Hive Moderation
Content moderation tools software
- Features
- Ease of use
- Ease of management
- Quality of support
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What is Hive Moderation
Hive Moderation is an API-based content moderation product that uses machine learning models to detect and classify potentially unsafe or policy-violating content in images, video, and text. It is used by platforms and developers that need automated pre-screening, triage, or enforcement support for user-generated content workflows. The product typically integrates into upload pipelines and trust & safety tooling via REST APIs and returns labels/scores that can be mapped to customer policies. It differentiates through broad model coverage across multiple media types and an emphasis on developer-oriented integration.
Multi-modal moderation coverage
Hive Moderation supports automated analysis across common user-generated content formats, including images, video, and text. This helps teams apply consistent policy checks across multiple surfaces (e.g., profile photos, posts, comments, and uploads). Multi-modal support can reduce the need to stitch together separate point solutions for each media type. It also enables unified routing to human review based on risk scores and categories.
API-first integration model
The product is designed to be consumed as an API, which fits typical content ingestion and upload workflows. Engineering teams can call moderation endpoints synchronously for gating or asynchronously for post-publication review. API responses (labels and confidence scores) can be used to implement configurable thresholds and escalation rules. This approach aligns with how many moderation stacks integrate detection services alongside case management and enforcement systems.
Configurable policy enforcement workflows
Hive Moderation outputs structured classifications that can be mapped to an organization’s specific policy definitions and enforcement actions. Teams can implement different thresholds by region, user segment, or content surface without changing the underlying model. This supports operational workflows such as auto-block, allow, quarantine, or send-to-review. It also enables measurement of false positives/negatives through downstream review outcomes.
Limited transparency on models
As with many hosted moderation APIs, customers may have limited visibility into training data, model updates, and category definitions beyond published documentation. Model behavior can change over time as vendors update classifiers, which can affect policy outcomes. This can require ongoing calibration of thresholds and monitoring of drift. Some regulated or high-risk use cases may require more explainability than a black-box API provides.
Customization may require vendor
If a team needs highly domain-specific categories, language variants, or bespoke policy taxonomies, out-of-the-box labels may not fully match requirements. Custom model training or specialized classifiers may not be available in self-serve form and can require vendor engagement. This can increase implementation time for niche communities or specialized marketplaces. It may also complicate comparisons across internal policy versions if label sets change.
Operational dependence on API
Using a hosted API introduces dependency on external uptime, latency, and rate limits in the critical path of content publishing. High-volume platforms may need careful architecture (batching, async queues, fallbacks) to manage cost and performance. Data residency and retention requirements can also constrain where and how content is processed. These factors can be limiting for organizations that require on-prem deployment or strict regional processing controls.
Plan & Pricing
Pricing model: Pay-as-you-go Free tier/trial: $50+ in free credits after adding a payment method; V3 Playground (developer demo) offers 100 requests/day for testing.
Example costs (official model pages):
- OCR (image): $1.50 per 1,000 requests.
- OCR (video): $0.10 per minute.
- Multimodal / Vision Language Model (VLM): $0.50 per 1,000,000 input tokens; $2.50 per 1,000,000 output tokens.
- Image generation (SDXL): $3.00 per 1,000 images (SDXL); $4.00 per 1,000 images (SDXL Enhanced).
- Speech-to-Text: $0.02 per minute.
- Text translation: $10.00 per 1,000,000 characters.
Visual Moderation & Text Moderation: Hive describes Visual Moderation and Text Moderation as usage-based products on the public pricing page and documents their APIs in detail, but I could not find per-call or per-request public prices for the Visual Moderation and Text Moderation classifiers on the vendor site. Enterprise/High-volume options (including the Moderation Dashboard and seat-based subscriptions) are offered via custom/enterprise pricing (contact sales).
Discount options: Enterprise/custom pricing and higher-rate limits available via Sales; contact for volume/commitment pricing.
Notes & source scope: All data pulled only from Hive's official website (pricing page, API/model pages, and documentation). If you need me to attempt a sales contact to obtain explicit Visual/Text Moderation per-call pricing, I can draft an email or request template.
Seller details
Hive AI, Inc.
San Francisco, CA, USA
2015
Private
https://thehive.ai/
https://x.com/thehive_ai
https://www.linkedin.com/company/thehive-ai/
