AI-Assisted Software Development
Partner with Edvantis to ensure balanced, secure, and legally compliant integration of gen AI assistants, code generation tools, and custom-trained language models in your software development lifecycle (SDLC). From proof of concept (PoC) and managed pilot programs to large-scale implementations, we offer on-demand AI-assisted software development services.
61%
of adopters say AI in SDLC enables innovative work, as per Capgemini
45%
of productivity gains come from AI in SDLC, says McKinsey
62%
of leaders say AI in SDLC is vital to be competitive, as per GitLab
AI for Software Engineering Our Services
The Value of our AI-Assisted Software Development Services
On-demand Service
Responsible AI Practices
Extensive AI Experience
AI Security by Design
We offer AI-assisted software development services on an on-demand basis. Therefore, we only use AI tools and coding assistants with our customers’ explicit, legally documented approval. During our cooperation, we ensure transparency with our customers and privacy of their data at every stage of AI-assisted engineering adoption.
We recognize the importance of using AI coding assistants and custom models responsibly while protecting our customer’s business and user data. Therefore, we make sure our models, tools, methods, and practices are GDPR-compliant and adhere to the EU AI Act. We have an internal AI committee consisting of tech, infosec, and legal experts who monitor the use of AI within the company.
Our artificial intelligence portfolio is backed by a team of 50+ AI, data science, and data engineering specialists. With experience in generative & predictive AI, natural language processing, and large language model training, our experts can automate your SDLC process. As part of our previous projects, our team designed models that predicted employee sentiment, automated knowledge base management, and provided personalized recommendations.
Before implementing AI-powered tools for software development, we perform a thorough risk assessment to avoid any security vulnerabilities or compliance issues. We only work with AI tools that have strong encryption and anonymization protocols. Also, we make it a priority to review and test all AI-generated code patterns and code suggestions to ensure they are reliable, accurate, and unbiased.
We offer AI-assisted software development services on an on-demand basis. Therefore, we only use AI tools and coding assistants with our customers’ explicit, legally documented approval. During our cooperation, we ensure transparency with our customers and privacy of their data at every stage of AI-assisted engineering adoption.
We recognize the importance of using AI coding assistants and custom models responsibly while protecting our customer’s business and user data. Therefore, we make sure our models, tools, methods, and practices are GDPR-compliant and adhere to the EU AI Act. We have an internal AI committee consisting of tech, infosec, and legal experts who monitor the use of AI within the company.
Our artificial intelligence portfolio is backed by a team of 50+ AI, data science, and data engineering specialists. With experience in generative & predictive AI, natural language processing, and large language model training, our experts can automate your SDLC process. As part of our previous projects, our team designed models that predicted employee sentiment, automated knowledge base management, and provided personalized recommendations.
Before implementing AI-powered tools for software development, we perform a thorough risk assessment to avoid any security vulnerabilities or compliance issues. We only work with AI tools that have strong encryption and anonymization protocols. Also, we make it a priority to review and test all AI-generated code patterns and code suggestions to ensure they are reliable, accurate, and unbiased.
Use AI to optimize your SDLC with Edvantis as your partner!
AI-assisted software development sparked interest in the IT industry, raising hopes for faster and cost-effective software delivery. However, the power of AI extends far beyond saving time and cutting costs. It’s an accelerator of creativity and productivity in development teams, preventing them from getting caught up in the same maintenance routines. Partner with Edvantis to reap the full benefits of AI for software development with complete confidence: your data, code base, and intellectual property are safe and sound.
Vasyl Mukhar
Technical Director, Edvantis
Benefits of AI Coding Assistants
01.
Deliver Software Projects Faster
AI coding assistants make a strong case for simple, routine tasks with the highest standardization potential. Use them to automate boilerplate code generation, code formatting, test script writing, code reviews, and minor bug detection.
02.
Prioritize Value-added Work
Redirect the time and cost savings you have gained from AI integration to value-added tasks. Focus your team’s attention on in-depth coding, security reviews, strategic planning, and complex solution design.
03.
Release More Products
AI assistants can potentially accelerate the whole SDLC, resulting in a faster time to market for new products and software updates. This way, you will be able to meet the evolving customer demands better than the competition.
04.
Reduce Technical Debt
Deliver software and updates faster without building up technical debt or settling for suboptimal code quality. AI coding assistants simplify code refactoring, summarize code changes, and explain complicated legacy code, improving maintainability.
05.
Improve Developer Experience
Enhance Software Developer performance by cutting inefficiencies within the development process. Focus their attention on upskilling, solving novel problems, and writing code – top activities that improve job satisfaction.
Steps to Adopt AI-assisted Software Development
A small-scale proof of concept is a good place to start. By doing so, we can assess how Gen AI impacts your software development lifecycle on a small, manageable scale while handling all security and compliance considerations.
01. Establish Goals and Select Tools
Through a series of workshops, we identify the outcomes you expect from AI-assisted software development. Are you looking to tackle legacy code, deliver more lines of code, or improve error detection and remediation? We make sure your goals align with all stakeholders, select the relevant tool per your use case and programming language, and estimate project timelines.
02. Create a Risk Management Strategy
Next, we create a risk management strategy to plan for and remediate any security issues, compliance considerations, or code leakage concerns. For increased security, we set up isolated development environments, rely on private servers, and use non-proprietary code.
03. Identify Success Criteria for your PoC
We create a productivity measurement protocol to monitor the impact of AI coding assistants on your Software Developers’ productivity. We recommend measuring not only lines of code delivered but also developer acceptance rate, developer sentiment, coding time, and software quality.
04. Onboard and Train Developers
AI-based coding assistants have only recently become popular, so even experienced Software Developers might not be familiar with all the ins and outs. We help you onboard your Software Engineers, ensuring continuous learning about the peculiarities of AI code generation tools and, if needed, on best practices for prompt engineering.
05. Launch the Pilot Project and Evaluate the Results
We help you select relevant tasks and then estimate the results, comparing them between groups that utilized AI and those that did not. We make sure both groups have the same starting point (like clean GitHub and Jira Instances). Then, we measure results using developer surveys, individual meetings, engagement data analysis, and code analysis.
06. Scale the Initiative
If the AI-assisted coding lived up to your expectations, we can scale the AI-assisted software development adoption for your whole department or for other stages of SDLC. We can integrate ready-made solutions or create custom models for project planning, requirements management, behavior-driven design, or code documentation.
AI Coding Assistants: Use Cases
AI-powered development tools boast advanced capabilities, like real-time suggestions, code autocompletion, prediction of the next line of code, and real-time issue detection. By iteratively experimenting with prompts, your software development team can automate or simplify numerous repetitive tasks.
- Code generation & refactoring
- Code review summary
- Legacy code explaining
- Test case generation
- Unit tests generation
- Incident analysis and resolution
Drop Us a LineAbout Your Project
Submit the form below or get in touch with us by email engagement@edvantis.com outlining your project details. You’ll get a response within one business day from an Edvantis expert skilled in your tech stack, industry, or specific business challenge.
It would be a pleasure to work with you.
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