# Harver: how AI models rank it, September 2026

HR AI Recommendation Index, September 2026 Edition. Named in 18 judge labels across 4 categories by 9 of 12 models. Page: https://hr-ai-index.com/vendors/harver/

## Standing by category

| Category | Share | Rank | Negative rate | Labels |
|---|---|---|---|---|
| Candidate assessment | 0% | 15 | 9% | 11 |
| Video interviewing | 0% | 31 | 50% | 4 |
| Skills intelligence | 0% | 57 | 0% | 2 |
| AI recruiting assistants | 0% | 73 | 100% | 1 |

## What the models said for it

- "Choose Harver if: You need to hire hundreds or thousands of frontline employees quickly" (Qwen 3.7 Flash, Candidate assessment)
- "High-volume frontline/ops hiring → Harver or Sova" (DeepSeek V4 Flash, Candidate assessment)
- "Best for: High-Volume Enterprise Hiring" (Kimi K2, Candidate assessment)
- "Best for Volume Hiring: Harver" (GLM 4.7 FlashX, Candidate assessment)

## And against it

- "Avoid enterprise-only solutions (like Harver) unless you have truly massive hiring volume, as they're likely overkill and overpriced for 500 employees." (Kimi K2, Candidate assessment)
- "Avoid tools like HireVue or Harver unless you are managing extremely high-volume, enterprise-scale recruitment campaigns" (Gemini 3.5 Flash, Video interviewing)
- "Tools like some iterations of *Harver* or *Graphology* tests ... frequently criticized for lacking psychometric validity" (DeepSeek V4 Flash, AI recruiting assistants)
- "Not suitable for professional/white-collar roles; requires long implementation times; steep learning curve." (Qwen 3.7 Flash, Video interviewing)

## Record

- Method: https://hr-ai-index.com/methodology/
- Raw judge labels and full responses: https://hr-ai-index.com/data/
- License: CC BY 4.0. Cite as HR AI Recommendation Index, September 2026 Edition, hr-ai-index.com.