Abstract: AppTek participated in the subtitling and formality tracks of the IWSLT 2023 evaluation. This paper describes the details of our subtitling pipeline - speech segmentation, speech recognition, punctuation prediction and inverse text normalization, text machine translation and direct speech-to-text translation, intelligent line segmentation - and how we make use of the provided subtitling-specific data in training and fine-tuning. The evaluation results show that our final submissions are competitive, in particular outperforming the submissions by other participants by 5% absolute as measured by the SubER subtitle quality metric. For the formality track, we participate with our En-Ru and En-Pt production models, which support formality control via prefix tokens. Except for informal Portuguese, we achieve near perfect formality level accuracy while at the same time offering high general translation quality.