Hume AI provides an emotional intelligence layer for next-generation AI applications. As basic AI capabilities become similar in core functions, emotional intelligence differentiates applications requiring human-like interaction.
While many companies focus on making AI smarter, Hume AI makes AI more emotionally intelligent—a capability that adds value as AI expands into healthcare, customer service, education, and domains where emotional understanding matters. Its technology functions as emotional intelligence middleware for AI systems.
Founding and Funding
Dr. Alan Cowen (former Google AI researcher, creator of "semantic space theory") and John Beadle founded Hume AI in 2021.
- Total Funding: $67.7 million
- Seed Round: $5 million in March 2021, led by Aegis Ventures. Northwell Holdings contributed $3 million
- Series A: $12.7 million in January 2023, led by Union Square Ventures
- Series B: $50 million in March 2024, led by EQT Ventures
- Key Investors: EQT Ventures, Union Square Ventures (Andy Weissman), Comcast Ventures, LG Technology Ventures, Northwell Holdings, Nat Friedman, Daniel Gross, and Metaplanet (Jaan Tallinn)
Product
Hume AI offers several core products:
- EVI: A voice-to-voice conversational AI launched in March 2024 that recognizes and responds with emotional expression
- Expression Measurement API: Analyzes facial expressions, vocal intonations, and text, measuring 48 distinct emotional dimensions
- Octave: A text-to-speech model designed for expressive voice synthesis
- LLM Integration: Integrates with LLMs including Anthropic's Claude and OpenAI's GPT-4. According to Anthropic, 36% of Hume users select Claude, and integration achieved 80% cost reduction through prompt optimization
- Usage: As of early 2024, users completed over two million minutes of AI voice conversations through the platform
Current competition
1. Affectiva (Acquired by Smart Eye)
- Founded: 2009 (MIT Media Lab spin-off)
- Total Funding: $60 million before acquisition
- Product: Emotion AI software detecting human emotions through facial expression analysis, used for automotive sensing, media analytics, and market research
- Strengths: Early facial expression analysis; large dataset; market presence with Fortune 500 clients