Hive Moderation is an AI content moderation system. It helps platforms screen text, images, video, audio. It flags harmful content, deepfakes, spam, nudity, hate speech, etc.
It offers you peace of mind so your community stays safe.
It gives you APIs + a no-code moderation dashboard. You set rules, view flagged items, escalate when needed. It’s built for scale and speed.
Why Hive Moderation matters
In user-generated platforms, bad content spreads fast. You can’t rely only on humans. Hive uses machine learning to automate content filtering.
That’s key for trust & safety. It prevents brand risk, protects users, and keeps moderation costs manageable.
Also, because it supports multiple media types, you don’t need separate systems for text vs video vs images. That unified approach is a big plus.
Core capabilities
Here are what Hive brings to the table:
- Text moderation: Detect profanity, hate speech, threats, spam, misleading content.
- Visual moderation: Spot nudity, violence, graphic imagery, disallowed content.
- Audio moderation: Review speech or sound for abusive language.
- Deepfake & synthetic content detection: Identify AI-generated images or manipulated media.
- OCR moderation: Extract text from images & moderate that too.
- Custom training / AutoML: You can fine-tune models for your niche content.
- Moderation dashboard & workflow tools: No code interface to assign, review, escalate content.
- Media search & duplicate detection: Helps you find content variants, spam copies.
They also support a “Moderation Dashboard” so non-tech staff (trust & safety teams) can manage flagged content without code.
Pricing talk & what you’ll pay
Hive uses usage-based pricing. You pay per 1,000 requests or per minute (for audio/video).
For example:
- Text moderation is $0.50 per 1,000 requests
- Visual moderation is $3.00 per 1,000 requests
- OCR (image) moderation is $2.00 per 1,000 requests
- Audio moderation is $0.03 per minute
- For video OCR: $0.13 per minute
If you have heavy volume, you contact sales and get enterprise pricing.
So your cost scales with traffic. If you moderate 100,000 images, that’s ~$300 (for visual) + extras.
Pros
- Covers many content types (text, image, audio, video) in one place
- Deepfake / synthetic AI detection is very useful
- Custom model training offers flexibility
- Dashboard helps team workflows easily
- Pay-as-you-go model: you only pay for what you use
Cons
- For small projects, costs may add up
- Some advanced features need enterprise deals
- If your content is very niche, base models may need tuning
- Latency could matter under extreme scale
Traffic & social reach
I couldn’t find a reliable “monthly visitors” number for Hive Moderation’s site. The parent Hive AI is fairly established though and works with big platforms. Hive’s brand is recognized.
As for social media followers, I found no consolidated public number for all platforms. They maintain presence on LinkedIn, Twitter, etc. But no confirmed total is published.
Use in real world
One interesting case: Highrise (a large avatar-based social network) used Hive Moderation to scale its content safety. That shows Hive can handle big, real use.
Also, Hive’s moderation API is used by big names like Reddit (for content filtering). Hive’s models have been used in livestreaming contexts too.
Tips for best results
- Always test on real content. AI tool models are only as good as your sample data.
- Use human review fallback for ambiguous cases.
- Regularly retrain with false positives/negatives.
- Use moderation dashboards so your team can see context, override.
- Monitor cost per 1,000 requests and adjust thresholds to trade off precision vs scale.
