Case Study: Leading Conglomerate Company trains 13-language digital assistant using 7M+ utterances with Shaip

Shaip delivered 7M+ Utterances to build Multi-lingual digital assistant in 13 languages

Leading Conglomerate Company engaged Shaip to build a multilingual digital assistant and faced the challenge of acquiring large volumes of spontaneous utterance data. The client required 3–30 second single‑speaker recordings in 13 languages, diverse speaker demographics and recording environments, transcriptions and JSON metadata, and audio at 16 kHz or higher to train robust conversational AI models.

Shaip provided end‑to‑end audio collection, transcription and annotation, delivering 22,250 hours of audio (7M+ utterances) across 13 languages and supplying corresponding metadata within a 7–8 month timeline. The high‑quality, diverse dataset enabled the Leading Conglomerate Company to accurately train its multilingual speech recognition/digital assistant models, meeting quality and schedule targets and producing gold‑standard training data for production use.