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.
- 1M+ production voice agent calls analyzed
- Data from 50+ enterprise deployments
- 10+ voice platforms (Retell, VAPI, Bland, LiveKit, etc.)
- 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 1M+ Calls
Statistics and benchmarks citing this are derived from our aggregate analysis of production voice agent deployments.
Corrections & 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- Outdated frameworks are marked or archived
Explore Our Research
See the frameworks and benchmarks built from our production data analysis.