Humans meet machines to reach their full potential
The business models and processes in today’s world must be agile and flexible. Organizations are overwhelmed to align IT with business priorities and adopt changes to deliver business value. The industry is fast embracing Automation fueled with advancements in intelligent technologies to address these challenges. NIIT’s Tron Smart Automation Platform brings Intelligent Development Automation: leveraging Artificial Intelligence Analytics and latest technologies orchestration thereby maximizing automation benefits of agility and reduced cost.
How it works…
- Automation Maturity Model for assessment
- Recommendations on automation roadmap
- Process, Tools, Cultural enablement
- Roadmap for enterprise or product portfolio
- Solution Design, Proof of concept
- Automation Solutions
- Sustainability model
Intelligent development automation orchestrates and brings intelligence in the application lifecycle from planning to production leading to automation of discrete phases or activities like Requirement Management, Automated Deployment, Release Automation. It also provides comprehensive automation solutions in areas of Test Automation, Continuous Delivery, and DevOps Automation. It orchestrates tools across the delivery chain and develops efficient processes for Fast Cycle times, Frequent Deployments, Low Defect Rates and Continuous Flow.
AI-powered Dashboard which is a single pane of view integrated with all the tools across the application development lifecycle. The Dashboard supports integration with industry-leading commercial and open source tools. It brings end-to-end orchestration and a single pane of view of application/ product development. It comes with Cognitive insights derived from historical data patterns using Machine Learning to take the corrective decisions upfront further improving on the success of delivery.
SDP – Software Defect Predictor
QA organizations are challenged by not having a scientific mechanism to determine risk-based prioritization of regression testing. This leads to inefficient test cycles and a higher probability of defect leakage.
Software Defect Predictor predicts defects using Artificial Intelligence to enhance QA efficiencies beyond traditional practices. Prediction is done based on functionality changes done for the QA cycle, historical data, tester profile and past production incidents. The key benefits are:
- Shift left on high-risk areas
- Better resource planning and skill utilization
- Optimized test cycles leading to faster software releases
- Reduced cost of testing.
- STA – Smart Test Analytics
With the increasing adoption of DevOps and Continuous Delivery, efficient test cycles, and the ability to deliver rapidly has been one of the greatest challenges the software industry is addressing. Additionally, defect leakage has been a constant area of concern for any product, and missing test cases are invariably the key contributors.
Smart Test Analytics uses Artificial Intelligence and Natural Language Processing to automatically identify Traceability between Requirements and Test Cases, impacted requirements, and its related test cases and identify missing Test Cases. Key benefits are:
- Optimized test cycles by executing only impacted test cases
- Reduced rework by identifying missing and impacted test cases early in the lifecycle
- Better Quality and reduced cost of Testing
- Speed, productivity, and quality: Reshapes application delivery by game-changing improvements in quality, productivity, speed to market, and cost optimization.
- AI-powered Smart Automation in Application Development: Provides intelligent automation solutions leveraging orchestration and Artificial Intelligence across application lifecycle to achieve unprecedented levels of efficiency
- Tomorrow proof: Pluggable architecture built as a federated set of services gives extensibility to add in new capabilities as innovative technologies like AI mature
- Flexible Platform that integrates with enterprise existing tools thus safeguarding their investments.