Most organizations frequently undervalue the importance of employee surveys, which results in lost opportunities for both reputational and financial improvement. In order to support organizational development, this study recommends a thorough survey approach that incorporates both written and oral feedback responses and takes into account a variety of linguistic preferences. A novel intelligent system that makes use of cutting-edge voice recognition technology is suggested for the smooth collection of feedback. The system that Survey Spark has proposed makes use of state-of-the-art voice recognition technology, allows oral feedback from respondents in their native tongues, and allows text-based feedback input according to user preferences. The sentiment analysis model based on deep learning is an essential element that reveals emotional subtleties in the gathered data. A word cloud visualization shows the terms that respondents use most frequently. This work enhances multilingual speech recognition, supporting 60 global languages, including 5–6 Indian languages. Survey Spark achieves 97% accuracy with voice recognition system and 99% accuracy in sentiment analysis. By merging linguistic diversity and advanced analytics, this system offers insights into the collective employee mindset, enhancing decision-making and organizational efficiency.