The Datadog CoScreen team developed an open-source noise suppression library named dtln-rs to enhance real-time collaboration tools for remote work, addressing the challenge of background noise in virtual meetings. This library was created after discovering existing solutions were either too resource-intensive or not easily integrable with WebRTC, the widely used real-time communication software. Dtln-rs is based on the Dual-Signal Transformation LSTM Network (DTLN) and is optimized for speed and portability, allowing it to run efficiently on client devices without server dependencies. Utilizing AI-powered noise reduction, dtln-rs can filter out background noise in real time by analyzing audio data to distinguish between desired signals and noise. This solution, which supports native clients and WebAssembly, aims to provide developers with an accessible tool for embedding high-quality noise suppression in their WebRTC applications. The project underscores the potential of AI in enhancing real-time audio experiences and emphasizes the importance of making advanced technologies available to the open-source community.