An intelligent code review service that takes context into account
Time-consuming code checks are now a thing of the past for the developers of a major German car manufacturer. This is made possible by an AI-based solution from Ki Reply, which not only checks the general quality of the code but also considers the company's specific conditions.
#AI-powered development
#Code improvement
#Automotive industry
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The challenge
"Good" code is not always "good" code.
The scenario
Avoid media breaks & boost tailored solutions
Consistent, maintainable, scalable, efficient: the list of attributes that "good" code should fulfill is long and the specific requirements are constantly evolving. This is why many developers use tools that check the code for possible errors. Unfortunately, these only take stylistic aspects and technical rule violations into account. This means that the specific requirements of the company are often ignored. But what "good" code looks like always depends on the specific conditions. In addition, such code review tools are often not directly integrated into the development environment. This increases the time required, as developers have to manually transfer suggested adjustments.
To avoid this media break and to enable convenient and tailored reviews, a major German car manufacturer therefore commissioned Ki Reply to develop a specialized code review service.
The solution
Analyzing the context with the help of AI
Today, the car manufacturer benefits from an intelligent AI-supported code review service that is directly integrated into the Gitlab development environment. It also pays attention to the context when evaluating the code. To achieve this, it analyzes user stories, for example, considers possible quality and security problems and takes into account code adjustments that have already been made in the past. An incredibly large amount of data in the case of the car manufacturer, which conventional AI models cannot easily process due to their token limit. However, the solution from the experts at Ki Reply condenses the material with the help of various integration strategies. The information and quality thereby remain unchanged. Thanks to this approach, the service is able to suggest precisely tailored improvements for the code to be checked. It lists them in a standardized manner, thus facilitating traceability and collaboration within the development team. In addition, the code review service is also able to implement the proposed changes itself if required.
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The concept behind it
Support along the entire development life cycle
The new code review service runs on AWS and uses the Large Language Model (LLM) from Azure OpenAI. At the heart of the solution are three special AI agents that perform the different code review steps completely automatically.
Their interaction is managed by a multi-agent system, the KICODE Reply framework from Ki Reply. This supports developers along the entire Software Development Life Cycle (SDLC). In this way, Ki Reply's experts ensure that the new agents not only master their task perfectly but also deliver future-ready results. At the same time, the code review service is compatible with other multi-agent systems and thus offers maximum flexibility.
The advantages
Fast and innovative
Ki Reply's new AI-supported Code Review Services enables the automotive manufacturer to:
Improve code quality
Recommendations tailored to the context
Orientation towards proven best practices
Early detection of problems
Better overview of changes
No media breaks during the code check
Higher productivity
Facilitated collaboration within the development team
Faster time-to-market
Relief of employees from repetitive tasks
More capacity for innovative projects
Ki Reply
Ki Reply is a service provider for AI-driven software development and supports companies in making software development more efficient and powerful with the help of artificial intelligence (AI) and machine learning. In addition to conventional software development, the experts at Ki Reply also use low-code platforms to realise and optimise business use cases more quickly. Companies benefit from time savings when testing IT solutions, a shorter time-to-market and high-quality software.