Reflex helps companies build production web applications in Python. We were excited to lead its $14 million Series A because it gives teams a way to use AI without abandoning the code, data, and expertise they already have. The opportunity is not just to make prototypes faster. It is to help companies build software they can understand, maintain, and run.
Founders Alek Petuskey and Nikhil Rao started with a gap in the Python ecosystem. Teams used Python for machine learning, data analysis, and backend services, but turning that work into a web application often meant learning another language or handing it to a separate frontend team. Reflex lets developers build the interface and the logic behind it in Python.
The company began as an open-source project, not an enterprise software sales operation. Developers tried it, built applications, and shared them inside their companies. In the interview, the founders describe how those users helped shape the commercial platform: the framework got them started, while deployment, authentication, and integration with existing systems became the next problems to solve.
AI makes that foundation more useful. A Python team can generate an application and still read and debug the result. That matters when the application connects to real company data or supports a business process. A convincing demo is not enough; someone has to understand what the code does and take responsibility for it.
The World Bank illustrates the difference. Its team used Reflex to build an internal document chatbot and data-review dashboards on top of its existing Python services. The applications run in the Bank’s own cloud environment. The team could reuse its data systems and build the interface without adding a separate JavaScript stack.
Reflex has built beyond the framework with an AI app builder and tools for deploying and managing applications. Teams can run software on Reflex’s infrastructure or their own. The enterprise platform adds controls such as single sign-on, permissions, and audit logs—the work that becomes important when an experiment turns into something people rely on.
The same open-source community has helped shape the team. The founders describe hiring early engineers from contributors who already used the framework and wanted to improve it. Building tools for other developers gives them a direct way to see what works: their users can inspect the code, report problems, and contribute fixes.
Reflex’s current approach also addresses the work around the code. In its Series A announcement, the company describes a “software factory”: engineers work with customers to understand their processes, connect their data, check business logic, and put applications into production. Customers own the finished applications and can use the AI platform to change them or build new ones.
The ambition is to make custom software practical for more businesses. As AI makes applications easier to create, connecting them to existing systems and keeping them reliable becomes more important, not less. Reflex is building from an open Python foundation toward that larger job.
Learn more at reflex.dev