GenAI is Revolutionizing the Landscape of Software Development Lifecycle (SDLC)
Artificial Intelligence (AI) & GenAI can play a significant role in Software Development Life Cycle (SDLC) from requirement gathering to maintenance of the implemented software. AI tools and Generative AI Services (GenAI Services) help to streamline the processes at every phase of SDLC. Polyxer Systems offers Generative AI Services (GenAI Services) and implementing and using AI tools in SDLC to get the best benefits of the team with visible impact on their efficiency, accuracy, and productivity at every stage. Thanks to the rapid progress of AI Tools in SDLC and Generative AI Services (GenAI Services), the software development has become significantly efficient to automate the time-consuming processes at lower cost.
The transformation of SDLC due to AI and Machine Learning (ML) has dramatically changed the way the software is developed, tested and managed. Let’s have a closer look how the AI and Generative AI in SDLC impacts all phases.
System Design, Architecture
- The AI Tools have enabled Polyxer Systems' technical architects to design the most effective and robust system architectures.
- AI Tools have helped our architects analyse the project goals, understand the project requirements and based on that, suggest the most suitable system architecture. This saves valuable time for the development team.
- The Machine Learning Algorithms with the help of AI tools can help to analyse the existing code and patterns to suggest the improvements for more maintainable codebase following the best code quality and practices.
- The GenAI in architecture design helps to validate specific design choices to predict the performance, maintainability and potential issues in the code.
- AI-driven tools can help to save the time of the developers to 10% - 30% to define more robust architecture designs.
Development
- Software developers at Polyxer Systems uses the AI Tools and Generative AI services (GenAI Services) to improve the code quality and standard, unit test cases, identify bugs at initial level and better performance.
- AI Tools act as an assistant for the software developer, suggest relevant code snippets, review the code and provide the required improvements based on the coding patterns to help in accelerating the development process.
- The combined use of AI and Generative AI Services (GenAI Services) help our developers to automate the code generation process for repetitive and boiler plate codes with adherence to coding standards resulting in focusing more on core functionality implementations.
- The effective use of AI tools in the code generation process can provide contextually relevant code suggestions, identify coding errors and vulnerabilities, refactor codes for improved productivity, readability, maintainability, and performance resulting in achieving 40%-50% more productivity for the development team.
- GenAI in software development & application development helps writing a better code and software quality can be achieved by generating unit test cases based on the method signatures and documentation.
Deployment
- AI Tools have helped Polyxer Systems’ team to streamline the deployment process by optimizing the CI/CD pipelines to predict the impact of updates and automate the entire deployment process for swift releases with minimum downtimes.
- AI tools has helped our team to analyse the performance continuously and identify potential issues before they affect the users.
- The deployment processes have been monitored to automatically rollback the changes if any issues occur.
- GenAI in DevOps help to make the prediction for the optimal configurations for deployments, performance and cost.
- The efficiency for the deployment can be increased to 20%-30% with the help of AI-driven tools and Generative AI.
Project Management
- Polyxer Systems has seen the significant increase in the quality of Project Management after implementing the use of AI tools and Generative AI (GenAI) services.
- Our project managers use AI tools to analyse historical data for the project, can identify potential delays and roadblocks, resource requirements and allocations for the smooth project management.
- Generative AI and AI tools can help to provide useful insights through data which can be really helpful for risk identification and effective decision making.
- The GenAI in Project Management implementation has increased the success of project management up to 35% till now.
- With the help of AI, 80% of the project management processes can be automated to increase the effectiveness of the process of project planning and analysis.
Productivity Gains
Use of AI and Generative AI can be extremely helpful in every stage of the SDLC. The productivities may vary at various stages but on an average, the organizations which have implemented AI tools in SDLC stages have observed improvement of approximately to 30%-40% in the productivity.
How Can We Contribute
The evolution of the AI tools and GenAI services have changed the way we approach to the software development. We trust the power GenAI to streamline and optimize each phase of the SDLC. We use the combined approach for AI technologies with domain expertise to deliver the software solutions.
We are committed to leverage the AI driven innovation in the software development to improve efficiency and provide better solutions.
Consulting and Strategy Planning
We offer expert consultation to identify optimal use of AI applications based on the project needs and objectives.
Customized AI Solutions
We help in implementation of customized solution using AI in every SDLC phase to automate tasks, improve decision making and enhance overall SDLC efficiency.
Implementation and Integration
Seamless integration and implementation of AI Tools and Generative AI services (GenAI Services) into the workflows help to minimize the disruptions and maximize the impact on the productivity.
Quality Check
We take help of AI-tools and Generative AI Services (GenAI Services) to maximize the test coverage and provide a better-quality software and services.
Training and Support
We provide continuous training and support by leveraging the AI effectively to empower to our implementation teams and clients throughout the SDLC.
Data Privacy and Security
We understand the importance of Data security; hence we utilize the best of the AI-tools to keep the data protected and secure.
Use Cases
FAQs
1What are the overall productivity gains when implementing GenAI in the SDLC?
At Polyxer Systems, we have observed that incorporating GenAI in SDLC can boost productivity by an estimated 30-40% on average.
2How does AI contribute to faster time-to-market for new features and products?
GenAI in SDLC helps Polyxer Systems at every stage to enhance our decision making, accelerate development by automating repetitive tasks, providing smart code suggestions, and optimizing development and deployment processes, resulting in faster delivery of new features and products. GenAI in SDLC has contributed from requirement analysis phase to delivery, reduced manual efforts and speeding our overall project timelines.
3How does AI improve quality and reduce defects in software development & testing?
- At Polyxer Systems, we leverage GenAI tools which helps writing the code quickly by learning from the design patterns and solution skeleton to suggest the real time code snippets to the developers while writing the code.
- For existing applications including legacy ones GenAI learns the existing code, functions, patterns and help in rewriting the new code quickly.
- GenAI also writes the unit tests, checks the code errors, ensure the optimized and beautiful code to provide improved code quality.
4In what ways does AI enhance collaboration and decision-making in the SDLC?
At Polyxer Systems, we use GenAI in SDLC to get data-driven insights, predict risks, and actionable recommendations, facilitating better collaboration and informed decision-making among our team members.
5How does AI reduce the workload for developers?
GenAI in SDLC helps our software developers to automate repetitive coding tasks, generate documentation, and identify potential issues early, allowing our developers to focus on more complex and creative tasks.