Coding Assistant
Innovate the programming experience and unlock development efficiency
Empower programming work with advanced AI technology, directly address the pain points of code efficiency, quality and retrieval, help enterprise developers significantly improve development efficiency, and ensure high-quality delivery of software projects. In the field of software development, as technology iteration accelerates and business needs become increasingly complex, writing high-quality code has become the most time-consuming and critical task for programmers.
Capabilities
Rich Model Portfolio
Offers a diverse range of model sizes, from advanced to enterprise versions, to meet varying project needs for speed and accuracy.
Question and Answer Module
Combines large models with tens of billions of parameters and the enterprise code repository to deliver precise answers to internal knowledge without relying on the Internet.
Code Completion Module
Enables enterprises to select speed- or accuracy-focused versions and customize code completion performance through upcoming fine-tuning services.
Enterprise Management System
Streamlines user management with simplified account imports, permission adjustments, AB test grouping, and provides intuitive data analytics for real-time monitoring and decision-making support.
Code Fine-Tuning and Business-Specific Code Generation
Leverages existing enterprise resources for fine-tuning large models to generate code aligned with business logic while managing volatility through professional guidance and effect evaluation.
RAG Code Repository and Private Function Generation
Automatically identifies and calls private APIs and functions, reduces erroneous calls through deep learning, and ensures real-time updates to match evolving business needs.
Challenges
Efficiency bottleneck
Code writing takes too long, and traditional methods make it difficult to break through the daily code limit for programmers, affecting project progress and agile response capabilities.
Quality Dilemma
Under the performance pressure of pursuing efficiency improvement, key activities to ensure code quality, such as testing, debugging, and annotation, are often neglected, resulting in low unit test coverage, missing documentation, and a host of potential risks.
Inefficient retrieval
During the development process, developers frequently switch between IDE, web pages, and OA systems to search for information and understand historical codes, which seriously affects their concentration and work efficiency.
Advantages
Improve Coding Efficiency
Automatic code completion offers millisecond-level generation speed, seamlessly integrating into the development process to greatly shorten coding time and reduce manual input for programmers. Additionally, code interpretation and translation quickly parse and clearly present historical code logic, enabling developers to understand and take over legacy projects more efficiently, enhancing team collaboration.
Improve Code Quality
Automatically generating test cases and comments enhances unit test coverage to ensure code robustness while providing standard comments to improve readability and maintainability. Automatic error correction and tuning leverage deep learning algorithms to detect defects in real time, offering targeted suggestions to effectively improve overall code quality.
Improve Search Efficiency
A unified interactive interface integrates various functions, allowing developers to avoid frequent switching between tools, enabling them to focus on programming and significantly improving their productivity.