Sammy Kolluru, is the Managing Director of imbus Canada Corporation and a leading figure in Software Testing and Quality Assurance. With over 17 years of experience, Sammy has been instrumental in shaping imbus Canada into a top solutions partner, known for its focus on effectiveness and innovation.
He is also a founding member and Board Director of TMMi America, contributing significantly to global software quality standards. Sammy’s journey in the tech industry offers a unique and inspiring perspective on entrepreneurship and innovation.

Software Quality and Testing plays a key role in the Software Development Lifecycle. Quality software not only avoids the businesses from becoming a nightmare headline in the news, it helps save money and time. Also, quality engineering plays an important role in ensuring that your customers will have a pleasant experience using your top-notch quality software.

The software testing industry is undergoing significant changes due to evolving technologies, customer expectations, and market demands. Emerging trends in testing have particularly impacted the quality engineering professionals.

This presentation is designed to discuss the key trends shaping the future of the software testing industry, especially for the quality engineering professionals.

In today’s data-driven world, silent failures in analytics pipelines can lead to flawed business decisions, poor AI model performance, and compliance risks. Traditional software test automation focuses on application behavior, but how do we ensure that the data powering our systems is reliable, accurate, and continuously monitored?
This session explores how test automation principles apply to data pipelines, the role of DBT in automating data quality testing, and how observability elevates testing beyond pass/fail assertions

• The unique challenges of data pipeline testing and why traditional test automation falls short.
• How DBT enables robust testing with singular, generic, and native tests—ensuring clean, governed, and validated data.
• How observability enhances test automation by detecting silent failures, enabling proactive monitoring, and feeding insights into AI models.
• The role of DBT Cloud and CI/CD integration in scaling automated data testing in modern DevOps environments.
• Why high-quality, observable data is critical for AI and LLMs—ensuring better decision-making and more reliable AI outcomes.

Problem Statement :

Traditional test Automation frameworks have been effective, however, there are lots of struggles with their Scalability, Maintenance, and adaptability to modern applications. Also, it takes time to build new scripts with the pace of new functionality during the Agile Process

About TestZen AI

TestZen AI is an AI-driven Test Automation framework that brings intelligence, efficiency, and robustness to the Automation framework. This TestZen AI helps overcome maintenance issues in tests, faster test case generation, and smart test case Execution with Predictive test Execution Solutions.

Below are the main features of this framework and the advantages it offers :

• Smart Test Case Generation and Execution
• Self Healing Test
• AI-driven Test Generation
• Overcoming Maintenance issues

In this session, we will be covering the topics listed below :

1. AI Redefines Test Automation Framework : How AI-driven framework reduces maintenance increases stability and optimizes execution like never before.

Example:

• AI can convert Manual Stories automatically into Test Scripts
• AI-powered NLP Test Script can generate Test Scripts from BDD feature files.

Impact:

• Reduces 30 to 40 percent of est Script Creation Effort
• Non- technical testers can also generate test scripts

2. Self Healing Test : How AI can detect UI changes and update locators automatically.

Example:

• When an Element Locator changes, instead of failing the test how AI can help in updating the elements dynamically.

Impact:

• It reduces the maintenance by 50 to 60 Percent

3. Smart Test Executions : How AI can analyze test changes and past test results and can run only impacted test cases.

Example:

• If there is a change in the Cart Module for a shopping platform then AI can easily skip login scenarios and can only run cart functionality if the need be .

Impact:

• Speed up test Execution by 40-50 % and makes ci/cd pipeline faster

4. AI-Driven Test Data Generation : How AI can help in Generating Test data based on analyzing production pattern

Example:

• Instead of using hard-coded data AI uses realistic data and provides test input dynamically

Impact:

• Improves Test coverage and uncovers more defects

What if I told you the future of QA isn’t just about automation — it’s about smart decisions, scalable processes, and people who know how to connect the dots between tools, teams, and business outcomes?

QA today isn’t a final phase — it’s a continuous, integrated practice. And with AI and analytics, we finally have the power to turn testing data into real insight. But dashboards alone don’t fix broken processes or misaligned teams.

Real transformation happens when you align people, tools, and goals — when metrics drive action, not just reporting. When vendors operate as one team. When QA speaks the language of delivery and business value.

In this talk, I’ll share how we led that shift for one of Canada’s largest enterprise programs — managing QA across multiple vendors, locations, and streams. From early challenges to building a unified quality strategy, data-driven dashboards, and real team alignment, I’ll walk through what actually made the difference — and what didn’t.

• Why QA must evolve from execution to strategic alignment — and what that really means in large-scale, multi-vendor programs.
• How to make quality metrics useful — turning data into decisions, not just dashboards.
• Lessons from failure — what didn’t work when trying to align teams and how we course-corrected.
• How to drive real collaboration across vendors and locations — building one quality mindset, not just parallel processes.
• Where AI and analytics fit into modern QA — and how to introduce them without overwhelming your teams.

Public Speaker – QA and Testing Topics
North American Ambassador & Chair Judge for the North American Software Testing Awards 2021- 2025
Chair/Judge The Software Testing & QE Awards 2019, HPE Application Delivery Management Customer Forum
Attendee World Economic Conference 2018-2022 Orlando Florida
Past President of TASSQ (TASSQ.ORG)
Conference Chair 2009 QAI – Toronto
Specialties: IT and QA

She is a Senior Software Engineering Leader with 17 years of experience in product innovation, technology strategy, and team development. She excels in building scalable software systems, leading global teams (100+), driving digital acceleration, fostering innovation, and establishing strategic partnerships to deliver seamless, high-impact solutions across industries.

Technology leader with 25+ years driving cloud transformation, digital banking, and enterprise software at scale. Expert in modernizing platforms, leading high-performance teams, and aligning tech strategy with business goals. Currently leading web banking transformation at Scotiabank with a focus on security, agility, and customer-centric innovation.