How AI-powered Quality Engineering services with a full-stack, continuous testing platform helps you achieve 10x test automation & market leadership

Delighted to invite you all to attend our 4th Fireside chat where I host Leaders from Innominds and AccelQ. Join us by registering here https://bit.ly/3pz0hv2 

In recent years, traditional approaches to application testing have been significantly disrupted with the advent of DevOps and intelligent automation, as well as the proliferation of digital applications. As delivery timelines have shrunk from months to weeks and nowadays, testing has shifted both left and right in the software development lifecycle. DevOps and agile have merged development and testing into a single continuous activity. Testing has evolved to quality engineering that begins upfront as part of initial application planning and establishes a continuous feedback loop to anticipate and act on the unknown.

But to truly understand the scale of evolution from testing to quality engineering, we need to recognize how data has changed software development itself. The power of data goes well beyond fueling automation use cases and AI learning datasets for repetitive development and testing tasks. The massive amounts of data users generate every day is now elevating quality engineers to predict risk, identify opportunities, increase speed and agility and minimize technical debt. With this vast influx of data, the quality engineer’s role has become far more exciting but also complex. It will further evolve as we move towards AI, edge computing and the massive IoT end datasets which require machine-to-machine (M2M) communications with complete autonomy and failsafe protection.

As enterprise applications and channels grow in number and complexity, and as new sources of test data emerge from a multitude of connected devices, platforms and technologies, both the volume and veracity of test data will increase dramatically. Moreover, with the need to integrate log and event data from so many devices, platforms and technologies, and with the coming shift from binary to quantum algorithms, the exponential growth in the number of test data points—and the complexity in processing them—is set to explode. The simple truth: today’s systems won’t be able to keep pace.

To adapt, QE will shift focus from the quantity of data to the quality of data—and the insights that can be derived from it. In place of trying to simply scan all available data, for instance, the focus will now shift to the most insightful data that can offer key insights into performance. Data-driven frameworks and quality platforms will store every test point and insight, enabling the real-time prediction of application defects. And AI-driven “test data as a service” will provide analytics as a function to testing systems, creating a playground for developing new products and services for the enterprise.

In this two-part session in the Innominds’ Fireside Chat series, you will experience how ACCELQ’s cognitive core engine combines with Innominds’ AI-driven quality engineering services to significantly accelerate the software readiness and quality of enterprises and software product companies. ACCELQ is the market leader in AI-powered unified codeless test automation and test management platform on cloud for Web, mobile, API, DB and Packaged Apps. It’s cognitive core engine unleashes the power of predictive analytics in scenario design, autonomics in test automation and adaptive change management in traceability.

As every company aims to be a software company and as every touchpoint is digitally transformed, improving end-customer experiences become a strategic imperative for companies. With enterprises increasingly building cloud-native applications, driving business processes with AI and adopting mobility and a Remote First approach to work, customer experiences have also radically changed.. And as enterprises and software product companies race to achieve digital transformation with AI-infused applications and complex software products, application quality becomes the cornerstone of competitive success

Therefore, continuous testing and full stack automation are necessary to ensure faster release of cutting-edge software. But as application release cycles get shorter and test environments more complex, there aren’t enough resources to meet the increasing QA demand and mitigate risks while trying to accelerate the pace of innovation. Conventional automated testing is often not adequate to address these QE needs.

Gartner forecasts that through 2025, AI and machine learning (ML) capabilities will emerge and mature in test automation tools to deliver faster time to market and reduce overall test creation and maintenance cycles.

Nelson Hall says that organizations engaged in an agile and continuous testing transformation are looking at emerging automation opportunities such as AI-based automated test script creation and are deploying automation through continuous testing approaches, AI and other cognitive technologies.

Against this backdrop, join us for an insightful Fire Side Chat series where ACCELQ and Innominds’ thought leaders give you an in-depth look at test automation. Innominds is a software engineering company that powers the digital next initiatives of some of the largest independent software, hardware and enterprise businesses of the world with its AI-driven quality engineering and continuous engineering services.

This fireside chat will focus on

a)   How ACCELQ’s AI-based test automation platform powered by no-code automation with self-healing capabilities, and built-in test management and CI tools integration is helping accelerate the quality and test automation of diverse application stacks. The ACCELQ platform is designed to support for web, API, DB, mainframe and more.

b)   How Innominds’ AI-driven quality engineering services, its relentless focus on offering full stack automation and DevTestOps is bolstered by the strategic partnership with ACCELQ and how this partnership is positioned to disrupt, and accelerate the software release cycles for global customers.

c)    The part 2 of the fireside chat series will focus exclusively on how ACCELQ’s market leading platform helps offer full-cycle automation for enterprise applications involving Salesforce applications, MS Dynamics applications and more.

d)   How Innominds’ enterprise quality engineering services and its partnership with ACCELQ is tailored to power test automation and accelerate the market readiness of global enterprises applications involving Salesforce.com and MS Dynamics applications.

Speakers

a) Shriram Krishnan: VP – Customer Success | ACCELQ

b) Sai Chintala: President, Head of Quality Engineering and DevOps | Innominds

Moderated by

C) Sairam Vedam: Chief Marketing Officer | Innominds