

Advancing Excellence Through Intelligent, Cognitive Quality Systems
At Noesis, we believe the future of testing is rooted in the power of AI and Machine Learning — automating end-to-end testing across diverse environments such as web, Mobile and Desktop applications.
Our AI Powered Intelligent automation solutions are designed to be agile, cost-effective, and low in complexity. They operate independently or integrate seamlessly within our clients’ existing ecosystems, creating a robust test value chain that enhances efficiency across the entire testing lifecycle — from requirements through to closure.
Our mission is clear: to help you release better software, faster — with greater confidence and reduced risk.
Our Services
Cognitive Quality Assurance: Delivering high-performance software
As your team continues to innovate and scale, we introduce a forward-thinking approach to QA that merges AI, Intelligent Automation, and Cloud-Native Scalability.
We can develop a solution that transforms test automation into a self-scaling, intelligent process—perfectly aligned with DevOps and agile demands.

Quality Engineering: Fast. Scalable. Reliable.
For us, Quality Engineering is a strategic discipline that ensures applications do more than function – they deliver a consistent and differentiated user experience. We embed quality across every stage of the development lifecycle, aligning with Agile and DevOps practices to enable fast, reliable, and scalable delivery.
2. AI & Robotic Test Executors – to transform those insights into real-time, adaptive test cases;
3. Synthetic Test Data Generation – to scale Automation;
4. Cloud Execution Layer – to run tests where Runners & Workers orchestrated by Kubernetes + Infrastructure as Code (IaC) ensure seamless scaling across environments.
Intelligent Test Automation: Speed Meets Precision
At Noesis, Intelligent Test Automation is the cornerstone of our Quality Engineering approach to enable software testing faster, smarter, and scale-out.
Using AI, our automation solution can cover unit tests, API tests, integration tests, performance tests, and end-to-end tests, all within CI/CD pipelines. This allows us to eliminate repetitive manual testing, reduce human error, and speed up the release cycle. By moving left and right in the testing lifecycle, we build the quality into the software from the inception stage through to post-release monitoring, while reducing cost and lead time to market.
Using AI, our automation solution can cover unit tests, API tests, integration tests, performance tests, and end-to-end tests, all within CI/CD pipelines. This allows us to eliminate repetitive manual testing, reduce human error, and speed up the release cycle. By moving left and right in the testing lifecycle, we build the quality into the software from the inception stage through to post-release monitoring, while reducing cost and lead time to market.
AI-Powered Automation: Smarter Testing at Scale
Intelligent test automation revolutionizes traditional testing with AI testing tools that read business requirements and generate automated test cases. Our autonomous testing platform uses Robotic Test Executors and machine learning to create synthetic test data and execute tests across devices with Kubernetes testing infrastructure, reducing design time by 70% while improving coverage and delivery confidence.
testingON, our AI test automation platform, intelligently extracts user stories from business documents and converts them to detailed test cases using predictive testing algorithms. This intelligent test automation approach ensures timely, organized test generation that aligns business requirements with functional testing, delivering faster, more reliable software delivery.

Test Data Management: Power your testing with fast, secure, and Compliant Data
Efficient and scalable test automation needs the right test data, a source that is diverse, reliable and compliant with privacy requirements that closely specifies the real-world scenarios. We generate synthetic test data that is specific to your application context, with consideration of the technology, data models and business logic. This approach can be applied to relational databases, NoSQL data stores, APIs, and legacy systems, so your relevant high-quality test input is consistent. This synthetic data is a means to enabling you to have large-scale automated testing, so you can test your solution consistently across environments, maintain data privacy and minimize the use of production datasets.
Testing Automation Execution Layer by Kubernetes @ Infrastructure as Code (IaC)
To support large-scale and high-speed test execution, we developed a solution that incorporates an Infrastructure-as-a-Code (IaC) model built on Kubernetes. This enables dynamic scaling of test environments, allowing for parallel execution of thousands of automated tests in a containerized and isolated environment. As a result, Noesis empowers your teams to release faster, with greater confidence and stability, while significantly reducing testing costs and complexity.
This results in faster execution cycles, reduced infrastructure complexity, and improved deployment consistency across environments. Organizations typically see up to 40–60% cost savings in test infrastructure and a significant reduction in setup and maintenance time, all while supporting faster, more reliable software releases.
Raise your Quality
Highlights
Discover how we help our clients across every stage of the data journey — from governance and visualization to AI-powered insights