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Forbes
5 days ago
- Business
- Forbes
How Virtual Testing Environments Are Unlocking Enterprise AI Agent Adoption
Olga Megorskaya is Founder & CEO of Toloka AI, a high-quality data partner for all stages of AI development. AI agents are having a moment. From customer service automation to complex workflow orchestration, these systems promise to revolutionize how enterprises operate. Yet despite the hype, actual deployment remains frustratingly limited. The reason? Safety risks are simply too high for most organizations to stomach. Unlike traditional AI models that respond to prompts in isolation, AI agents perform sequences of actions across multiple systems—accessing databases, modifying files, interacting with APIs and making decisions that cascade through entire business processes. When an agent malfunctions in a production environment, the potential consequences include operational disruptions, security breaches, compliance violations and reputational damage. The solution isn't to restrict AI agents—it's to test them properly before deployment. Enter agentic environments: realistic virtual spaces that mirror your actual business operations, allowing you to stress-test agents without risking your real systems. The Enterprise Safety Paradox Here's the challenge enterprise leaders face: AI agents must interact with real tools and data to be effective, but testing them in production environments is unacceptably risky. A customer service agent who accidentally exposes PII, a workflow automation that corrupts financial records or a research assistant who inadvertently violates compliance protocols can cause immediate, tangible damage. Traditional testing approaches fall short because they can't capture the complexity of real enterprise environments. Sandbox testing with dummy data doesn't reveal how agents behave when faced with the messy realities of actual business operations, like incomplete datasets, legacy system quirks or the subtle contextual cues that guide human decision making. This creates a deployment deadlock. Organizations need to see agents perform in realistic conditions to build confidence, but they can't afford the risks of letting unproven agents loose on production systems. What Are Agentic Environments? Agentic environments solve this paradox by creating high-fidelity digital twins of real business operations. These aren't simple testing sandboxes; they're comprehensive virtual organizations, complete with realistic data, workflows and system integrations. Leading organizations are now implementing sophisticated virtual companies that serve as testing grounds for enterprise AI agents. These environments typically include fully functional instances of Google Workspace, Confluence, Salesforce CRM, Jira, GitHub and Slack, along with virtual employees, department structures and ongoing projects. These environments can be customized to match specific industry requirements or integrate proprietary tools, allowing them to safely validate AI agent performance before real-world deployment. The value of this approach has become clear as companies are using these virtual environments to test agents before launch. Realistic environments reveal critical vulnerabilities that would be invisible in traditional testing scenarios—issues that could compromise data security or cause system failures in production. By identifying and addressing these problems in virtual environments, organizations prevent what could be costly deployment failures. To build these virtual environments, data companies are employing real human experts to generate realistic scenarios that reflect the nuanced decision making and complex interactions agents will encounter in actual business operations. The key to success is realism. Rather than testing agents with sanitized, artificial scenarios, these environments present the complexity agents will encounter in production: conflicting information across systems, incomplete data sets, varying user permissions and the kind of edge cases that only emerge in real-world operations. Beyond Basic Testing: Agent-Oriented Benchmarks This focus on realistic testing has driven the development of sophisticated agent-oriented benchmarks. SWE-bench tests coding agents in structured development environments, while TAU-bench evaluates agents in retail and airline scenarios where they must navigate complex, domain-specific rules while interacting with both humans and APIs over extended periods. What makes these benchmarks valuable for enterprise deployment isn't just their technical rigor—it's their emphasis on real-world conditions. Human insight remains essential for creating benchmarks that address customers' unique operational requirements and designing realistic scenarios that reflect actual business complexities. These benchmarks test whether agents can maintain performance across millions of interactions, follow nuanced compliance requirements and handle the kind of ambiguous situations that human workers navigate daily. Enterprise teams are increasingly requesting custom versions of these benchmarks tailored to their specific industries and use cases. The demand signals that disruptive technologies require brand-new testing approaches. Security Implications From a security perspective, agentic environments are essential for identifying potential vulnerabilities before deployment. Agents that can modify files, access databases and interact with external APIs represent significant attack surfaces. Testing in isolated environments allows security teams to observe agent behavior under various conditions, including adversarial scenarios designed to exploit potential weaknesses. These environments also enable red team exercises where security professionals can attempt to manipulate agents into performing unauthorized actions or accessing restricted data. Better to discover these vulnerabilities in a controlled setting than after deployment. The Path Forward Using realistic testing environments enables organizations to build the confidence needed to deploy agents safely and effectively. Companies that establish robust agentic environments now will be positioned to take advantage of future advances while maintaining the safety and reliability their operations demand. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Yahoo
23-07-2025
- Business
- Yahoo
GitLab's Partner Base Expands: Is Growth Thesis Strengthening?
GitLab GTLB is benefiting from strong demand for its DevSecOps platform. Its rich partner network, which includes cloud platforms such as Alphabet's Google Cloud and Amazon's cloud arm, Amazon Web Services (AWS), and Zscaler has been a major growth driver. These platforms are helping it expand its footprint among large enterprise April 2025, GitLab announced the general availability of GitLab Duo with Amazon Q, integrating Amazon Q's AI agents into its DevSecOps platform to accelerate development, modernize legacy code, and streamline security and code reviews. The integration of GitLab's DevSecOps platform with Alphabet's Google Cloud services is enhancing developer productivity by streamlining authentication, boosting application deployment and improving the developer experience. This collaboration between GitLab and Alphabet ensures a more seamless and efficient development a cloud security leader, selected GitLab in a competitive process, forming a partnership. This reinforces GTLB's position in DevSecOps by enhancing security, streamlining workflows and expanding its enterprise expanding clientele and market leadership in the DevSecOps platform category are contributing to its growth prospects. In the first quarter of fiscal 2026, customers with more than $5K of Annual Recurring Revenue (ARR) increased to 10,104, up 13% year over year. Customers with more than $100K of ARR increased to 1,288, up 26% year over year, demonstrating GTLB's ability to attract and retain large enterprise customers. GitLab Suffers From Stiff Competition GitLab operates in a highly competitive environment. It faces stiff competition from Microsoft MSFT, its principal rival in the DevSecOps space. Other competitors include Atlassian TEAM and other DevSecOps platforms that specialize in various stages of the software development has a strong focus on DevSecOps, integrating security into the software development lifecycle. It strengthens its position through the seamless integration of GitHub and Azure DevOps. Microsoft also partners with other companies to provide comprehensive DevSecOps solutions, like Contrast Security. Atlassian is expanding its footprint in the DevSecOps space through its robust suite of tools like Jira, Bitbucket, and Bamboo, which provides a strong foundation for development and DevOps workflows, including CI/CD. Atlassian is actively advancing DevSecOps through partnerships and integrations, notably with the recent addition of security integrations to Jira and its Open DevOps initiative. This includes collaborations with companies like Snyk, Mend, Lacework, Stackhawk, and JFrog to aggregate vulnerability data within Jira, making it easier to prioritize and address security issues within the DevOps workflow. Gitlab's Share Price Performance, Valuation and Estimates GitLab's shares have lost 18.6% year to date against the broader Zacks Computer & Technology sector's return of 10.6%. GitLab Stock's Performance Image Source: Zacks Investment Research GitLab stock is trading at a premium, with a forward 12-month Price/Sales of 7.21X compared with the industry's 5.90X. GTLB has a Value Score of F. GitLab Valuation Image Source: Zacks Investment Research The Zacks Consensus Estimate for second-quarter fiscal 2026 earnings is currently pegged at 16 cents per share, which has remained unchanged over the past 30 days. This indicates a 6.67% increase year over year. GitLab Inc. Price and Consensus GitLab Inc. price-consensus-chart | GitLab Inc. Quote The consensus mark for fiscal 2026 earnings is pegged at 75 cents per share, which has remained unchanged over the past 30 days, suggesting 1.35% year-over-year currently carries a Zacks Rank #3 (Hold). You can see the complete list of today's Zacks #1 Rank (Strong Buy) stocks here. Want the latest recommendations from Zacks Investment Research? Today, you can download 7 Best Stocks for the Next 30 Days. Click to get this free report Microsoft Corporation (MSFT) : Free Stock Analysis Report Atlassian Corporation PLC (TEAM) : Free Stock Analysis Report GitLab Inc. (GTLB) : Free Stock Analysis Report This article originally published on Zacks Investment Research ( Zacks Investment Research Sign in to access your portfolio
Edinburgh Reporter
16-07-2025
- Edinburgh Reporter
Top 4 AI Tools for Software Testing in 2025
The field of software testing is changing fast because of AI. Today, AI tools for software testing help QA teams to automate test creation, improve test coverage, and find defects more quickly than ever before. With things like self-healing test scripts and smart test case generation from AI, these tools save a lot of time. They also cut down on how much manual work and fixing is needed. In this article, you will read about the best AI testing tools 2025 will bring. We talk about what each tool can do, their good and bad sides, and what they cost. If you want to know more about how AI works in testing, have a look at this ai model testing guide. It explains AI ways of testing in detail, and helps people see how things are done with ai and software testing, including how test creation and fixing defects work these days. Whether you are a new company looking for constant testing, or a big one using Selenium, Jenkins CI/CD pipelines, and Jira, you will find a tool that fits you here. We cover the top options for AI test automation and QA testing within the software development process. You can use these on web applications, mobile, API, and even for checking what you see on the screen. Let's look at the best AI tools for software testing. You can use these to make your QA better in 2025 with automation, CI, and more. 1. is a strong tool for test management that uses AI to make test automation simpler. The platform gives QA teams a single place to handle both manual and automated tests. With the help of AI, can write test documentation and even suggest test code. This helps both technical and non-technical team members to work together with ease. You can connect to development tools like Jira, Jenkins, and GitHub, so that it fits well into your Agile process. The platform also works with all big testing frameworks, such as Selenium, Cypress, and Playwright. AI engine works to lower the time you spend keeping tests up to date and to help you get better test coverage. It looks at your test results to find flaky tests and the real reasons why they fail. This makes a great choice if you want AI test automation features in a strong test management tool. If you are working in test automation and want to use the power of AI, is worth looking at. Key Features: AI-Generated Documentation: The platform makes up-to-date documents from test cases by itself. This saves people time because they do not have to write reports by hand. The platform makes up-to-date documents from test cases by itself. This saves people time because they do not have to write reports by hand. Plain-English Test Descriptions: The tool changes tests written in code into simple steps anyone can read. It can also turn these easy steps back into code. This helps people who do not write code take part in the work. The tool changes tests written in code into simple steps anyone can read. It can also turn these easy steps back into code. This helps people who do not write code take part in the work. Code Suggestions: When you tell the AI what you want to test, it will give you some ready-made code to automate the work. When you tell the AI what you want to test, it will give you some ready-made code to automate the work. Intelligent Analytics: There are easy-to-use dashboards that show you things like how much is covered by automation, tests that often fail, or tests that are slow. The AI points out places where there are the most problems. There are easy-to-use dashboards that show you things like how much is covered by automation, tests that often fail, or tests that are slow. The AI points out places where there are the most problems. Jira Integration with AI Validation: Your tests can link with Jira in both directions. The AI checks that each test fits the requirements in Jira and lets you see which test covers what. This way, nothing is missed. Your tests can link with Jira in both directions. The AI checks that each test fits the requirements in Jira and lets you see which test covers what. This way, nothing is missed. Failure Analysis: If any test fails, the AI checks the logs and tells you where the problem may be. This helps you fix things much faster. If any test fails, the AI checks the logs and tells you where the problem may be. This helps you fix things much faster. CI/CD Support: The platform works well with CI tools like GitHub Actions or Jenkins. It keeps tests and reports running all the time and makes the process easy. These features make use of AI, test automation platform automation, and CI to make testing, reporting, and enhancing user experience simpler and quicker for everyone, allowing for robust tests to be conducted efficiently. Pros: Unified Platform: This tool brings both manual and automated test management together in one place. It also has AI features, so QA workflows are easier and more organized. This tool brings both manual and automated test management together in one place. It also has AI features, so QA workflows are easier and more organized. Generative AI Capabilities: The tool can use AI to create documentation and test cases by itself. This means QA engineers do not have to spend so much time on manual work. The tool can use AI to create documentation and test cases by itself. This means QA engineers do not have to spend so much time on manual work. Self-Healing Integrations: It spots when your application changes and helps you freshen up tests on its own. This can lower the amount of maintenance you need to do. It spots when your application changes and helps you freshen up tests on its own. This can lower the amount of maintenance you need to do. Broad Framework Support: It works with many test frameworks like WebDriverIO, Cypress, and Cucumber. This means it is easy to use and fit into any setup. It works with many test frameworks like WebDriverIO, Cypress, and Cucumber. This means it is easy to use and fit into any setup. Real-Time Insights: You get rich data and live charts while running test execution. This helps you find flaky or broken tests faster, so you get better test coverage and higher quality. You get rich data and live charts while running test execution. This helps you find flaky or broken tests faster, so you get better test coverage and higher quality. Collaboration Friendly: AI makes test cases easy to read by giving clear, plain-language descriptions. With this, everyone from BA, QA, Dev, to PM can understand the tests and work together. AI makes test cases easy to read by giving clear, plain-language descriptions. With this, everyone from BA, QA, Dev, to PM can understand the tests and work together. Scalable & Cloud-Based: The tool can handle more tests as you grow. You get features like versioning, branching, and the ability to run parallel tests across several environments. Cons: Relatively New AI Features: Some parts that use ai, like code generation, are still quite new. Teams may need some time to feel good about using them and to learn how to get the most out of these new tools. Some parts that use ai, like code generation, are still quite new. Teams may need some time to feel good about using them and to learn how to get the most out of these new tools. Limited Offline Use: This is a cloud SaaS. You will need internet to use it. The on-premise option is mostly for bigger business plans. Pricing: has a Free plan that lets one user work on a single project at $0. This is a good way to try it out. Paid plans begin with the Professional option at about $30 per month. This plan works well for small teams. Larger groups can find higher plans that go up from there. If you have special needs, there is Enterprise pricing made just for you. A free trial comes with all the paid options. 2. ACCELQ ACCELQ is an AI-powered cloud platform for automation. It helps people do testing without using code. Teams can make, run, and handle tests for web, mobile, API, and desktop in plain English. The platform comes with a self-healing tool. It changes the locators for you when a UI changes. With predictive analytics, it puts tests that have more risk at the top. ACCELQ has labs for different browsers and devices. You can also connect it with Jenkins, Azure DevOps, and Jira. This makes the whole QA process faster and easier with automation and AI. Key Features: Codeless Natural Language Automation: You can make tests in plain English or use a visual designer. This means you do not need to have special skills for test automation. It is easy for anyone to get started with test creation. You can make tests in plain English or use a visual designer. This means you do not need to have special skills for test automation. It is easy for anyone to get started with test creation. Self-Healing Tests: The AI in the tool can update test scripts by itself when something in the UI or app flow changes. You do not need to spend much time fixing your tests. This helps you work faster and worry less about maintenance. The AI in the tool can update test scripts by itself when something in the UI or app flow changes. You do not need to spend much time fixing your tests. This helps you work faster and worry less about maintenance. Dynamic Element Handling: The tool is smart enough to find and track UI parts in real-time on all browsers and devices. This keeps your test automation stable and strong every time you use it. Photo by Christina Morillo: Pros: Codeless & Accessible: You can set up automation here with no code. It works with simple text and in the UI. This is good for people and testers who do not have much programming experience. You can set up automation here with no code. It works with simple text and in the UI. This is good for people and testers who do not have much programming experience. AI-Powered Stability: The smart locators and self-healing make your tests less likely to fail for no reason. They are strong against UI and DOM changes, so you get fewer false test fails. The smart locators and self-healing make your tests less likely to fail for no reason. They are strong against UI and DOM changes, so you get fewer false test fails. Full-Stack Coverage: You use one platform to do everything. This covers web, API, mobile, and desktop automation, also with manual testing. You do not need several tools for all this work. Cons: Premium Pricing: ACCELQ's top features come with a higher price. It is made for big companies, so it may be hard for very small teams or startups to pay for it. ACCELQ's top features come with a higher price. It is made for big companies, so it may be hard for very small teams or startups to pay for it. Initial Setup Learning Curve: You can do test creation without code, but setting up big or complex systems with ACCELQ and making it work for the whole company may take time and help. You can do test creation without code, but setting up big or complex systems with ACCELQ and making it work for the whole company may take time and help. Closed Ecosystem: This is a closed platform. People or teams who like to use open-source tools may feel limited because they do not have full access to change things in the code. Pricing: ACCELQ has different subscription levels that come with no limits on the number of users or tests. You start with a free trial. After that, prices are usually between $300 and $500 each month if you have a small team. For larger companies, the cost can be $3,000 or more every month when you make a big or business-wide setup. 3. Testim Testim is an automation tool that helps you create UI tests faster. Its Smart Locator technology makes tests more stable. At every step, it saves several element details so that small UI updates do not break the script. Testim gives you a way to record tests without code. You can also export tests to Selenium or Playwright. Some other features are scheduling, version control, and running tests in parallel. This helps your team work in an agile way. You spend less time fixing tests. Your web tests stay reliable with Testim, especially when ensuring the functionality of mobile applications. Key Features: AI Smart Locators: When you make tests in Testim, AI helps create strong locators by using things like ID, classes, and the order of the items on the UI. If the app or its ui changes, these locators change on their own. This makes the tests fix themselves so you do not have a lot of false test failures. It helps save time when you work with AI in your tests. When you make tests in Testim, AI helps create strong locators by using things like ID, classes, and the order of the items on the UI. If the app or its ui changes, these locators change on their own. This makes the tests fix themselves so you do not have a lot of false test failures. It helps save time when you work with AI in your tests. Fast Authoring with Recorder: There is a Chrome extension that lets you record the things you do on the ui. After recording, you can change these steps, add your own details, or mix in your own code if you want. This helps you get started building test suites for an app much faster. There is a Chrome extension that lets you record the things you do on the ui. After recording, you can change these steps, add your own details, or mix in your own code if you want. This helps you get started building test suites for an app much faster. Modular Steps & Reuse: You get to keep the steps you use a lot (like 'Login' or 'Add Item to Cart') as parts you can use again and again. This stops you from doing the same work in your app tests and makes things much easier if you have to change something later on with Testim. Pros: Quick Ramp-Up: This traditional tool gives something to both new and skilled automation people. If you are just starting, you can use the codeless options to help you do your best work. If you know code, you can add more features or export your tests as code, allowing for consistent execution, enabling more individuals to play an active role in enhancing the overall testing process, and think about higher value things, ultimately leading to significant cost savings. This way, it works well for both kinds of users, and that is a big benefit. This traditional tool gives something to both new and skilled automation people. If you are just starting, you can use the codeless options to help you do your best work. If you know code, you can add more features or export your tests as code, allowing for consistent execution, enabling more individuals to play an active role in enhancing the overall testing process, and think about higher value things, ultimately leading to significant cost savings. This way, it works well for both kinds of users, and that is a big benefit. Highly Maintainable Tests: The AI tools help you keep your UI tests working with less effort. The locators find what changes on a page, and the self-healing feature fixes small issues on its own. You do not have to spend time fixing tests every time there is a new update. Most teams say they use far less time taking care of tests than when using just Selenium. The AI tools help you keep your UI tests working with less effort. The locators find what changes on a page, and the self-healing feature fixes small issues on its own. You do not have to spend time fixing tests every time there is a new update. Most teams say they use far less time taking care of tests than when using just Selenium. Supports Complex Apps: This is made for groups that need to test more than simple web pages. It handles dynamic apps really well, like single-page apps or web tools with rich UI. You can use it to test things like Salesforce or React apps. These are hard to test with old automation tools because locators for them easily break. This tool makes it easier. Cons: Initial Recording Finesse: Like many other tools, Testim may record a few extra actions. It might also use values in the test that are not flexible, like hard-coded text. You will have to go back and fix or update these first tests. For example, you might need to add checks, change the test data, or adjust inputs so the test works in more than one case. This is normal for testers who use tools like this, but it takes some of your time and you need to know how the tool works. Like many other tools, Testim may record a few extra actions. It might also use values in the test that are not flexible, like hard-coded text. You will have to go back and fix or update these first tests. For example, you might need to add checks, change the test data, or adjust inputs so the test works in more than one case. This is normal for testers who use tools like this, but it takes some of your time and you need to know how the tool works. Image/Visual Assertions Limited: Testim mostly works with the structure of web pages, known as the DOM. There is a way to use Testim to do visual testing if you connect it with Applitools. But, the built-in options in the tool for checking how things look are not strong, so you will need a separate service to do detailed visual checking. Testim mostly works with the structure of web pages, known as the DOM. There is a way to use Testim to do if you connect it with Applitools. But, the built-in options in the tool for checking how things look are not strong, so you will need a separate service to do detailed visual checking. Pricing for High Volume: Testim can feel low-cost or reasonable at first if you run just a few tests. But, if you or your team want to run a lot of tests at the same time, or use the Testim cloud, the price will go up. Big companies that need to run many tests have to pay for enterprise plans, and the price for these plans from Tricentis can be very high. Pricing: Testim has custom pricing to fit your needs. A free plan let you have about 1,000 runs each month, which helps with small projects. Paid plans start at a few hundred dollars per month. If you are with a big company, high-level agreements can cost several thousand dollars a year. These come with unlimited runs, more features, and a special support team. There will be free trials and lower prices for students or schools. 4. Functionize Functionize is an automation platform made for big businesses. The tool lets you write tests in everyday language. It uses deep learning to fix tests by itself and can grow or shrink as your needs change, thanks to the cloud. You can make and keep up web, mobile, API, and database tests with it. When something in your app changes, it updates scripts on its own. The system uses reinforcement learning to find out how your app works and then builds more tests. This helps teams get more done and cover more ground without hiring more people. Key Features: Natural Language Tests: You can make tests in plain English by using a UI. For example, you can say, 'Open the homepage, login with username X, verify account page is displayed.' The tool from Functionize will read what you say and build a test case from it. This helps you work with tests without needing deep know-how of automation. You can make tests in plain English by using a UI. For example, you can say, 'Open the homepage, login with username X, verify account page is displayed.' The tool from Functionize will read what you say and build a test case from it. This helps you work with tests without needing deep know-how of automation. ML-Powered Element Recognition: Functionize uses AI-driven automation to find things like buttons or links in an app. It learns how each part of your UI acts and looks, using a flexible or 'fuzzy' way. So, even if text or position changes a lot, it can still find the right thing. Functionize uses to find things like buttons or links in an app. It learns how each part of your UI acts and looks, using a flexible or 'fuzzy' way. So, even if text or position changes a lot, it can still find the right thing. Self-Healing & Adaptive Tests: If it can't find an element just like before, Functionize's engine will use its model of your app and search the DOM to pick out the most likely new match. This means your tests will not break every time your app changes, which cuts down on test fails. Pros: Highly Autonomous: Functionize tries to cut down how much manual work you do in every part of testing. This includes test creation, running the tests, and keeping them updated. A busy QA team will see that tests can update or even create themselves, so people save a lot of time and get more done. Functionize tries to cut down how much manual work you do in every part of testing. This includes test creation, running the tests, and keeping them updated. A busy QA team will see that tests can update or even create themselves, so people save a lot of time and get more done. Enterprise Integration: This tool works with the top tools, like Jira, Jenkins, GitLab, Slack, and TestRail. It also lets you use SSO and set roles for access. These features help large companies work easier together. This tool works with the top tools, like Jira, Jenkins, GitLab, Slack, and TestRail. It also lets you use SSO and set roles for access. These features help large companies work easier together. Scalability for Large Projects: Functionize was made for big work. It can handle thousands of tests and keep working well, even with heavy use. Large teams can use it for continuous testing and can run tests often, even on every build or code change. Cloud execution helps things move fast. Cons: Proprietary System: You need to stay within the Functionize ecosystem for your test execution. It is not like open-source tools, so you do not get to see or change the main code running tests. If you want to do something very custom that is not in the current features, it might be hard or not possible. You need to stay within the Functionize ecosystem for your test execution. It is not like open-source tools, so you do not get to see or change the main code running tests. If you want to do something very custom that is not in the current features, it might be hard or not possible. Cost Visibility: The price for Functionize is not shown on their site and is known to be high, as it is made for large businesses. A small company may feel it does not fit their budget. The price for Functionize is not shown on their site and is known to be high, as it is made for large businesses. A small company may feel it does not fit their budget. Initial Onboarding: Learning every AI feature for your test execution and setting them up to work best for your app may take both time and some help from the Functionize team. It has a lot to give, but to get the most from these tools, you may have to put in a little extra work at first. Pricing: Functionize has different plans that fit your project size and support needs. The cost for the Starter plan begins in the low thousands of dollars each month and will be higher for the Enterprise plans. Every package gives you unlimited users and test runs. A 14-day trial is offered. If you want the exact price, you can ask for it. FAQ Which are the top AI testing tools available? In 2025, there are 4 giants in the industry: ACCELQ, Testim, and Functionize. has a slight lead because it integrates test management, manual and automated coverage and AI-driven analytics in a single workspace, providing teams with a single source of truth to plan, execute and report. The other 3 are special in one or more areas, such as codeless design (ACCELQ), smart UI locators (Testim), and autonomous cloud scaling (Functionize), but lack the end-to-end completeness of What are the main characteristics of an AI testing tool to consider? UI resistant self‑healing locators Plain-language-based test generation with the help of AI Smart CI/CD support to have continuous delivery Clear analytics to identify and pinpoint flaky tests and root causes. Web, API and mobile targets supported in a single interface addresses all the points on a single console; the rest of the tools fulfill most but not all of them. What are the key advantages of the AI test automation tools? More rapid scripting using natural-language or record-and-convert processes Reduced maintenance due to self healing and intelligent locators Broader coverage with the help of AI-created edge-case scenarios Faster feedback loops in CI pipelines, releases in shorter cycles Evidence‑based information that guides teams to the most at-risk locations first The most efficiency is observed in teams that implement a full-stack platform like where planning, execution, and analytics are in one place instead of multiple tools. Like this: Like Related
Techday NZ
16-07-2025
- Business
- Techday NZ
DevOps platforms see surge in outages & downtime in 2024 report
has released a report detailing a significant increase in outages and security incidents across key DevOps platforms, including GitHub, GitLab, Jira, Bitbucket, and Azure DevOps. Report findings The CISO's Guide to DevOps Threats, the latest publication from highlights that 2024 has been marked by notable growth in service disruptions and vulnerabilities affecting development teams worldwide. The report analyses incident data and the resulting impacts for some of the most widely used development environments, with a combined user base of approximately 1.2 billion. Among the platforms surveyed, Jira exhibited a 44% year-on-year increase in reported incidents, rising from 75 in 2023 to 132 in 2024. These incidents caused an accumulated 2,131 hours of downtime, equivalent to 266 standard working days or nearly 13 full weeks of lost productivity. The study notes that the trend is persistent, recording a 63% increase in incident numbers compared to 2022. In the third quarter of 2024 alone, Jira users experienced over 7 hours of critical disruptions. Bitbucket, another popular tool in the Atlassian suite, recorded 38 incidents in 2024, leading to more than 110 hours of downtime. With additional maintenance windows included, the total impact rose close to 200 hours, with more than 70 hours classified as critical or major disruptions. GitHub and GitLab incidents GitHub's service saw a reduction in the number of incidents, falling 25% to 124 events in 2024, down from 165 in the previous year. However, despite this improvement, users still contended with approximately 800 hours of degraded performance, translating to over 100 working days lost across 26 major and 97 minor incidents. The third quarter was particularly unstable, with 42 incidents noted. GitLab faced a 21% increase in reported incidents, growing from 76 in 2023 to 97 in 2024. The platform also had to address 153 vulnerabilities and experienced 798 hours of service disruption. Just 44 incidents collectively contributed to over 585 hours of partial outage, and September stood out as a challenging month with 21 critical vulnerabilities resolved. Azure DevOps impact Azure DevOps, operated by Microsoft, was also affected by service interruptions. The platform suffered 826 hours of downtime across 111 incidents, disrupting services for a period equal to roughly 103 standard working days - approximately 28% of a typical working year. The report suggests these extended outages had a significant operational impact, noting that the lost time could amount to 8 to 10 completed hackathon cycles under normal circumstances. Underlying causes "The source of these numbers across all platforms is rarely limited to isolated technical failures. In most cases, they result from the growing complexity of DevOps environments and the lack of comprehensive, end-to-end visibility across the entire software delivery pipeline. The widespread adoption of distributed architectures, CI/CD practices, and multi-cloud infrastructures significantly increases the challenge of detecting vulnerabilities, enforcing consistent security policies, and responding to incidents in real time," explains Greg Bak, Chief of R&D at "Without a robust backup and disaster recovery strategy, even minor incidents can escalate into critical outages, data loss, or delays in software delivery. Resilience must be embedded into every phase of DevOps - from code repositories to production runtime," Bak added. Industry context The compiled data underlines the growing operational risks in a landscape increasingly reliant on complex integration, distributed systems, and continuous delivery methods. The report's analysis suggests that as organisations continue to adopt advanced development practices and multi-cloud environments, there is a corresponding rise in both the frequency and duration of service disruptions and security incidents. The CISO's Guide to DevOps Threats also includes discussion of emerging cyber threats targeting DevOps environments - covering malware such as Lumma Stealer, NJRat trojans, fraudulent repositories, and various platform vulnerabilities. These findings indicate that security and continuity planning remain critical challenges for DevOps teams operating within today's interconnected software infrastructure.
Mid East Info
15-07-2025
- Business
- Mid East Info
Zoom rolls out new agentic AI offerings to save time and drive connections - Middle East Business News and Information
Zoom AI Companion now connects with 16 third-party apps, including ServiceNow, Jira, Salesforce, Asana, and Box, to complete tasks and orchestrate agents Custom AI Companion add-on is now available to online customers, delivering extended capabilities, including AI meeting summaries across top meeting platforms and customized meeting summaries Zoom expands core AI Companion capabilities, including real-time call questions, voice recorder for in-person meetings, and meeting agenda creation, included at no additional cost with paid Zoom licenses July 2025 — Zoom Communications, Inc. (NASDAQ: ZM) today delivered new agentic AI capabilities to help users complete tasks across platforms and save time during the work day. With the Custom AI Companion add-on, Zoom AI Companion can now connect to 16 third-party apps to help orchestrate tasks without leaving Zoom. Additionally, the Custom AI Companion add-on is now available for online purchase, enabling small business owners to leverage AI Companion across third-party video conferencing platforms, customize meeting summary templates, create custom avatars, and connect third-party apps to boost productivity, and help them get more done so they can focus on building and growing their business. 'With Zoom AI Companion's agentic skills, users will see a significant productivity boost to help them get more done — not just in Zoom, but across business-essential apps like ServiceNow, Jira, Salesforce, Asana, Box, and more,' said Smita Hashim, chief product officer at Zoom. 'The Custom AI Companion add-on empowers users to streamline their workflows by having AI Companion join their Zoom Meetings and in-person meetings, and can now access AI Companion across other video conferencing platforms.' New connected third-party apps for Custom AI Companion add-on With the Custom AI Companion add-on, users can now connect to 16 third-party apps. AI Companion uses agentic AI capabilities to maximize efficiency, helping users save time and get more done without leaving Zoom Workplace. With the Custom AI Companion add-on, users can already connect to apps like Amazon Q, Glean, and Jira to deliver powerful indexing, enterprise search, and ticketing capabilities. New app connectors also deliver context-rich answers and help complete tasks across workstreams with intelligent app orchestration. Improve sales and service outcomes: Accelerate decisions and improve customer satisfaction by empowering teams to resolve service tickets, track opportunities, and update records in real-time, directly from Zoom. When connected to Salesforce, ServiceNow, and Zendesk, AI Companion helps organizations streamline workflows, reduce manual effort, and ensure customer interactions drive meaningful business results. Reimagine document collaboration: When connected to Microsoft OneDrive, Google Drive, Box*, Confluence, Notion, or Coda, AI Companion helps drive meaningful conversations with secure access to existing documents during meetings, and the ability to generate new documents based on current meetings, update existing documents with simple prompts, or get a quick summary of a document. * Not all document features available at launch. Simplify project management: Keeping teams updated on projects and activities can be challenging, but when connected to Asana and Jira, users can query and command project tools, using AI Companion to update project statuses, assign tasks, and set deadlines without app-juggling or manual workflows. Reduce communication silos: Keep chats and ideas organized in Slack with the ability to search, summarize, and post messages from AI Companion. Recruit and onboard new talent: When connected to Workday, AI Companion can help expedite recruiting, interviews, and onboarding workflows with search and summary capabilities about open jobs and candidate profiles. Custom AI Companion add-on expands to online customers AI Companion captures meeting summaries from Microsoft Teams with the Custom AI Companion add-on. Many entrepreneurs, solopreneurs, small business owners, and consultants often find themselves switching meeting platforms throughout their day to take calls with clients and stakeholders, without a central way to organize their meeting notes. The Custom AI Companion add-on, now available for purchase online, expands AI Companion's meeting summary capabilities to third-party video conferencing platforms, and delivers agentic AI capabilities to help small businesses get more done: Professional service providers like consultants and freelancers can simplify workflows and save time beyond Zoom Meetings, Zoom Phone calls, and in-person meetings by using AI-generated meeting summaries across third-party meeting platforms. With connections to third-party applications like Asana, they can automatically have projects updated in Asana without leaving the meeting. Sales professionals can nurture relationships with prospects and clients while reducing admin time by automatically updating sales records in CRMs like Salesforce, based on the conversation. Educators can go beyond meeting summaries and lecture plans to reliably generate summaries and takeaways with custom summaries that can be shared with students to reinforce learning, and create personalized videos using Custom Avatars for Zoom Clips to connect with students in different languages. With the Custom AI Companion add-on, small businesses can connect AI Companion to the 16 aforementioned apps, plus tailor AI Companion skills to address their unique needs and drive efficiency across their organizations: Work across platforms: Zoom is an open platform, and AI Companion can attend third-party meetings, including Microsoft Teams and Google Meet, with Cisco Webex support coming soon. AI Companion can join meetings on a user's behalf to automatically transcribe, summarize, and deliver actionable follow-ups. Save time with AI-generated clips: With Custom Avatars for Zoom Clips, users can create an avatar in their likeness, provide a transcript of the desired content, and allow AI Companion to generate a clip for them, saving time and helping them scale their efforts. Customize meeting summaries with templates: Users can turn meetings into tailored, actionable summaries by selecting from 11 purpose-built templates designed to reflect the tone, structure, and focus of each meeting and match the meeting goals. Users can turn meetings into tailored, actionable summaries by selecting from 11 purpose-built templates designed to reflect the tone, structure, and focus of each meeting and match the meeting goals. Expand knowledge: Admins can connect Google Drive or Microsoft OneDrive accounts as data sources in AI Studio while respecting existing permission controls, and crawl public URLs as a data source for knowledge collections so AI Companion can crawl those pages and provide more relevant answers to users' queries. The Custom AI Companion add-on is now available for purchase online for $12 per user per month with paid Zoom Workplace plans. To learn more about how organizations can tailor AI Companion to meet their unique needs with the Custom AI Companion add-on, visit the Zoom website. Maximize the workday with AI Companion Zoom AI Companion continues to enhance productivity and collaboration across Zoom Workplace. These capabilities are included at no extra charge as part of Zoom AI Companion for all paid Zoom Workplace licenses. Get started faster: The new onboarding experience within the Zoom desktop app makes it easier to configure AI Companion settings, including what meetings are summarized, who summaries are shared with, and how they are shared. Build better meeting agendas: Users can easily add structure to meetings by creating agendas for upcoming meetings from templates. AI Companion can also leverage previous meetings or Zoom Docs to create even more tailored agendas. Get more out of calls: Users can now query AI Companion before, during, and after Zoom Phone calls to help them catch up and gain deeper insights. They can ask questions like, 'What was the disagreement about?' or 'Can you tell me the main points being discussed?' Users can also have AI Companion pull up information from previous conversations, prioritize missed calls, and draft follow-up messages. Summarize documents in chat threads: AI Companion can summarize supported text-based documents shared in Zoom Team Chat to help quickly and efficiently digest new information without leaving the chat thread. Capture notes and tasks for in-person interactions: AI Companion also supports in-person meetings with the Voice Recorder, transcribing, summarizing, and capturing action items, allowing users to focus on the conversation and revisit details and action items later. Easily access meeting assets: Users can access meeting summaries, transcripts, recordings, and event details from the meeting card in the calendar event and via email. Hosts will also be able to share the assets with participants via the meeting card in Zoom Calendar (coming later this month), and participants can request access to the meeting card via the Zoom Calendar event. Seamless sharing: AI Companion can be configured to automatically share meeting summaries to other platforms, to update counterparts and refresh customer records with the latest conversation highlights. Zoom Workplace powers collaboration and productivity Zoom Workplace continues to accelerate collaboration and help users ideate, create, and deliver effective work effortlessly on a single app. Track edits and publish externally in Zoom Docs: Easily track content changes to docs, highlighting content additions, deletions, replacements, and formatting with specific styles. Users can also now publish Zoom Docs as public webpages, accessible to anyone, whether they are logged in or not. Stitch, combine, and create longer clips: Merge multiple Zoom Clips into one seamless video without external apps, preview and make adjustments before finalizing edits, and preserve original content without overwriting original assets. About Zoom: Zoom's mission is to provide an AI-first work platform for human connection. Reimagine teamwork with Zoom Workplace — Zoom's open collaboration platform with AI Companion that empowers teams to be more productive. Together with Zoom Workplace, Zoom's Business Services for sales, marketing, and customer experience teams, including Zoom Contact Center, strengthen customer relationships throughout the customer lifecycle. Founded in 2011, Zoom is publicly traded (NASDAQ:ZM) and headquartered in San Jose, California. Get more information at
