Editorial standards

Our commitment to accuracy.

Every framework, benchmark, and recommendation on Hamming is derived from production data. Here's how we ensure accuracy and transparency.

Our editorial
principles.

Three principles guide every piece of content we publish.

  • Production-based research

    All frameworks, benchmarks, and recommendations are derived from real production data, not synthetic tests or theoretical models.
    • 10M+ mins protected
    • Data from 10K+ voice agents
    • 10+ voice platforms (LiveKit, Pipecat, ElevenLabs, Retell, Vapi, and custom-built solutions)
    • 6+ industries (Healthcare, Finance, Retail, Legal, Insurance, E-commerce)
  • Expert verification

    Content is written or reviewed by voice AI practitioners with hands-on experience building and testing production systems.
    • Authors have deployed voice agents at scale
    • Technical review before publication
    • Frameworks tested across multiple deployments
    • Regular updates as methodologies evolve
  • Transparent conflicts

    We build voice agent testing tools. We're transparent when our content relates to problems our product solves.
    • We clearly identify our own product recommendations
    • Educational content goals come first
    • Frameworks are platform-agnostic where applicable
    • We cite third-party research when available

What our
labels mean.

You'll see these indicators throughout our content. Here's what they signify.

  • Expert verified

    This badge appears on content written or reviewed by voice AI practitioners with production deployment experience.
  • Named framework

    Frameworks like "Hamming's VOICE Framework" represent structured methodologies derived from our production data analysis.
  • Based on 10M+ mins protected

    Statistics and benchmarks citing this are derived from our aggregate analysis of production voice agent deployments.

Corrections and updates

Voice AI moves fast. Benchmarks shift, best practices evolve, and new patterns emerge. We're committed to keeping our content accurate.

  • Articles show "Last Updated" dates
  • Significant corrections are noted inline
  • Outdated frameworks are marked or archived
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Explore our
research.

See the frameworks and benchmarks built from our production data analysis.