Unlock the Emotional Pulse of Conversations with Pulse API
Real-time Emotion Detection for
Customer Intelligence
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Team communication
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Digital accessibility
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Customer Intelligence - Team communication - Digital accessibility -
AI-Powered Communication Insights
With Pulse API, gain insights into emotional subtleties in real-time conversations and elevate your sales, customer support, and team collaboration.
How Pulse works
Deep learning for tonal analysis
10+ Emotion Classes
Edge Capability
Real-time classification
Voice Centered
Secure Data Collection and Storage
92% accuracy for North American English
It’s all going virtual
80% of B2B sales are expected to be conducted virtually by 2025*
Emotional miscommunications are expensive for businesses and people. By better understanding your clients and your team, you can alleviate the guesswork and strengthen connection in digital spaces.
*Gartner’s The Future of Sales Report
Emotional Intelligence = Business Intelligence
☆ 70% of buyer decisions are driven by emotional factors, but current digital communication tools lack emotional context ☆
☆ NPS scores are subjective and don’t provide actionable insights ☆
☆ Recent advancements in generative AI are calling us to humanize our relationships in digital spaces ☆
Our AI is built using advanced machine learning techniques and inspired by principles from computational neuroscience, allowing our processing to mimic and augment the human brain's ability to process vocal tone¹ ².
We've developed state-of-the-art emotion classification models, ensuring accuracy and reliability in identifying nuanced emotional states³.
We have a strategic partnership with SRI International to ensure our data is robust and representative of the vocal diversity of North American English speakers⁴.
Backed by Science
¹ K. Rangra and M. Kapoor, “Exploring the mel scale features using supervised learning classifiers for emotion classification,” Int. J. Applied Pattern Recognition, vol. 6, no. 3, 2021, pp. 232-532, doi: 10.1504/IJAPR.2021.117204.
² S. A. Kotz, C. Kalberlah, J. Bahlmann, A. D. Friederici, and J.-D. Haynes, “Predicting vocal emotion expressions from the human brain,” Human Brain Mapping, vol. 34, no. 8, pp. 1971–1981, 2012. doi:10.1002/hbm.22041
³ F. Abtahi, T. Ro, W. Li and Z. Zhu, "Emotion Analysis Using Audio/Video, EMG and EEG: A Dataset and Comparison Study," 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Tahoe, NV, USA, 2018, pp. 10-19, doi: 10.1109/WACV.2018.00008.
⁴ J. Smith, A. Tsiartas, V. Wagner, E. Shriberg and N. Bassiou, "Crowdsourcing Emotional Speech," 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, AB, Canada, 2018, pp. 5139-5143, doi: 10.1109/ICASSP.2018.8462224.
Customer Intelligence
Harness the power of emotion AI to gain deeper insights into customer sentiments and emotional responses, enabling you to tailor your products and services to meet their needs and preferences more effectively.
Applications of Pulse AI
Digital Accessibility
Ensure a more inclusive and empathetic digital experience by using emotion AI to enhance accessibility across the team, making your digital spaces more user-friendly and accommodating to people with different communication styles.
Qualitative Research
Elevate your qualitative research efforts by integrating emotion AI to capture and analyze emotional nuance in your research subjects' responses, providing richer and more actionable insights for your studies.
