Spectro Cloud completed a $75 million Series C funding round led by Growth Equity at Goldman Sachs Alternatives with participation from existing Spectro Cloud investors.
Ensuring a positive digital experience has never been more important than it is today. Across all industries — from healthcare to banking to business — shifting customer expectations, and an increasingly rapid pace of innovation, are driving organizations to accelerate their digital capabilities.
Despite the push for digital transformation, a recent study found that many are experiencing challenges maintaining quality when building, deploying, and operating their applications, with testing reported as the primary bottleneck to delivering apps.
Further, according to Forrester's 2021 report, 54% of respondents say that they struggle to keep up with ever-changing customer demands and 49% of respondents say that their company has lost revenue due to poor digital CX (including quality).
To meet this changing landscape, organizations must adopt platforms and applications to operate more efficiently and serve customers more effectively. The solution? Quality engineering (QE).
Quality engineering plays a pivotal role in helping companies not only keep up but innovate faster, deliver high-quality products and services, outperform competitors, and exceed customer expectations.
In today's dynamic digital landscape, organizations need a method of software development that allows them to anticipate and stay ahead of customer demand. With an end-to-end perspective, quality engineering ensures every step of the software engineering and delivery process — including web, desktop, mobile, APIs and more — is performing to the best of its ability.
In particular, quality engineering can help organizations keep up with digital transformation in five key ways:
1. Fosters innovation by streamlining processes
Quality engineering involves a thorough examination of existing processes to identify inefficiencies, bottlenecks, and areas of improvement. When these pain points are identified, teams are able to make changes that streamline and optimize any areas that are lagging, create more efficient processes, and ultimately, spend more time focusing on more complex and innovative tasks.
Similarly, think of quality engineering as a trial-and-error process. When something isn't working, it's revisited and reworked until it operates according to plan. Sometimes teams have to get creative with solutions which, in turn, fosters overarching innovation.
2. Ensures compliance
For many industries, regulatory compliance is not only essential, but critical to staying afloat. When an end-to-end quality engineering process is implemented, products and services are better able to meet all necessary regulations and standards which, in turn, reduces the risk of fines, legal issues, and reputational damage.
3. Lowers cost and improves the bottom line
Investing in quality engineering can lead to long-term cost savings. As technology progresses and becomes more complex, quality engineering helps to improve process efficiency and address the app errors and defects that are costing companies money. With quality engineering, companies can reduce waste, minimize recalls and warranty costs, and optimize resource allocation to ultimately improve the bottom line.
4. Reduces risk
In a rapidly changing digital landscape, there are inherent risks associated with new technologies and complex systems — like security and privacy concerns, potential dependencies, regulatory challenges, and human error. Quality engineering helps companies assess and mitigate these risks through rigorous testing, security measures, and risk analysis, safeguarding their reputation and customer trust.
5. Helps exceed customer expectations
More than anything else, quality engineering focuses on meeting customer needs and ensuring that products and services are of the highest quality. By regularly reviewing processes, gathering feedback, and implementing corrective actions, quality engineering ensures customers are getting the best possible product and companies are staying at the forefront of their industry.
In addition to the five benefits listed above, combining quality engineering efforts with artificial intelligence (AI) can also help teams move quicker and streamline processes in an ever-changing digital world. AI allows companies to gain deeper visibility into testing and the software development lifecycle, expedites the tedious aspects of engineering, and helps to create more accurate and more powerful solutions.
Navigating a Digital-First World with Quality Engineering
In this dynamic and fast-paced environment, businesses must consistently deliver high-quality products and services to meet customer expectations and maintain a competitive edge. As organizations navigate this rapidly changing digital landscape, quality engineering is a powerful solution that meets the challenges of innovation and customer expectations head-on.
In fact, when a quality engineering approach is implemented, businesses experience 85% less testing effort, 90% higher automation rate, 95% less maintenance effort, 100% less cost avoidance, and a 30% higher project capacity.
By streamlining processes, ensuring compliance, lowering costs, reducing risk, and exceeding customer expectations, quality engineering empowers businesses to adapt quickly to the changing technological landscape, capitalize on opportunities, stay ahead of the curve, and outperform competitors.
Industry News
The Cloud Native Computing Foundation® (CNCF®), which builds sustainable ecosystems for cloud native software, has announced significant momentum around cloud native training and certifications with the addition of three new project-centric certifications and a series of new Platform Engineering-specific certifications:
Red Hat announced the latest version of Red Hat OpenShift AI, its artificial intelligence (AI) and machine learning (ML) platform built on Red Hat OpenShift that enables enterprises to create and deliver AI-enabled applications at scale across the hybrid cloud.
Salesforce announced agentic lifecycle management tools to automate Agentforce testing, prototype agents in secure Sandbox environments, and transparently manage usage at scale.
OpenText™ unveiled Cloud Editions (CE) 24.4, presenting a suite of transformative advancements in Business Cloud, AI, and Technology to empower the future of AI-driven knowledge work.
Red Hat announced new capabilities and enhancements for Red Hat Developer Hub, Red Hat’s enterprise-grade developer portal based on the Backstage project.
Pegasystems announced the availability of new AI-driven legacy discovery capabilities in Pega GenAI Blueprint™ to accelerate the daunting task of modernizing legacy systems that hold organizations back.
Tricentis launched enhanced cloud capabilities for its flagship solution, Tricentis Tosca, bringing enterprise-ready end-to-end test automation to the cloud.
Rafay Systems announced new platform advancements that help enterprises and GPU cloud providers deliver developer-friendly consumption workflows for GPU infrastructure.
Apiiro introduced Code-to-Runtime, a new capability using Apiiro’s deep code analysis (DCA) technology to map software architecture and trace all types of software components including APIs, open source software (OSS), and containers to code owners while enriching it with business impact.
Zesty announced the launch of Kompass, its automated Kubernetes optimization platform.
MacStadium announced the launch of Orka Engine, the latest addition to its Orka product line.
Elastic announced its AI ecosystem to help enterprise developers accelerate building and deploying their Retrieval Augmented Generation (RAG) applications.
Red Hat introduced new capabilities and enhancements for Red Hat OpenShift, a hybrid cloud application platform powered by Kubernetes, as well as the technology preview of Red Hat OpenShift Lightspeed.
Traefik Labs announced API Sandbox as a Service to streamline and accelerate mock API development, and Traefik Proxy v3.2.