Overview
Prism, a suite of Portable, Reusable, Integrated, Software Testing, Modules, is our homegrown Test Automation platform to introduce more efficiencies, accuracy, and speed in the software testing processes. It is easy to set up & configure and offers a one-stop solution for all the automation needs for Web, Mobile, and API testing at no additional cost
Our Automation Framework
Our Automation Framework
Why Prism
  • design-led

    Integrates well with other popular open-source tools & frameworks used for web application testing, native application testing, automation testing, behaviour-driven development, Continuous Integration & Test Management, and Agile project management

  • mvp

    Reduces analysis efforts by up to ~90% with the help of Auto Analysis, Pattern Analysis & Error Bucketing and keeps the script maintenance low by using Page Object Model & Page Factory Design patterns

  • agile

    Uses an AI/ML-powered Reporting Dashboard to provide detailed reports, important insights & fast feedback, with less noise through

  • analytics-led

    Offers Multi-Device, Multi-Platform & Cross Browser support and integrates well with multiple cloud-based platforms

Key Features

One-click setup!

The simple web-based Prism interface assists in choosing the framework of choice with great ease. One-click setup with the required integrations for the corresponding automation suite.

 

Real-Time Execution View

The centralized dashboard shows the execution status of the parallel runs in real-time. It offers the flexibility to run tests from the local machine, across multiple platforms, browsers, or devices/emulators & simulators.

 

Unified Test Reporting

The AI/ML-powered dashboard provides detailed analysis, important insights, and fast feedback with less noise - all in one place. 20+ reporting widgets are available to slice and dice all present as well as historical test execution data and offer a customized dashboard.

 

Cross-platform Test Coverage

The insightful reporting analytics provides test coverage across multiple platforms, browsers & devices. The data can be seen for individual launches (e.g current build) as well as collectively for all the launches in a sprint.

 

Analysis Efforts Optimized

The Machine Learning (ML) powered algorithm filters out false failures and helps to focus on real product bugs. With the Auto Analysis, Pattern Analysis & Error Bucketing features in place can reduce analysis efforts by ~90% reduction in analysis efforts. Visual Analytics is available for Launch Statistics, Failure Trends, Bug Categories, and Log Exceptions. Issues can be logged with a single click, along with the required information like screenshots & comments.

 

Flaky Tests & Preventive Measures

See the patterns of Test failures from the historical data and take preventive measures to increase the pass percentage in subsequent launches.

 
Insights

Best of industry knowledge for you!