Validata announces technology advances and innovations in the latest Validata Sense.ai release

The purpose is to enable banks and financial services organisations to be agile and resilient and achieve success in their digital transformation, DevOps or Cloud adoption initiatives.

As far as the actual product, Validata is launching a total of four new products. These include new test automation features with automated business impact analysis and tools for root cause insights and business monitoring analytics. Among others it offers:

• Smart requirements modelling: This enables business and IT teams to easily design business requirements from scratch using an intuitive drag-and-drop modeler. It also allows for importing requirement documents, easily linking them to their respective business workflows and test cases. It models complete and unambiguous flowcharts for maximum test coverage, automatically generates the optimal set of tests directly from your requirements, and self-updates the tests if there is a change in the requirements.
  By visualising and modelling complex digital and legacy systems, flow and subflow dependencies testers and developers gain the in-depth understanding they need, to deliver better quality applications to market faster.
• Root Cause Insights: With advanced AI and ML-augmented algorithms, defect clustering and classification techniques it is able to automatically pinpoint the reasons underlying defects and suggest the optimum corrective actions. Defects are prioritized based on their impact so you always know if an issue is impacting the user experience.
• Test Data Automation: We have extended the test data automation capabilities to deliver secure, compliant and quality test data on-demand at higher performance and speed. Through the platform’s AI test recommendation engine, we also provide test data recommendations and suggestions on the best data combinations to maximise the test coverage using the minimum number of test cases and data.
• Advanced Data Privacy: Masking algorithms and an intelligent data profiling functionality, allows to understand the complex table structures and metadata formats used in your critical applications and faster identify and protect your sensitive data even in the largest, most complex environments. Masking is integrated with data virtualization to deliver masked virtual or synthetic data within data centers and across private and public clouds.

On the machine learning (ML) side, the company is strengthening its predictive intelligence functionality with supervised and unsupervised machine learning algorithms which gain knowledge through known or unknown patterns. This new solution makes it easier to detect issues while also suggesting the ‘next best action’ and optimal user journeys to achieve maximum coverage.

The advances in the use of machine learning and explainable AI technology, enable 100% justifiable recommendations that trigger proactive actions for the sprint or cycle test optimization against the business risk and bug hunting. The same applies for Release Summary insights with faster data aggregation and analysis to reveal release health and readiness to go-live in a centralised view.

Along with AI and ML capabilities, we have extended the use Natural Language Processing (NLP) and data ranking algorithms in the SearchIQ engine to enable faster voice and chat-driven data searches and predictions.

With specialised solutions for Temenos clients the company is also now bringing together some of its existing solutions with more advanced features for those customers. The Validata advantage has always been one architecture, one data model and one cloud-native unified platform that empowers QA, development and operation teams deliver flawless digital experiences across digital and legacy systems.

This new release provides smart experiences powered by AI, iRPA, pre-built banking content and workflows to test end-to-end the user experience. All these together, will provide the agility banks need to accelerate their digital transformations.