Modern QA Strategies Making Life Sciences Platforms Reliable

Data in life sciences is now the engine, not just a reference point driving commercial strategy market forecasting clinical insights and competitive intelligence. Organizations need real-time information for important decisions so the platforms providing that information must be accurate, reliable and perform well. Given healthcare’s complexities, clinical workflows, and data-driven analytics, 10decoders builds AI-powered QA foundations, a strategic imperative for safeguarding trust, compliance, and frictionless innovation.Data in life sciences is now the engine, not just a reference point driving commercial strategy market forecasting clinical insights and competitive intelligence. Organizations need real-time information for important decisions so the platforms providing that information must be accurate, reliable and perform well. Given healthcare’s complexities, clinical workflows, and data-driven analytics, 10decoders builds AI-powered QA foundations, a strategic imperative for safeguarding trust, compliance, and frictionless innovation.

Deliver High-Quality Software By Validating Every User Story

In today’s world, agile development is highly appreciated because it is fast and flexible. Businesses respond quickly to the market requirements and teams deliver and make changes rapidly. However, this pace often comes at a cost and subtle details can go unnoticed. Even though the user story appears to be complete in Jira, automated tests may pass and the code compilation happens without errors, still the product may behave differently in production.
A key behavior may not function as expected or an edge case was not accounted for. When gaps like this occur, the issues stem not from a lack of effort but from broken functional traceability. Even if there are requirements, validation and implementation, if there is no route map binding them together, teams cannot be sure that what they built matches what was intended. The lack of alignment can cause agitated stakeholders, constant rework, and even delays in the release cycle.

Migrating From Selenium to Playwright for a New Era of Automation

For over a decade, Selenium has been the cornerstone of web automation testing. It helped teams verify complex user flows, validate UI consistency, and ensure smooth cross-browser functionality. However, as web applications have become more dynamic, the demands on test frameworks have evolved. Modern apps are built on asynchronous operations, API interactions, and frequent releases — all of which demand speed, reliability, and smarter automation capabilities.

This is where Playwright, an open-source automation framework developed by Microsoft, enters the scene. Playwright reimagines browser testing with a faster, more reliable architecture and built-in tools that reduce test maintenance overhead. Many organizations are now migrating from Selenium to Playwright to gain better performance, seamless cross-browser coverage, and deeper integration with modern CI/CD pipelines.

This blog explores why this migration makes sense, the advantages Playwright brings to automation teams, a side-by-side conceptual comparison with Selenium, and how AI-powered tools are transforming the way we write and maintain tests.

6-Step Process to Adopt Agents in Digital Assurance Today

Digital assurance has always been about precision, speed, and resilience. But as web ecosystems grow more complex—with dynamic UIs, evolving APIs, and constant releases—traditional test automation is starting to show its limits. Scripts break when the UI changes, locators drift, and teams spend countless hours maintaining test suites instead of innovating. That’s where Agentic AI steps in.

Reimagining Quality Engineering for the Agentic AI Era

A few years ago, Generative AI was the industry’s newest marvel — a clever assistant capable of writing, summarizing, and conversing. It worked quietly behind the scenes, helping humans think faster.