Meeting transcription for SaaS applications involves complex challenges due to platform-specific limitations and the need for accurate, automated, and reliable audio-to-text conversion. Developers face a decision between building custom transcription stacks or leveraging APIs to streamline audio capture and processing. Effective transcription requires robust audio processing, speaker diarization, real-time or batch processing, compliance with enterprise standards, and support for multiple languages and custom vocabularies. A variety of APIs, such as AssemblyAI, Deepgram, OpenAI Whisper, AWS Transcribe, Speechmatics, and Nylas Notetaker, offer different benefits and limitations depending on the use case, such as latency, accuracy, deployment options, and integration capabilities. Nylas Notetaker, for instance, simplifies integration with major platforms like Zoom, Teams, and Google Meet, offering built-in transcription and calendar synchronization. Developers must consider factors like audio capture complexity, accuracy requirements, language support, compliance, real-time processing needs, and budget when choosing a transcription solution. Testing with real-world audio data is crucial to address platform-specific challenges and achieve the desired transcription quality.