Tabnine is an AI coding assistant that provides context-aware code generation, testing, and review tools tailored to individual engineering teams, enhancing software development efficiency. It ensures complete code privacy with zero data retention, allowing teams to produce high-quality, secure code while minimizing intellectual property liability.
Funding
$25M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
TVFounders
Product
Problem
Software development teams face challenges in maintaining code quality, ensuring code privacy, and minimizing intellectual property risks while striving for efficient code generation, testing, and review processes. Traditional coding assistance tools often lack context-awareness and fail to provide adequate protection against data breaches and IP liability.
Solution
Tabnine offers an AI-powered coding assistant tailored to individual engineering teams, providing context-aware code generation, testing, and review tools that enhance software development efficiency. The platform ensures complete code privacy with zero data retention, enabling teams to produce high-quality, secure code while minimizing intellectual property liability. Tabnine's AI agents support the entire software development lifecycle, from code creation and explanation to test and documentation generation and bug fixes. The solution is highly personalized, offering context-aware suggestions based on the user's code and patterns, supporting popular languages, libraries, and IDEs, and providing the ability to create bespoke models trained on the user's codebase.
Target Audience
Tabnine is designed for software development teams seeking to improve code quality, accelerate development cycles, and minimize IP risks.
Features
- Context-aware code suggestions based on existing code and patterns
- Support for popular languages, libraries, and IDEs, including VS Code, IntelliJ, and Eclipse
- Ability to create bespoke AI models trained on a team's codebase
- Code review agent for identifying and suggesting fixes based on team-specific standards
- Testing agent for generating comprehensive test plans and test cases
- Code fix agent for autonomously generating fixes for selected code errors
- Documentation agent for creating documentation for selected code, including API guides and inline docs
- Jira implementation and validation agents for generating code from Jira requirements and validating code to ensure it meets those requirements
- Code explain and onboarding agent for providing plain language explanations of projects, behaviors, and dependencies
- Option for on-premises, VPC, or secure SaaS deployment
- AI-generated code checked against publicly viewable repositories to minimize IP liability
- Provenance and attribution features to minimize IP liability for GenAI output