significant maintenance of the test cases. The outcome is excellent. When it encounters failed locators or missing controls, it first analyzes the situation, then provides an AI-generated expected output. I can maintain that particular report in a dashboard and view the use cases and specific test cases whenever needed.

With algoQA, for 10 test cases, I can complete them within two hours, reducing what would typically be a one-day task. For 20 to 30 test cases, I can complete them within three or four hours. This reduces my manual effort significantly and saves time daily.

The best features algoQA offers in my experience are the auto-test agent, prompting, AI agent, Scott, and script-to-test script conversion. The scraper is also a very useful feature. Without any manual interactions, I can select particular features and controls, scrape the things, and generate test cases and execute the script. I get the report, and I can upload the main report to a dashboard where I can see the controls, features, and the extent of the report.

I am using test-to-script conversion, called Sketch, which naturally adds the language and creates an automation script, reducing manual script effort. The Test Authoring agent generates test scenarios and test cases, improving test coverage and removing manual effort. Coda is a script agent that supports existing scripts already present in the application and supports multiple frameworks. Test Optimize optimizes the test cases that are already created in the project. Failure Analysis helps when test cases fail by showing particular reasons for the failure, such as an incorrect locator, and then healing and executing the test. Test Migrate migrates existing test cases and reduces the framework involvement when moving between automation frameworks. These are the features present in algoQA.

algoQA has already added more AI agents that I am using, so nothing additional needs to be added.

They can maintain more detailed documentation. They are already providing documentation, but if they provide more information about the features, it would be better.

algoQA can improve the AI capabilities further. They have already provided them, but there is room for more AI platform improvements.

I have been using algoQA for the last two years.

algoQA is stable.

In my project, I am using more than 4,000 use cases, which is a large project. I am working on a daily basis without any issues. I am not getting any errors, and it is a very good experience using algoQA.

algoQA provides 24/7 support. When I need their support, I can contact them through email, calls, and chat.

They support me 24/7 and clarify any doubts I have. When I need to connect with them, they can arrange meetings and clarify issues within minutes.

I have been using algoQA for the past two years and have not switched to any other solution.

algoQA is deployed in a private cloud. Whatever cloud is provided to me, they deploy algoQA there, and I use it.

algoQA is a time-saving application, and I am also saving money. If algoQA employees are required, I would hire them.

Regarding pricing, I am using enterprise licenses. If I get any license error, they can provide the resolution within minutes.

I would choose algoQA only.

I would give algoQA a rating of 10 out of 10 because my manual effort is very minimal, and I get more efficient results and output. The features I am using are perfect for my needs. In my team, there is no additional manual effort needed. Regarding algoQA's AI capabilities, the security governance ensures that the information I provide is secured on their side. My use case information will be very secure.

Accuracy is a key strength. I previously worked on a proof of concept in a healthcare department where I configured image validations and X validations. I received very perfect output that matched my expectations, which is why I continue to choose algoQA.

Others can use algoQA without concerns because it uses AI technologies already proven in the market and is very useful and user-friendly. I do not need to provide perfect English, as the AI agent does not require it. I can provide normal English and receive the use cases and test scripts I need.

My main use case for algoQA is to generate scripts. I am working on a project where I'm using algoQA to verify login scenarios and generate scripts related to authentication scenarios.

algoQA comes with a capability that allows me to directly record whatever I'm doing on a particular application, and it will directly give me readily executable scripts.

Regarding my main use case, all I have to do is go to algoQA, type my project details, and it has an extension that will directly launch me to that particular application, where I can type my actions, such as login scenarios, clicking buttons, or typing credentials. Based on my details, it will generate scripts.

algoQA has positively impacted my organization by reducing the time it takes to create a test scenario from one day to nearly 20 minutes.

This time savings has allowed me to work on more scenarios, enabling us to meet deadlines, and our productivity has been significantly boosted.

The best features algoQA offers are that all the scripts it generates are context-aware scripts rather than generic scripts for all use cases. I can generate scripts in whatever technology I want, making it quite faster compared to other LLM tools such as Claude or ChatGPT.

I have generated Java Selenium scripts and Python Appium scripts using algoQA. While I have not fully experienced it, algoQA claims that all the scripts it generates are self-healing and future-proof, and it comes with impact-based analysis, which means if I make any change in the application, the scripts will automatically identify the part of the code where I have made the change.

Regarding algoQA's governance and security, I don't have any issues because it doesn't directly access any code or my application, making it quite safe compared to other LLM tools such as Claude or ChatGPT.

Regarding algoQA's AI capabilities, I find it quite reliable, and the output it gives is context-aware and is not a poor tool compared to others.

One area where algoQA can improve is pricing. They currently have a freemium subscription that is free for a lifetime but comes with limited features, so adding a few more good AI capabilities would be very helpful.

Regarding integration with other tools, I don't have any complaints because algoQA supports integration with all major running frameworks in the industry, including DevOps tools and ALM tools.

The main reason I didn't give it a 10 is because their freemium subscription is an issue I am facing, as using any major AI capabilities requires a paid subscription.

I have been using algoQA for around six months.

In my experience, algoQA is stable.

Regarding algoQA's scalability, it is quite adequate. Whatever scenario I need, it provides high-quality scripts and has a deduplication feature that identifies duplicate test cases based on their similarity.

Customer support for algoQA has been quite adequate. I reached out to them twice for a demo, and they were supportive. On a scale of one to 10, I would rate customer support an eight.

Before using algoQA, I was using Claude for script generation. Once I learned about algoQA, I decided to switch.

My experience with pricing, setup cost, and licensing is that it's quite cheaper. However, I had to purchase the subscription for one feature.

Overall, I would rate algoQA a nine. My advice for others looking to use algoQA is that anyone can use it. It does not require much coding knowledge or testing knowledge, making it simple for people with even basic coding knowledge or testing knowledge to utilize it to its fullest.

My main use case for algoQA is in the medical device field, where I need to log into one application, search for a patient ID, verify the patient ID details are correctly updated, log out, and log into the same application with a different ID to approve patient details. Additionally, I use algoQA for e-commerce and banking, where I conducted a proof of concept in e-commerce by taking a basic use case for logging into the application and verifying products.

algoQA has been particularly helpful for automating medical device applications, as I managed to automate a challenging application called Edensic, which was not well-maintained and frequently changed.

algoQA has positively impacted my organization by making work smoother and increasing efficiency and productivity. Centralized testing allows multiple users to work on the same project, reducing manual efforts and simplifying script maintenance.

When adopting algoQA, we significantly reduced the time taken to create test cases. For example, what used to take two days can now be accomplished in about five minutes.

algoQA helps me with these workflows by saving time and reducing manual errors. This tool has helped me significantly with agents like the test-to-script conversion agent, known as Sketch, which allows me to create test cases. The platform uses an approach of creating test cases from requirements, generating test cases, and executing them. The agents support various scenarios such as creating test cases from Jira tickets, prompts, or Excel data.

algoQA also has a Test Authoring agent called Scout, which analyzes the application and provides positive and negative scenarios. The test scripting agent allows framework migration, which is another useful feature.

The best features algoQA offers in my experience are the Sketch agent, Test Authoring agent, test optimization agent, impact-based testing, and auto-healing capabilities. Additional features include smart ordering, smart report analysis, test health features, deduplication, and Feature File Quality Analyzer.

I find myself using the Test Authoring agent the most because it explores the application I want to test and provides positive and negative scenarios, allowing me to approve or decline them quickly.

algoQA's governance and security are quite strong. The data is very secure, which is especially important since I work in medical devices and cannot share sensitive details.

The accuracy and reliability of algoQA's output are very good, providing correct and measurable results for generated test cases.

algoQA can improve in auto-healing for multiple frameworks, as this is a current issue. Everything else functions well.

I have been using algoQA for the past two months.

algoQA is entirely stable.

algoQA's scalability is excellent. It can handle increased workloads and large projects, as we can automate around 40 test cases in just two days with fewer people.

Customer support is very genuine. I have had good experiences reaching out for information, and they provide necessary support.

I would rate the customer support from seven to eight.

Before algoQA, I used Tosca, which I found complex and difficult to set up, while algoQA is easy to use without requiring any setup or installation.

Our team has seen a return on investment by saving time when creating automation scripts in a fraction of the time, with fewer employees needed to automate around 10 to 20 test cases per day.

Regarding pricing, I am not directly involved but did receive a one-year subscription about two months ago. I have heard from my management that the pricing is reasonable.

Before choosing algoQA, I evaluated other options like Tosca and Mabel.

I would rate algoQA around an eight out of ten because the features are very helpful for my team and organization, but a few improvements are necessary.

My advice for others looking into using algoQA is to definitely choose it because it reduces automation time, requires less manual support, and is useful for business purposes.

My main use case for algoQA involves scraping elements or agents that assist in writing test cases or scenarios easily without manual effort. This enables us to automatically generate or retrieve the XPaths needed for our tasks.

Recently, I used algoQA for a desktop application. First, we selected the application for testing. We then utilized the AI Scraper to identify the application elements, followed by the authoring agent to prepare test cases and scenarios. Next, the test scripting agent generated automation scripts, while the Auto Heal feature addressed any incorrect XPaths by recovering lost locators. Finally, automation execution reports were generated for us.

This is how we have used it, and it is very helpful as it simplifies our daily tasks. Instead of manual work, we can automate processes, and if we have older scripts, the test scripting agent allows us to modify them without manual input. The Auto Heal feature assists if an XPath is incorrect due to UI changes, while the sync up feature generates detailed reports on the requirements or aspects we need to address. Thus, it is very useful for us.

The most significant advantage of algoQA is that it consolidates multiple AI-assist capabilities into one platform, enabling coverage of different automation stages—from test preparation to element identification, script generation, execution, and maintenance. These enhancements positively impact our organization, providing substantial benefits.

Before, we could deliver around 15 test cases in about 20 days. Using algoQA has enabled us to finish the same volume in just 15 days.

I have been using algoQA for a long time, and it is very useful as it helps to reduce the manual effort, minimizes repetitive testing activities, and makes test automation easier for both technical and non-technical users. I have used many features of algoQA, which help me to automate easily, such as the AI Scraper, which helps to identify and capture application elements like text boxes, buttons, dropdown links, and other UI controls. It also reduces the manual efforts involved in identifying locators and creating an object repository. Additionally, I have used the test scripting agent, which generates automatic automation scripts based on the test scenario or requirement provided, helping to reduce coding effort and speed up script development. Another feature I use is the authoring agent, which provides us with end-to-end test case creation from start to finish, simplifying test case preparation and improving test coverage. I also use the Auto Heal feature, which identifies alternative locators when the original locator becomes invalid due to changes in the application URL or UI, aiding in script maintenance and locator recovery. Finally, I have also utilized the sync up feature, which explains the role of the application and how it supports the automation workflow.

I believe the best features of algoQA are its ability to reduce manual efforts, speed up automation, improve test coverage, and minimize maintenance. It supports multiple application types and different automation types, offers centralized reporting, increases productivity, and promotes reusability. These are some of the useful features we have access to.

The centralized reporting feature allows me to add test cases for a specific scenario or project shared with my colleagues, enabling them to contribute their test cases as well. Regarding productivity, multiple users can work simultaneously, reducing the time needed to complete our tasks. This capability helps our team finish our work ahead of deadlines.

I think it is good as it stands now.

I have personally been using algoQA in my workflow for two years.

It has been closer to a year.

algoQA is stable.

algoQA's scalability is notably improved, with many new implementations added. As AI continues to evolve, its capabilities have also seen significant enhancements. It is performing well.

Concerning customer support, it is very good; I receive prompt responses when I require assistance or additional information. Their support meets my expectations, and they help me as much as possible.

I would also rate customer support a 10 out of 10.

I believe there are savings in both money and time, especially regarding time saved.

My experience with pricing, setup costs, and licensing has been straightforward; we found the pricing acceptable and the setup costs reasonable.

I would rate algoQA a perfect 10 out of 10.

I selected 10 out of 10 because it significantly enhances productivity while reducing time and improving efficiency. It provides numerous benefits, such as offering alternate locator options when locators differ and streamlining my daily tasks, which saves time while completing my work. This impressive functionality justifies my highest rating.

In terms of algoQA's AI capabilities, I find it fairly secure as not everyone can access it; there are specific limitations in place regarding who can utilize the AI capabilities.

algoQA simplifies the process of identifying elements and capturing their properties, which can then be leveraged during automation development to yield the expected outputs.

I recommend algoQA as it has proven very useful for us, and I believe it will also benefit others considering its use.

My main use case for algoQA is for image verification and patient data validation.

For example, I am working on a medical device application where whenever a patient registers, they must submit details like Aadhaar or PAN or photos. The use cases involve verifying that patient's data such as their name, Aadhaar number, phone number, and patient profile images verification based on their Aadhaar number and face.

Along with that, we are also working on non-functional use cases, but that is not the main focus, and we have not yet started on those.

The best features of algoQA include the introduction of AI agents, tailored specifically for brownfield solutions.

This feature has significantly improved my workflow by allowing me to automatically fill test gaps and generate executable scripts from manual test cases whenever we make any changes in the application.

Before using algoQA, we spent a lot of time generating test cases, but now it has significantly reduced the time required, and we can generate and automate nearly six to seven test cases per day.

The significant time savings allow us to achieve more coverage, automate even more test cases, and reduce our release cycle significantly.

Regarding improvements, algoQA can enhance its freemium subscription by adding some AI capabilities, as there are minor changes needed.

I have been using algoQA for the last one and a half to two years.

algoQA is quite stable.

algoQA's scalability is impressive, offering high-quality script generation and features like deduplication to streamline execution.

Customer support is quite good; they are highly supportive and available when I reach out for demos.

I rate customer support a 10 because they are really good.

We previously used Cloud for automation but switched to algoQA due to issues with generic scripts and the effort required to explain our application scenarios.

While I am not exactly sure about the financial savings, we have significantly saved time and effort since we can now complete multiple test cases in a single day.

The pricing and setup costs for algoQA are quite economical compared to market competitors, especially with their flexible Enterprise subscription.

Before choosing algoQA, I evaluated other options like Katalon and Testsigma, but their pricing was not suitable for us.

I would rate algoQA a 10 because compared to other tools, they provide an excellent free version.

I chose a 10 rating due to the capabilities of algoQA and its significant value to my organization compared to the cloud services we used before.

I find it quite safe to use algoQA as it keeps all generated data secure in a personal account without sharing it with any external tools.

In terms of accuracy and reliability, algoQA has not produced any wrong test cases thus far, making it highly reliable with context-aware scripts based on our application needs.

My advice for others looking to use algoQA is that no coding knowledge is required, as it is a low-code, no-code tool with advanced features.

I use algoQA mainly for automating login test cases, logout test cases, patient details, and entries details.

First, I use algoQA to scrape all the elements using AlgoScraper, and then I record manual test cases using AlgoScraper, which captures all the elements and downloads a JSON file that I upload into algoQA, and later I create test cases for login.

I sometimes use algoQA to create negative test cases; for example, I created one successful login test case, and I asked the prompt engineering to create multiple test cases, resulting in the creation of multiple test cases for login.

In my opinion, the main feature algoQA offers is the low-code, no-code approach, allowing a user without any experience in automation to work on algoQA.

algoQA has an agent that records online and scrapes elements, along with all features.

The main advantages of algoQA are that maintenance is very easy, I generate test cases very quickly, and I have efficient reports and cloud executions.

algoQA is good so far, without any notable areas for improvement.

I think a free subscription could be increased.

I have been using algoQA for 1.8 years currently.

In my experience, algoQA is stable.

algoQA is highly scalable.

In terms of customer support, algoQA has very good customer support.

On a scale of 1 to 10, I would rate customer support a nine.

I don't have any issues with the pricing, setup cost, and licensing of algoQA.

On a scale of 1 to 10, I would rate algoQA a 10.

I choose 10 because it increases the test cases efficiently and quickly.

I think the governance and security of algoQA are good, particularly the security aspect.

In my experience, algoQA is reliable regarding its AI accuracy and the reliability of its output.

algoQA is deployed in my organization as a private cloud, specifically on-premises cloud.

I would advise others looking into using algoQA that it is the best tool for beginners and allows easy automation.

In the MedTech field, my day-to-day use cases involve logging into the application, creating the patient ID, and verifying whether the patient ID is correct, and after that, verifying their details and handling some other use cases as well.

For example, in a DeepHealth application, after logging in, I have to search for the patient ID, create the dashlet in a dashboard setting, fill in the data, verify it, and finally delete the created dashlet input and log out of the application. This is one of my examples of day-to-day use cases.

Regarding my main use cases, I have agents in algoQA, such as the scripting agent and the authoring agent, although I am not sure of their exact names. Using those agents and AI features, I can easily automate my daily test cases, and I think that within one day, I can automate 10 scenarios using those agents.

In the medical domain, the use cases are very tough, and the integration between one application and another is also required, so with algoQA, I can easily automate those test cases, especially for integration between one application and another. For example, in terms of hybrid, if I want to automate both web and desktop applications, I can integrate them easily, so I find that algoQA is useful and helps us with integration.

Regarding time savings, before algoQA, automating one scenario took around two to three days, but now, using algoQA, I can finish my test cases easily within one or two hours. The efficiency is greatly improved, as it provides quality output and quality use cases.

In terms of bugs, I can easily identify them in production using this tool. algoQA has functionalities such as impact analysis, which analyzes the changes based on our code and assesses which test cases might be impacted during releases. This allows for easier identification of bugs and effective smoke testing, regression testing, and more, while functionalities such as smart analysis and smart AI executions further aid in our testing processes.

The best feature in algoQA is the Test Authoring agent, which explores the application and generates positive, negative, and all the test cases, while also identifying whether I have covered all the test cases according to the requirements. Apart from that, if I have a script in one language, such as Java Selenium, and want to convert it into another language, such as Playwright, I can easily convert it using this agent. Functionalities such as auto-healing are very useful and helpful for my daily tasks.

Currently, I am relying on the Test Authoring agent because it explores the application and provides positive, negative, and all the use cases, making my daily work easier, as I just have to review it to see whether it covers all the steps according to my requirements.

In addition, algoQA includes all the GenAI capabilities and agents. Creating the offline model is very easy using the recorder option along with prompting and the Test Authoring agent. They also provide a manual option for users who prefer it, and the co-pilot guides users to automate correctly. They have extended report and framework support in automation, which makes our work balance more manageable.

They maintain good governance and security, ensuring that even if they capture images of the application, the data is hidden. In our medical domain, we must not share screenshots with vendors, and we have terms and conditions in place to ensure they keep everything confidential and secure, preventing the person automating from seeing any secured data.

The accuracy and reliability of output from algoQA are good. In one day, I can automate around ten scenarios, and the output depends on our prompt, which also remains favorable.

I don't see any areas for improvement as of now. algoQA is good, but they can still add more AI-related features, although there are already many available.

There are many impressive AI features currently available in algoQA, such as auto-healing, smart execution, smart ordering, and smart reporting, and with six AI agents included, it is already quite substantial, so I don't see a need to press for additional AI features at this moment.

I have been using algoQA for the past year. We have a relationship with the algoQA team, so we took the subscription from them, and for the past year, I have been handling algoQA.

We have a private cloud where algoQA deploys its application onto our server.

I would undoubtedly rate algoQA 10 out of 10.

I choose a 10 out of 10 rating because they have more agents and AI features, it is easy to use, and they provide excellent knowledge about the application. They claim no-code and low-code capabilities that allow even those without coding experience in automation to automate test cases easily, making maintenance smooth along with effective test gap coverage and bug identification, which is why I give a perfect score.

My advice for others looking into using algoQA is to go for it, especially for product owners, automation QA leads, or business stakeholders, as it encompasses all the capabilities we regularly use in the automation field and provides great service.