The startup develops a full-stack testing environment software that creates temporary, tailored environments for each code change or pull request, facilitating integration and contract testing. By converting user stories into actionable test cases, the platform enables software development teams to deliver high-quality software with real-time feedback from stakeholders through accessible preview URLs.
Funding
$4M 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.
Founders
Product
Problem
Software development teams face challenges in maintaining code quality and delivering reliable software due to the time-consuming and complex nature of software testing. Traditional testing methods often struggle to keep pace with rapid development cycles, leading to incomplete test coverage and delayed feedback. This can result in increased errors, reduced collaboration, and slower time-to-market.
Solution
Roost.ai provides an AI-powered testing copilot that automates test case generation, enabling software development teams to build reliable software more efficiently. The platform leverages generative AI and large language models to convert user stories, source code, and application logs into actionable test cases for unit and API testing. Roost.ai automatically updates the entire unit test library to ensure tests remain relevant and synchronized with the evolving codebase. By automating repetitive tasks and providing comprehensive test coverage, Roost.ai frees up developer time, elevates test accuracy, and accelerates the software delivery pipeline. The platform offers flexible deployment options, including a command-line interface, a VS Code extension, and a self-hosted Docker solution, to seamlessly integrate with existing development workflows.
Target Audience
Roost.ai is designed for software development teams, QA professionals, and enterprises seeking to automate and accelerate their testing processes, improve code quality, and reduce time-to-market.
Features
- Automated test case generation using generative AI and large language models
- Integration with code repositories such as GitHub, GitLab, Bitbucket, and Azure DevOps
- Integration with platforms like Jira to glean insights from user stories
- Utilizes application logs from sources like Elasticsearch or Amazon CloudWatch
- Automatically updates unit test libraries in response to code changes and pull requests
- Supports unit and API testing across new code, legacy systems, and CI pipelines
- Offers a command-line interface (CLI) for scripting and CI/CD integration
- Provides a VS Code extension for interactive test generation within the IDE
- Supports self-hosted Docker deployments for secure, on-premises environments