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    Home»Development»Perficient Named 2025 Gold Globee® Winner for Best Artificial Intelligence Service Provider

    Perficient Named 2025 Gold Globee® Winner for Best Artificial Intelligence Service Provider

    May 21, 2025

    We’re excited to share that Perficient has been named the Gold Globee® Winner for Best Artificial Intelligence (AI) Service Provider in the 2025 Globee® Awards for Artificial Intelligence. The prestigious recognition highlights our leadership in delivering responsible and scalable AI solutions that are transforming businesses across various industries. 

    “The 2025 winners reflect the innovation and forward-thinking mindset needed to lead in AI today,” said San Madan, President of the Globee® Awards. “This recognition truly represents industry-wide respect and validation.” 

    Perficient was honored for its work helping enterprises rapidly adopt and scale AI technologies in collaboration with a broad ecosystem of partners. These include cloud providers and enterprise platforms with embedded AI capabilities, as well as leaders in generative AI (GenAI). Recent innovations include AI-powered assistants, intelligent automation solutions, and accelerators that reduce time-to-value and ensure the ethical implementation of AI. 

    “Winning the Gold Globee is an incredible honor and a reflection of our team’s commitment to helping clients understand, adopt, and leverage AI to move faster with confidence,” said Santhosh Nair, senior vice president, Perficient. “Our AI expertise is helping businesses transform operations, elevate customer experiences, and unlock new growth opportunities.” 

    Not only do we help clients harness the power of AI, but we also utilize it internally to enhance productivity, accelerate delivery, and elevate the quality and consistency of our work. By embedding AI into our processes, we can deliver greater output with fewer resources, reducing costs, increasing efficiency, and enabling clients to scale without increasing headcount. 

    “Winning the Globee Award for Best Artificial Intelligence Service Provider is a testament to our continued success as a disruptor in the technology services industry,” said Eric Walk, principal, enterprise data strategy, Perficient. “Our leadership in responsible AI-first management consulting and technology services allows us to simultaneously drive efficiency and growth for our clients through both AI-driven customer and employee experiences. This latest recognition alongside others for our LLM-as-Judge accelerator, our work in AI-driven Commerce with Coveo, and more highlights the true scale and diversity of our capabilities.” 

    We also developed a proprietary GenAI Integrity accelerator that identifies and mitigates the risks of bias and misinformation in AI models. The solution recently earned a 2025 Artificial Intelligence Excellence Award, demonstrating the company’s leadership in responsible AI. 

    “The GenAI Integrity solution is a reflection of our commitment to ethical and effective AI,” said Robert Bagley, director, AI, Perficient. “By proactively identifying risk, we help clients deploy AI responsibly and confidently.”

    Building on that commitment, Perficient’s PACE Framework (Policies, Advocacy, Controls, and Enablement) provides organizations with a structured approach to responsible AI adoption. It helps define governance policies, foster cross-functional collaboration, manage risk, and empower teams with the tools they need to succeed. By combining strategic oversight with practical enablement, PACE ensures that AI solutions are implemented ethically, transparently, and at scale. 

    This recognition follows the release of our Generative AI in the Workforce study, which revealed that while executives are enthusiastic about GenAI’s potential, many employees feel uncertain and unsupported due to limited communication and training. The study provides valuable insights to help organizations align their strategy and execution as they implement AI. 

    “Our research shows how critical it is to bridge the gap between leadership vision and workforce readiness,” said Walk. “As organizations embrace GenAI, success depends on strategy, communication, and education.” 

    Learn more about our award-winning AI consulting services that help businesses design and implement intelligent solutions responsibly. 

     

    Source: Read More 

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    Data-Driven Testing with Selenium WebDriver

    June 19, 2025

     
    Data-driven testing is a robust testing methodology that focuses on testing the functionality of an application using multiple sets of data. Instead of hardcoding input values and expected results, this approach separates test logic from the test data, enhancing reusability and maintainability. Selenium, being a popular automation tool, supports data-driven testing seamlessly when integrated with testing frameworks like TestNG or JUnit.
    In this blog, we’ll delve into the concept of data-driven testing, explore its benefits, and demonstrate how to implement it using Selenium with detailed coding examples.

    What is Data-Driven Testing?
    Data-driven testing involves executing test scripts multiple times with different sets of input data. The test data is typically stored in external sources such as:

    Excel files

    CSV files

    Databases

    JSON or XML files

    This approach is particularly useful for validating applications where the same functionality needs to be tested with various input combinations.

    Benefits of Data-Driven Testing

    Reusability: Test scripts are reusable for different data sets.

    Maintainability: Test logic is separated from test data, making maintenance easier.

    Scalability: Allows extensive test coverage with diverse data.

    Efficiency: Reduces redundancy in writing test scripts.

    Tools Required

    Selenium WebDriver: For browser automation.

    Apache POI: To read/write data from Excel files.

    TestNG/JUnit: For test execution and data provider functionality.

    Setting Up Your Project
    Add Dependencies
    Include the following dependencies in your pom.xml if you’re using Maven:<dependencies>
    <dependency>
    <groupId>org.seleniumhq.selenium</groupId>
    <artifactId>selenium-java</artifactId>
    <version>4.10.0</version>
    </dependency>
    <dependency>
    <groupId>org.apache.poi</groupId>
    <artifactId>poi</artifactId>
    <version>5.2.3</version>
    </dependency>
    <dependency>
    <groupId>org.apache.poi</groupId>
    <artifactId>poi-ooxml</artifactId>
    <version>5.2.3</version>
    </dependency>
    <dependency>
    <groupId>org.testng</groupId>
    <artifactId>testng</artifactId>
    <version>7.8.0</version>
    </dependency>
    </dependencies>

    Code Example: Data-Driven Testing Using Excel and TestNG
    Step 1: Create the Test Data
    Create an Excel file named TestData.xlsx with the following columns:

    Username
    Password

    user1
    pass1

    user2
    pass2

    Save this file in the project directory.
    Step 2: Utility Class to Read Excel Data
    Create a utility class ExcelUtils.java:import java.io.FileInputStream;
    import java.io.IOException;
    import org.apache.poi.ss.usermodel.*;

    public class ExcelUtils {
    private static Workbook workbook;
    private static Sheet sheet;

    public static void loadExcel(String filePath) throws IOException {
    FileInputStream fis = new FileInputStream(filePath);
    workbook = WorkbookFactory.create(fis);
    }

    public static String getCellData(int row, int column) {
    sheet = workbook.getSheetAt(0);
    Row rowData = sheet.getRow(row);
    Cell cell = rowData.getCell(column);
    return cell.toString();
    }

    public static int getRowCount() {
    return sheet.getLastRowNum();
    }
    }
    Step 3: Test Class with Data Provider
    Create a test class LoginTest.java:import org.openqa.selenium.By;
    import org.openqa.selenium.WebDriver;
    import org.openqa.selenium.WebElement;
    import org.openqa.selenium.chrome.ChromeDriver;
    import org.testng.annotations.*;

    public class LoginTest {

    WebDriver driver;

    @BeforeClass
    public void setup() {
    System.setProperty(“webdriver.chrome.driver”, “path_to_chromedriver”);
    driver = new ChromeDriver();
    driver.get(“https://example.com/login”);
    }

    @DataProvider(name = “loginData”)
    public Object[][] loginData() throws Exception {
    ExcelUtils.loadExcel(“TestData.xlsx”);
    int rowCount = ExcelUtils.getRowCount();
    Object[][] data = new Object[rowCount][2];

    for (int i = 1; i <= rowCount; i++) {
    data[i – 1][0] = ExcelUtils.getCellData(i, 0);
    data[i – 1][1] = ExcelUtils.getCellData(i, 1);
    }
    return data;
    }

    @Test(dataProvider = “loginData”)
    public void testLogin(String username, String password) {
    WebElement usernameField = driver.findElement(By.id(“username”));
    WebElement passwordField = driver.findElement(By.id(“password”));
    WebElement loginButton = driver.findElement(By.id(“login”));

    usernameField.sendKeys(username);
    passwordField.sendKeys(password);
    loginButton.click();

    // Add assertions here to verify login success or failure
    }

    @AfterClass
    public void teardown() {
    driver.quit();
    }
    }

    Best Practices for Data-Driven Testing

    Use External Data: Store test data in external files to reduce script changes.

    Parameterize Test Cases: Avoid hardcoding data in test scripts.

    Error Handling: Implement robust error handling for file operations.

    Optimize Performance: Load test data only once if possible.

    Clear Test Data: Ensure the test environment is reset before each run.

    Advantages of Data-Driven Testing with Selenium

    Flexibility: Easily test multiple scenarios by changing input data.

    Enhanced Coverage: Test edge cases by providing varied data sets.

    Reduced Redundancy: Write fewer scripts for multiple test cases.

    Conclusion
    Data-driven testing is a vital strategy for efficient and thorough test automation. By combining Selenium with tools like Apache POI and TestNG, you can create scalable and maintainable test suites that cover a wide range of scenarios. Implement this approach to enhance your testing process and ensure high-quality software delivery.

    Keywords: Data-Driven Testing, Selenium, TestNG, Apache POI, Automation Testing, Excel Integration, Test Automation Framework.

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