HE2

Hume EVI 2

Emotion-aware voice AI and empathic interfaces

AI Agents & VoiceVoice AIEmotion detectionEmpathic interfacesReal-time conversation
Function:Customer Support
Subfunction:Call Center / Contact Center
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Founded
2021
Employees
11-50 employees
Funding
~$67.7M total ($50M Series B March 2024)
Stage
Scale-up stage, Series A funding
Report version: Sep 24, 2025

1. Products/Services & Features

  • Main Offerings:

    • EVI 2 (Empathic Voice Interface) - emotion-aware voice-to-voice AI model
    • OCTAVE - next-generation speech-language model with on-the-fly voice creation
    • Expression Measurement APIs - multimodal emotion detection for video, audio, text
  • Feature Breakdown: Real-time emotion detection, customizable personalities, tool integration, phone calling capabilities, sub-second latency (~500ms), voice modulation, developer SDKs (Departments: Customer support, contact centers, healthcare, user research, product development)

  • Business Industry Gearing: B2B SaaS, healthcare, finance, customer-facing industries requiring empathic automation

2. Security & Compliance

  • Certifications: SOC 2 Type II compliant (clean audit by Sensiba San Filippo, LLP), GDPR compliant, HIPAA compliant

  • Vendors/Tools: Role-based access control, API key authentication, likely AWS infrastructure

  • Risk Profile:

    • Breaches: No publicly reported security breaches or compliance gaps
    • Features: Audit trails, role-based access controls, secure API authentication, data export/retention controls, privacy controls portal

3. User Feedback & Adoption

  • Aggregated Reviews: No G2/Capterra ratings yet (recent release); positive expert reviews from Tom's Guide

    • Pros: Highly natural and emotionally expressive voice, customizable personalities/accents, significant cost advantage vs OpenAI
    • Cons: Slightly slower response than some competitors, lacks some human-like features (breathing sounds)
  • Adoption Insights:

    • Adoption Ease: High ease of integration with comprehensive developer documentation and API parity
    • Adoption Cultural Fit: Training modules for cultural embedding, developer-driven fine-tuning for organizational tone matching
  • Metrics: No published NPS or churn rates available

  • Barriers: Legacy voice system entrenchment, technical skepticism around AI empathy claims, ultra-low latency requirements

4. Monetization & Business Model

  • Revenue Model: Hybrid SaaS subscription and API usage-based pricing with enterprise licensing

  • Pricing: Free ($0), Starter ($3), Creator ($14), Pro ($70), Scale ($200), Business ($500), Enterprise (custom) (Sources: Official Hume AI pricing page (https://www.hume.ai/pricing))

  • Market Context:

    • TAM: Low single-digit billions USD in emotion-aware voice AI sector
    • Growth Stage: Scaling/high-growth stage with rapid product releases and enterprise expansion

5. Leadership & Recent Developments

Name Description LinkedIn X Account
Alan Cowen CEO & Chief Scientist, PhD in Computational Psychology from UC Berkeley, former researcher at Google and Facebook https://www.linkedin.com/in/alan-cowen/
  • Key Metrics Update:

    • Funding: Series A funding underway (amount not disclosed)
    • Employee Growth: Not disclosed
  • News/Trends:

    • News Launch: OCTAVE launched December 2024, EVI 2 publicly released September 2024
    • News Partnerships: Anthropic partnership integrating EVI 2 with Claude models for sophisticated voice interactions
    • News Funding: Series A funding round in progress
    • News Challenges: No explicit business challenges reported; focus on ethical voice modulation and competitive differentiation

6. Target Audience & Use Cases

  • Target Market: B2B organizations prioritizing emotional intelligence, especially SaaS, healthcare, finance, customer-facing industries

  • Target Users & Personas: Product/engineering teams, CX/UX professionals, contact center managers, support operations

  • User Experience Level: Developers via APIs and SDKs; business users via conversational UI; both entry-level and power users supported

  • Key Use Cases:

    • Automating and enhancing customer service with empathetic AI agents for call centers
    • Building interactive virtual assistants and research companions for complex decision-making
    • Real-time sentiment and emotion analytics for marketing campaigns and user testing

7. Impact & Recommendations

  • Measurable Outcomes:

    • Workflow Improvements: Reduced agent workloads, improved customer satisfaction through emotional awareness, faster response times
    • ROI Examples: Improved CSAT through emotion-aware responses, cost savings in call center operations
  • Fit Assessment: Strong fit for B2B organizations needing empathic customer interactions and emotional intelligence in voice AI

  • Custom Rec Flags:

    • Priority ICP: High-growth SaaS companies, healthcare organizations, finance firms with customer-facing operations
    • Short Term Goals: Scale API adoption, expand enterprise partnerships, enhance emotional intelligence capabilities

8. Data Sourcing Notes

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