Case Study
2 Min Read
A leading conversational AI startup based in Germany, building next-gen multilingual voice assistants for consumer electronics and automotive interfaces.
The client needed a high-quality, diverse multilingual dataset for model training—covering over 10 languages and varied demographic segments.
Lack of real-world, natural speech samples
Data inconsistencies across regions
Limited in-house bandwidth to handle annotation and quality control
Savvy Strat delivered an end-to-end data solution, globally executed and tightly managed:
Collected over 500 hours of conversational audio from 10+ countries, using real-life scenarios and diverse speaker profiles
Designed a robust QA framework to validate audio authenticity, demographic diversity, and transcription accuracy
Managed a multi-layered annotation process for speaker diarization, sentiment tagging, and intent classification
Modeled and structured the dataset for immediate deployment in the client’s LLM pipeline
Model accuracy improved by 27% due to higher-quality training data
Reduced time-to-market by 6 weeks
Enabled expansion into 4 new language markets
Client used the dataset to demo a successful product update at CES 2024
"Savvy Strat delivered not just data, but clarity, confidence, and global execution. Their team understands scale and nuance like no one else."
— Head of AI Research, Conversational AI Startup, Germany
