Poolside is developing a foundation model specifically designed for software engineering, utilizing reinforcement learning from code execution feedback to enhance coding performance. The platform enables businesses to create custom AI models that continuously learn from their unique codebases and practices, improving developer efficiency and software quality.
Funding
$626M 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.
+5Founders
Product
Problem
Software development teams face challenges in maintaining developer velocity and code quality due to the complexities of modern software engineering, including large codebases, diverse technology stacks, and the need for continuous integration and deployment. Existing AI models often lack the specialized knowledge and context required to provide effective code completion, code review, and other developer assistance.
Solution
Poolside offers a suite of AI-powered tools designed to enhance software development workflows. Its core offering is a foundation model specifically trained for software engineering tasks, leveraging reinforcement learning from code execution feedback to improve coding performance. The platform allows businesses to fine-tune this model using their own codebases, documentation, and development practices, creating custom AI models tailored to their specific needs. These custom models can then be integrated into the development environment via a code completion engine and an AI assistant, providing intelligent code suggestions, automated code review, and contextual awareness.
Target Audience
Poolside primarily targets software development teams in regulated industries such as financial services, defense, and technology, as well as retail, tech, and systems integrators seeking to improve developer productivity and software quality.
Features
- Foundation model trained on software engineering tasks using Reinforcement Learning from Code Execution Feedback (RLCF)
- Fine-tuning capabilities using proprietary codebases, documentation, and knowledge bases
- Code completion engine with a large context window, providing real-time code suggestions
- AI assistant integrated into popular code editors for faster code edits and contextual awareness
- Secure deployment options within the customer's own infrastructure, ensuring data privacy and compliance
- Native integrations with popular development tools and platforms
- Code review capabilities with fine-grained control over suggestions