M9 Developer is an on-device AI coding assistant that automates over 95% of software development tasks while ensuring sensitive code remains within the user's infrastructure. By integrating directly with existing IDEs like VS Code, it enhances code quality, generates tests, and performs security audits without transmitting data to third-party services.
Funding
Funding not disclosed
Founders
Product
Problem
Software development often involves repetitive tasks such as code generation, testing, and security auditing, which can be time-consuming and prone to errors. Existing AI coding assistants may transmit sensitive code to third-party services, raising concerns about data privacy and security.
Solution
M9 Developer is an on-device AI coding assistant designed to automate over 95% of software development tasks while ensuring code remains within the user's infrastructure. By integrating directly with IDEs like VS Code, the platform enhances code quality, generates tests, and performs security audits without transmitting data to external services. The AI is fine-tuned with company-specific knowledge, including code and documentation, to provide highly contextual and accurate assistance. M9 Developer offers both active and passive modes of operation, allowing developers to guide the AI or have it automatically implement code based on requirements from platforms like Jira.
Target Audience
M9 Developer targets software developers and engineering teams who want to automate repetitive tasks, improve code quality, and ensure data privacy and security.
Features
- On-device operation ensures data privacy and security by keeping code within the user's infrastructure.
- Integration with existing IDEs like VS Code streamlines the development workflow.
- Automated code generation, testing, and security auditing reduce repetitive tasks and improve code quality.
- Context-aware AI is fine-tuned with company-specific knowledge for accurate and relevant assistance.
- Active and passive modes of operation offer flexibility in how the AI is used.
- Automatic generation of unit and integration tests enhances code reliability.
- Code documentation is automatically generated for better maintainability.
- Code quality checks identify issues early in the development process.
- Security audits scan code for vulnerabilities, ensuring robustness.