An automated content moderation platform from the US AI company Hive (thehive.ai). Send user-submitted images, video, text, or audio to the API, and AI returns a real-time assessment of possible policy violations such as violence, sexual content, hate speech, drugs, and weapons. In recent years the company has invested heavily in detecting AI-generated images and deepfake audio and video, and the platform is used by operators of user-generated services and communities to hand off the volume of checking that human teams can no longer keep up with. Hive is said to process billions of pieces of content per month, and the platform is designed for large-scale enterprise operation.
Key Features
- Four modalities through one API: Images and video (Visual Moderation), text (Text Moderation), and audio (Audio Moderation) are all handled on the same platform. Post images on a social app, frames from a live stream, chat messages, and voice chat audio can be checked in one place instead of stitching together several vendors
- Fine-grained classes with confidence scores: Rather than a binary “inappropriate or not,” the API returns a confidence score for each of many classes such as sexual content, violence, weapons, drugs, and gambling. You decide where to draw the line, so the same API can be tuned differently for an adults-only community and a kid-facing app
- AI-generated content and deepfake detection: Dedicated models judge whether an image, video, or audio clip was produced by generative AI. As generative tools spread and impersonation and disinformation posts increase, this addresses a risk that sits on a different axis from ordinary moderation. Adoption by US government agencies has been reported
- Reads text baked into images and video (OCR Moderation): Text rendered inside an image or video is extracted and then evaluated. This covers the tactic of embedding banned advertising or spam as pixels, which pure text checks would miss
- Moderation Dashboard and bulk processing: Results can be reviewed in a management UI, with local file uploads (10–100 items) and bulk CSV submission (up to 50,000 items). Results export to CSV, and role permissions such as Collaborator, Read, Write, and Admin are available
- Flexible judgments with a Vision Language Model: Alongside fixed-class classifiers, Hive offers a VLM that evaluates content against a policy written in natural language ─ an option when your rules do not map onto the existing classes
Pricing
| Plan | Price | Highlights |
|---|---|---|
| Developers | Pay-as-you-go (over $50 in free credits after adding a payment method) | Self-serve access to major models, 10+ Hive models, default rate limits, custom model training via AutoML |
| Enterprise | Contact sales | Access to all models and the Moderation Dashboard, higher rate limits for large-scale traffic, premium support from experts, multi-region support |
Key pay-as-you-go unit prices are as follows.
| Use | Unit price |
|---|---|
| Visual Moderation (image / video) | $3.00 / 1,000 requests |
| Text Moderation | $0.50 / 1,000 requests |
| Audio Moderation | $0.03 / minute |
| OCR Moderation (image) | $2.00 / 1,000 requests |
| OCR Moderation (video) | $0.13 / minute |
| AI image + deepfake classifier | $6.00 / 1,000 requests |
| AI video detection | $6.00 / 1,000 frames |
| AI audio classifier | $10.00 / audio hour |
Note that some models, including CSAM (child sexual abuse material) detection and face detection, have no published unit price and require a separate inquiry.
Pricing is as of August 2026. Check the official site for the latest details.
Pros & Cons
✅ Pros
- Images, video, text, and audio are covered by a single vendor’s API, which simplifies the design and operation of a moderation stack
- Per-class scores let you draw precise lines between “auto-remove,” “hold for human review,” and “publish as-is” according to your service’s policy
- Covers AI-generated content and deepfake detection, an area that general-purpose moderation APIs often handle only thinly
- Free credits after registering a payment method let you test accuracy on your own content before committing
- A track record on large platforms means fewer concerns about scaling as traffic grows
⚠️ Cons
- Not aimed at individuals or hobby projects; in practice this is a service for businesses
- Pay-as-you-go pricing makes monthly cost hard to predict for high-volume services, so estimating up front is essential
- AI judgments are not perfect ─ false positives and misses will happen, so the design must include a human review process for final decisions
- Some models have undisclosed pricing, making the total cost hard to grasp early in evaluation
- The judgment criteria are close to a black box, so a mechanism to explain to users why a post was blocked has to be built in-house
Comparison with Similar Services
| Item | Hive Moderation | Amazon Rekognition Content Moderation | Sightengine | OpenAI Moderation API |
|---|---|---|---|---|
| Provider | Hive (US) | Amazon Web Services (US) | Sightengine (France) | OpenAI (US) |
| Modalities | Image, video, text, audio | Image, video (text is a separate service) | Image, video, text | Text, image |
| AI-generated / deepfake detection | Yes (dedicated models) | Limited | Yes | No |
| Pricing model | Pay-as-you-go + Enterprise | Pay-as-you-go (billed through AWS) | Pay-as-you-go / monthly plans | Free |
| Best suited for | Comprehensive safety for large platforms | Embedding into systems already on AWS | Lightweight adoption by smaller services | Guarding input and output of your own LLM app |
Hive is the natural centerpiece when you want audio covered end to end alongside everything else, or when AI-generated content detection matters. If your stack is already AWS-centric, Rekognition fits; if you want to start small, Sightengine; and if you only need to guard an LLM app’s input and output, OpenAI’s free API is enough. The right choice depends on the goal.
Who Is It For
- Operators of user-generated services ─ social apps, forums, dating apps ─ where manual checking of policy violations no longer keeps up
- Services handling live streaming or voice chat that need to monitor both video and audio in real time
- Operations teams that want concrete countermeasures against impersonation images and synthetic voices produced by generative AI
- Marketing and adtech companies that need to guarantee brand safety of ad placements and creatives programmatically
- Development teams currently juggling several moderation vendors who want to consolidate to a single API and point of contact
Summary
Hive Moderation is a moderation platform that covers four formats ─ image, video, text, and audio ─ through one API, and goes further into judging AI-generated content and deepfakes. Because it returns per-class scores, it is easy to combine automated handling with human review in a way that fits your service. It is worth evaluating at the point where post volume outgrows manual patrolling, though you should settle your pay-as-you-go cost estimate and your human-side workflow for false positives before adoption. A good starting point is to run your own real data through the free credits and get a feel for accuracy and thresholds.