Boston-based SmartBear is the new owner of QMetry, a provider of an AI-enabled digital quality platform that aims to scale software quality, the software and API testing firm confirmed.
Financial details were not disclosed by SmartBear or the sellers, QMetry’s private equity owners, Goldman Sachs Alternatives and Everstone Group.
“This strategic acquisition will further enable agility for DevOps teams to speed up feature delivery, shorten time-to-market, and consistently deliver high-quality software,” the company explained in a statement.
In addition, Dan Faulkner, SmartBear’s chief product officer, said that “QMetry’s solutions align perfectly with our objectives.”
Makarand Teje
“By adding their test management and AI-enabled tools to our portfolio, we’re expanding our technical and market footprint,” he added.
Explaining the rationale to agree to a takeover by SmartBear, QMetry’s chief executive officer, Makarand Teje, called the sale “a new chapter” for QMetry.
“Our AI-driven solution is designed to help organisations scale their test management efforts, and with SmartBear we will be able to accelerate that innovation,” Teje stated.
Built on “compliance-driven” test management, as SmartBear put it, QMetry’s GenAI-enabled platform aims to scale testing efforts, reduce manual tasks, and accelerate release cycles. The company claims to serve several Fortune 500 companies.
Some of its selling points are features such as approval workflows, e-signature capabilities, advanced reporting, flexible deployment options, auto test case generation, flaky test detection, and ISO and SOC 2 compliance.
Integration into portfolio
The companies said QMetry’s platform will be integrated into SmartBear’s Test Hub solution, which is part of SmartBear’s range of software testing products, which also include API Hub and Insight Hub.
They all feature HaloAI, an AI-driven capability that was introduced across SmartBear’s entire product portfolio earlier this year.
The launch of HaloAI meant a major push into AI, following a range of new products and features earlier in the year.
Analysts across the board told QA Financial at the time of the launch they did welcome SmartBear’s move as the company’s artificial intelligence strategy is rapidly maturing.
Scrutinising SmartBear’s moves, Paul Nashawaty, practice lead for application development and modernization at Texas-based research and consultancy firm The Futurum Group, said that “by extending its test management functionalities with intuitive, codeless GenAI-powered automation capabilities, teams can achieve a synergistic test workflow that enhances test quality and accelerates software release cycles.”
“This combination democratises testing, making it not only accessible and manageable but also significantly boosts efficiency and coverage, ensuring higher software quality and faster go-to-market times and will allow for a great adoption of AI in production workloads,” the analyst stated.
In addition, Melinda Ballou, Research Director for Agile ALM, Quality, and portfolio strategies at IDC, said that “as code assistants permeate software development increasingly, effective software quality and testing strategies are vital to help ensure the quality of code which is being created more quickly and with less human oversight.”
She added that “to improve efficiency, cited areas of focus with AI and GenAI as the technology evolves include test prioritisation, identifying root cause of failed tests and code, test case creation, self-healing, test case maintenance, and test process improvement insights.”
HaloAI comprises of generative AI solutions that are designed to tackle complex, real-world problems.
As a result, the new tech tool enhances software development and testing by automating repetitive, error-prone tasks that often require manual intervention due to their complexity, according to SmartBear’s chief executive officer, Frank Roe, who has been at the helm since 2018.
Massachusetts-based Roe stressed that “HaloAI is more than another coding assistant; it accelerates development, enhances team productivity, and delivers innovative business outcomes, while addressing existing and future talent gaps.”
In fact, he went on to say that “HaloAI isn’t just AI; it’s a catalyst for smarter work. We are transforming, amplifying creative and strategic abilities. This will shatter test times by 89% and automate half of QA tests.”
Frank called HaloAI “a game-changer” for teams grappling with a shortage of skilled development and test resources.
Product expansion
The HaloAI launch came only weeks after SmartBear rolled out a new no-code test automation tool that was integrated into the firm’s popular Zephyr Scale solution, a platform that delivers scalable, performance test management capabilities.
Industry observers responded positively to that announcement, with one analyst telling QA Financial the new integrated capability paves the way for “a more sustainable fusion of AI-assisted test generation and automation.”
“We are witnessing the emergence of more sustainable fusions of AI-assisted test generation and automation that go far beyond simply putting a chat interface in front of a testing tool,” said Jason English, director and principal analyst at Intellyx.
“A natural language interface designed with declarative, intent-based testing in mind allows test and development teams to achieve higher test resiliency and regression test coverage, as the machine learning model will gain additional user context over time,” he observed.
Dan Faulkner
The technology specialist also said the new solution was a direct result of the company’s recent acquisition of rival firm Reflect.
“With our strategic acquisition of advanced AI-powered provider Reflect just months ago, we are pioneering a groundbreaking approach in test automation,” explained Faulkner.
In February, as reported by QA Financial, SmartBear acquired the AI-driven no-code testing platform called Reflect in a strategic move to strengthen the company’s GenAI capabilities.
The testing solution for web applications allows developers and testers to write tests faster as text prompts, enabling greater automation.
Prior to the acquisition, Reflect was owned by Battery Ventures, Craft Ventures, and Y Combinator. Financial details were never made public.
In addition, SmartBear also recently rolled out a new solution that allows back-end performance monitoring and distributed tracing.
The new platform, called BugSnag, includes OpenTelemetry-native performance insights and distributed tracing as part of its error and real user monitoring solution.
“This new functionality empowers developers to proactively identify and resolve performance bottlenecks and systemic issues with a truly comprehensive view of application performance, increasing responsiveness and enhancing overall customer experience,” explained Justin Collier, senior director of product management at SmartBear.
Justin Collier
“These new capabilities are valuable for enterprises with highly critical applications and those that prioritize delivering exceptional user experiences, especially on mobile and other front-end platforms where quality of interaction is critical,” Collier added.
He stressed that “the uniqueness of BugSnag’s new distributed tracing lies in its end-to-end nature, which is increasingly hard to achieve in modern architectures today.”
In fact, “in today’s complex, distributed environments, ensuring seamless performance across all layers of the application stack has become progressively challenging. By tracing issues from the user’s application all the way through to distributed systems and tying everything together, BugSnag provides a thorough view of an application’s performance,” Colliers elaborated.
The product is expected to be taken up by a range of banks and financial services firms as they are increasingly turning to sophisticated applications, embedded in their digital infrastructure.
AI approach
Faulkner pointed out that the Reflect acquisition accelerated SmartBear’s AI strategy to meet diverse customer needs by intelligently powering the firm’s three integrated hubs “for API development, testing, and production readiness with insights that power great user experiences across the entire software development lifecycle.”
In addition, he disclosed the firm is in the process of realigning around 20 products into “intuitive solution hubs,” including its Test Hub, primarily to simplify the customer experience.
The Test Hub allows testers to manage, automate, and execute all tests in one place to guarantee app quality.
Faulkner called his firm’s approach “groundbreaking in test automation” as it “removes barriers such as lack of time, technical expertise, and resources, allowing for complete traceability in the testing process.”
“Testing codes are being created more quickly and with less human oversight.”
‘Breaking point’
Despite the firm focus on AI, and the rollout of HaloAI across SmartBear’s entire portfolio, CEO Roe takes an open yet measured approach towards AI.
Software companies face tremendous pressure to deliver products quickly, but too many AI-based tools create low-quality code, he warned.
Therefore, “the software testing space is at a breaking point,” Roe said.
According to the industry insider, the crisis is precipitated by two interrelated problems.
Firstly, “the increasing and immense business pressure on teams to continue to deliver software code faster amidst fierce competition and a developer shortage,” Roe wrote in a recent analysis.
Secondly, the unstoppable rise of generative AI. “Although the promise of AI-powered development tools is undeniable, a crucial element is missing from the conversation around these AI assistants, the increasing flood of low-quality code, with catastrophic consequences,” he stated.
The Microsoft/CrowdStrike outage in July was a stark reminder of the global dependence on software and the challenges an internet shutdown could cause to many banks, financial services firms and other companies, such as airlines, around the world.
Roe singled out a recent study which found that the U.S. is the nation that’s most economically vulnerable to an internet outage, with the cost estimated at a staggering $458,941,744 per hour.
“The overwhelming impacts of software failures are making headlines at an alarming rate, wreaking havoc on businesses and directly endangering lives,” he said.
“Hailed as a game-changer, generative AI has undeniably transformed software development, but it’s important to remain aware of the potential complexities and risks it introduces,” Roe noted.
“A crucial element is missing from the conversation around these AI assistants, the increasing flood of low-quality code.”
– Frank Roe
As generative AI tools have lowered the barrier to entry for code creation and democratised software development, the foundation of our software-dependent world has come under threat, Roe continued.
“Limited oversight has led to an influx of subpar code, often riddled with bugs and vulnerabilities that enter the system.”
He pointed out that the increasingly common practice of having non-technical individuals create code exacerbates the issue because they may not understand the intricate nuances and potential downstream consequences of the code they’re creating.
“The lack of understanding about coding complexities and the necessity of rigorous testing is leading to a degeneration in code quality,” Roe explained.
According to the industry veteran, this trend is evidenced by increasing reports of software failures, which are often linked to overlooked coding errors and inadequate testing.
“Studies have shown that as more people with limited programming experience contribute to codebases, the number of critical bugs and security vulnerabilities undergoes a significant increase,” Roe noted.
Pressure
As the CEO of a global tech company, Roe said “I understand the immense pressure businesses face to stay competitive, and the subsequent pressure this places on our engineering and product teams.”
He called generative AI a powerful tool, catalysing increased productivity and automating repetitive tasks in development and testing.
Nevertheless, it also “poses potential threats to the foundation of software development, and is contributing to the generation of subpar code and heightened vulnerability to security threats,” Roe summarised.
He argued that AI lacks the ability to fully grasp the nuances and intentions behind complex software architectures, which can lead to suboptimal design choices.
Additionally, AI-generated code often suffers from poor documentation and readability, complicating future development and debugging efforts.
“Automated code generation has also resulted in less rigorous code review processes, increasing the likelihood of undetected errors and vulnerabilities,” Roe said.
Therefore, thoughtful use of generative AI, rooted in trust and transparency, is critical, he argued.
“This involves clearly communicating when AI is being employed, embedding responsible practices, and ensuring AI-driven code is thoroughly tested and reliable.”
“The software testing space is at a breaking point.”
– Frank Roe
Moreover, Roe thinks “this approach helps build confidence in AI tools among developers and end users, ensuring AI enhances rather than compromises the quality and integrity of software.”
Finally, for the industry veteran it is also important to ensure you are using generative AI to solve real customer problems, making feedback and transparency with customers critical.
In other words, by understanding AI’s limitations, developers can capitalise on its strengths while mitigating its risks, Roe stressed.
“Creating code that drives the apps and software we have all grown accustomed to is a complex and complicated process,” he added.
“This requires a human-centric approach, where developers maintain ownership of the code, validate outputs rigorously, and prioritise quality.”
QA teams
Finally, Roe was keen to stress that the power of AI does not diminish the importance of experienced development teams.
“We need to use AI to streamline processes, not replace human judgment and critical thinking. AI can handle repetitive tasks, identify patterns, and suggest optimizations at a scale and speed that humans alone cannot match,” he said.
“The deeper understanding of context, project goals, long-term implications, creative problem-solving, and ethical considerations that experienced developers bring are irreplaceable, however.”
Roe added that by combining AI’s capabilities with human expertise, we can achieve a balance that enhances productivity while ensuring superior quality.
“The software industry is at a breaking point, facing a silent crisis that demands immediate attention,” he warned.
“Prioritizing software quality is not just an option; it is a necessity to safeguard the future of technology,” Roe said.
“We have had several wake-up calls, emphasizing the need to place software quality at the forefront. Compromising on this aspect is a risk we cannot afford to take,” he concluded.
“It’s time for a revolution in software quality.”
NEXT WEEK
QA FINANCIAL FORUM LONDON: RECAP
Last month, on September 11, QA Financial held the London conference of the QA Financial Forum, a global series of conference and networking meetings for software risk managers.
The agenda was designed to meet the needs of software testers working for banks and other financial firms working in regulated, complex markets.
