Sightengine is an API-first content moderation service for image, video, and text classification. You send content, get back confidence scores, and handle the rest yourself. It's minimal by design, meaning no workflow layer, no human review, and no bundled infrastructure.
That works well for teams who want direct model access and tight control over their moderation logic. It's less suited to teams that need audio moderation, compliance tooling, real-time chat integration, or out-of-the-box human-in-the-loop escalation.
This guide compares Sightengine to nine alternatives — from lightweight API tools to full enterprise platforms — to help you find the right fit for your use case.
What is Sightengine?
Sightengine is used by platforms across social networking, dating, marketplaces, and gaming. Its models are trained specifically on user generated content (not generic image recognition datasets), which separates it from cloud vision APIs.
Its 120+ moderation classes are more granular than most competitors:
- Nudity splits into sexual activity, erotica, underwear, bikini — each scored separately
- Violence distinguishes real vs. illustrated gore, weapons in context, graphic injury
- Hate content separates symbols, gestures, and extremist imagery individually
This granularity gives you meaningful threshold control rather than a blunt pass/fail, which is useful when your platform has nuanced content policies that differ by audience or region.
Pricing
- Free: $0 — 2,000 operations/month (max 500/day), 1 simultaneous video stream
- Starter: $29/month — 10,000 operations + $0.002 per additional op, 1 video stream
- Growth: $99/month — 40,000 operations + $0.002 per additional op, 2 video streams
- Pro: $399/month — 200,000 operations + $0.0015 per additional op, 5 video streams
- Enterprise: Custom pricing
Sightengine Versus the Top 9 Alternatives
Below is a side-by-side look at how Sightengine compares to nine moderation platforms across features, pricing, and key differentiators.
Sightengine vs. Stream
Stream is an AI-powered content moderation platform that combines automated classification with a full moderation operations layer. This includes human review queues, no-code policy configuration, audit logs, and a moderator dashboard built for trust and safety teams.
The key architectural difference is that Stream gives you both the detection and the workflow to act on it. Sightengine returns a confidence score; Stream returns a confidence score, routes the content, applies a configured action, surfaces it in a review queue, and logs the decision.
Comparison Chart
| Feature | Sightengine | Stream |
|---|---|---|
| Text moderation | Profanity, hate speech, spam; returns confidence scores | Profanity, hate speech, spam + LLM-based contextual analysis across 50+ languages |
| Image & video moderation | Deep subcategory scoring (e.g., nudity broken into 8+ subclasses) | Nudity, violence, weapons, drugs + OCR text detection within images |
| Contextual analysis | ❌ | Understands nuance; sarcasm, indirect threats, conversation context |
| Human review queue | ❌ | Built-in queue with contextual views to reduce reviewer fatigue |
| No-code policy builder | ❌ | Define if/then rules per channel or content type without engineering work |
| DSA / GDPR compliance tooling | ❌ | Audit logs, appeals workflow, EU + US data residency options |
The core tradeoff: Sightengine is a classification API. Stream is a moderation platform. If your team needs to go from flagged content to a resolved decision (with accountability, reviewer tooling, and policy enforcement), Sightengine will require you to build all of that on top. Stream includes it.
Stream Pricing
Pay-as-you-go:
- Messages: $2.00 per 1,000
- Images: $4.00 per 1,000
- Video: $0.80 per minute
- Live video: $4.00 per 1,000 frames
- Includes dashboard for 3 moderators, 40 AI harm engines, semantic filtering, LLM engine, rule builder
Enterprise:
- Contact sales for pricing
- Includes unlimited moderators, SAML/SSO, 99.999% SLA, NLP engine, facial recognition, OCR, dedicated AWS region
Stream also offers a free tier with $100 in monthly credits across messages, images, and video.
Sightengine vs. Hive Moderation
Hive is an AI model platform offering content moderation APIs for image, video, text, and audio. On the surface, it looks similar to Sightengine with its REST API, confidence scores, and multi-modal coverage. However, they differ in model depth, classification architecture, and what's available at the enterprise tier.
Hive's visual moderation uses a multi-headed model where each head covers a distinct category (nudity, weapons, drugs, etc.) and returns a full probability distribution across subclasses that sum to 1. Sightengine uses per-class confidence scores. This matters when you're building automated enforcement logic, since Hive's outputs are more directly usable as mutually exclusive classifications.
| Feature | Sightengine | Hive |
|---|---|---|
| Image moderation | Confidence scores across 120+ subclasses | Multi-headed model returning probability distributions per category; generally stronger for automated enforcement logic |
| Text moderation | Profanity, hate speech, PII detection, URL filtering, leet speak and obfuscation detection | Same categories, plus PII detection (email, phone, address) and pattern-matching built in by default |
| Audio moderation | Limited (profanity detection only) | Full audio moderation with multi-level severity results |
| VLM / contextual analysis | ❌ | Moderation 11B VLM; fine-tuned on Llama 3.2, handles contextual and cross-modal violations |
| Custom model training | ❌ | AutoML for custom text and image classifiers, including fine-tuning and full training |
| Moderation dashboard | ❌ | Available at enterprise tier; includes human review queue, user history tracking, and automated enforcement rules |
The core tradeoff: Both are API-first moderation tools, but Hive goes deeper on model architecture, adds a VLM layer for contextual reasoning, and offers a moderation dashboard with human review at the enterprise level. Sightengine is simpler to get started with and has more transparent self-serve pricing, but you'll hit its ceiling faster if your use case grows in complexity.
Hive Pricing
Pay-as-you-go:
- Visual moderation: $3.00 per 1,000 requests
- Text moderation: $0.50 per 1,000 requests
- Audio moderation: $0.03 per minute
- Free tier: 100 requests/day via playground; $50+ in credits after adding a payment method
Enterprise:
- Contact sales
- Includes access to all Hive models and moderation dashboard; higher rate limits, premium support, multi-region deployment
Sightengine vs. ActiveFence (by Alice)
ActiveFence, now rebranded as part of Alice, is an enterprise trust and safety platform that combines AI-powered content detection with a full moderation operations layer and a continuously updated threat intelligence database. It covers text, image, video, and audio across 117+ languages and is built around a fundamentally different operational model than Sightengine.
Sightengine is a classification API: you call it, get a score, decide what to do.
ActiveFence is designed around the idea that moderation is an ongoing operation. Its models are continuously informed by a team of trust and safety researchers tracking emerging threat patterns and feeding those signals back into detection. That's a meaningful advantage in categories like CSAM, extremism, and coordinated inauthentic behavior.
| Feature | Sightengine | ActiveFence |
|---|---|---|
| Detection scope | Standard UGC categories (nudity, violence, hate speech, spam) | 20+ abuse areas including extremism, CSAM, grooming, disinformation, election interference, and fraud |
| Threat intelligence | ❌ | 24/7 monitoring across clear, deep, and dark web; continuously updated adversarial data including domains, IPs, hashes, and behavioral signals |
| Moderation operations | ❌ | SaaS tooling (ActiveMind) with LLM-powered review, automated enforcement, and moderator queue management |
| Human review | ❌ | Dedicated global teams of analysts and policy experts available for escalation and investigation |
| DSA / compliance tooling | ❌ | Reporting and accuracy tooling built to meet evolving regulatory standards |
| Scale | Self-serve, limited rate limits on lower tiers | 750M+ daily signals analyzed; built for platforms protecting billions of users |
The core tradeoff: Sightengine is a fast, self-serve classification API. ActiveFence is an intelligence-led moderation platform with the operational depth to run trust and safety at enterprise scale. If you're managing complex or high-risk content categories and/or need to demonstrate regulatory compliance, ActiveFence is in a different category entirely.
ActiveFence Pricing
ActiveFence does not publish pricing. Pricing is custom-based on use case, content volume, abuse areas covered, and team size. Contact their sales team directly for a quote.
Sightengine vs. Azure AI Content Safety
Azure AI Content Safety is Microsoft's content moderation API, available as part of Azure AI Services. It covers text and image moderation across four core harm categories — hate, sexual, violence, and self-harm — with adjustable severity thresholds and custom blocklist support.
Azure AI Content Safety is primarily designed for teams already building on Azure, particularly those deploying LLMs or generative AI applications, rather than as a standalone UGC moderation tool. Its most differentiated features (Prompt Shields, groundedness detection, protected material detection) are squarely aimed at LLM pipelines, not social platforms or marketplaces.
| Feature | Sightengine | Azure AI Content Safety |
|---|---|---|
| Image moderation | 120+ subclasses with granular confidence scores | Four harm categories (hate, sexual, violence, self-harm) with severity scoring; less granular but simpler to act on |
| Text moderation | Profanity, hate speech, PII detection, URL filtering, leet speak and obfuscation detection | Same core categories plus PII detection, custom blocklists, and multilingual support across 100+ languages |
| LLM / GenAI safety | ❌ | Prompt Shields (jailbreak/injection detection), groundedness detection, protected material detection; purpose-built for LLM pipelines |
| Custom categories | ❌ | Custom category API; train your own filters using examples without retraining the base model |
| Azure ecosystem integration | ❌ | Native integration with Azure OpenAI, Azure AI Foundry, and the broader Azure AI services stack |
| Standalone UGC use case | Strong fit; purpose-built for UGC platforms | Weaker fit; narrower taxonomy, optimized for GenAI safety rather than social/marketplace content |
The core tradeoff: If you're building on Azure and deploying LLMs or generative AI features, Azure AI Content Safety is a natural fit with minimal integration overhead. If you're moderating UGC on a social platform, marketplace, or dating app, Sightengine's broader classification schema and UGC-specific training data will generally serve you better.
Azure AI Content Safety Pricing
Azure AI Content Safety uses a consumption-based model with two tiers: Free (F0) and Standard (S0). Exact per-transaction rates vary by region.
Sightengine vs. WebPurify
WebPurify is a content moderation service that offers profanity filtering, image moderation, and video moderation via API. It's one of the older players in this space and has built its reputation specifically around hybrid moderation, combining AI classification with a trained human review team.
While Sightengine is purely automated — you get model output and build your own review process on top — WebPurify offers a hybrid model that routes content through AI first and then automatically escalates low-confidence or edge-case content to human moderators. This makes it more accurate on nuanced content but slower and more expensive per item than a pure API approach.
| Feature | Sightengine | WebPurify |
|---|---|---|
| Image moderation | AI-only, 120+ subclasses, ~250ms response | AI + optional human review; hybrid pipeline catches nuanced violations that AI alone misses |
| Video moderation | Frame-by-frame AI analysis | AI + human review; purpose-built tool for high-volume video with multi-clip viewing and storyboarding |
| Text / profanity filtering | Profanity, hate speech, spam via API | Profanity filtering with custom block/allow lists; strong multi-language support (15+ languages) |
| Human review | ❌ | Core offering; 24/7 human moderation team, 90%+ of images reviewed in under 2 minutes |
| Custom moderation criteria | Limited threshold tuning | Fully custom criteria per client; human reviewers are trained to your specific community guidelines |
| Scalability model | Self-serve API, scales automatically | Managed service; volume spikes may require coordination; better suited for predictable workloads |
The core tradeoff: If automated classification is sufficient for your use case, Sightengine is faster and cheaper per operation. If you need human judgment on edge cases, WebPurify's hybrid model is more reliable. But, you're paying for a managed service, not just an API.
WebPurify Pricing
- Plugins only: $5/month — 1 simultaneous request, 1 domain, 1 language
- Standard: $15/month — 2 simultaneous requests, 2 subdomains, adds email/phone/URL filtering
- Enterprise: $50/month — 4 simultaneous requests, 6 domains, multiple languages, SSL, advanced reporting
- Custom: Contact sales
Sightengine vs. Checkstep
Checkstep is an AI content moderation platform built around policy management, workflow automation, and regulatory compliance. It covers text, image, video, and audio across 100+ languages, and recently added live voice moderation via a partnership with Modulate.
The most important architectural difference is that Checkstep is model-agnostic. Rather than running a single proprietary detection stack, it operates as a moderation operating system that sits on top of an "AI marketplace.”
This matters because no single model is best at every harm category; Checkstep lets you route content to the most accurate model per use case, and swap providers without rebuilding your pipeline.
| Feature | Sightengine | Checkstep |
|---|---|---|
| Model architecture | Single provider, proprietary models | Model-agnostic; swap models without rebuilding pipelines |
| Policy engine | ❌ | Fully configurable policy engine with version control; define rules per abuse type, update policies instantly without re-engineering |
| Human review workflow | ❌ | Customizable moderation queues with sub-50ms AI triage, human escalation, moderator wellness tools |
| DSA / compliance tooling | ❌ | Native DSA plugin |
| CSAM detection | ❌ | Integrated; includes both hash-matching and novel CSAM detection via Resolver's Athena model |
| Audit & governance | ❌ | Full audit trails, moderator performance tracking, quality assurance tools for both human and automated decisions |
The core tradeoff: Sightengine is a fast, self-serve classification API, which is ideal if you want direct model access with minimal overhead. Checkstep is better suited for teams that need policy governance, regulatory compliance, and the flexibility to manage multiple AI models without vendor lock-in.
Checkstep Pricing
Checkstep does not publish public pricing. Pricing is based on a matrix of setup fees, content volume tiers, operator seats, media types, and abuse categories covered.
Sightengine vs. Imagga
Imagga is a computer vision API company, originally built around image tagging and recognition. Content moderation was added on top of that visual recognition foundation. It's available as both a cloud API and on-premise deployment.
The most important distinction from Sightengine is product focus. Imagga is primarily a visual recognition platform; content moderation is one vertical within a broader image intelligence suite that also covers tagging, categorization, color extraction, visual search, and face detection.
| Feature | Sightengine | Imagga |
|---|---|---|
| Image moderation | 120+ subclasses across nudity, violence, hate, drugs, weapons, and more | Narrower taxonomy; strongest on adult/explicit content detection; 0.96 precision, 0.98 recall on their adult model |
| Video moderation | Frame-by-frame analysis | Scene-based analysis with smart frame selection; discards blurred/duplicate frames, preserving context across rapid cuts |
| Text moderation | Profanity, hate speech, spam via API; no contextual analysis | ❌ |
| On-premise deployment | ❌ | Available for teams with data residency or privacy requirements |
| Product focus | Purpose-built for content moderation | Visual AI platform; moderation is one use case among many (tagging, search, face detection, etc.) |
| Custom model training | ❌ | Custom training available |
The core tradeoff: If your primary moderation need is adult/explicit image or video content and you want strong out-of-the-box accuracy without extensive threshold tuning, Imagga is a credible option. If you need text moderation, broader harm categories, or a platform built exclusively around trust and safety, Sightengine covers more ground.
Imagga Pricing
- Free: $0/month — 100 API requests, basic solutions
- Indie: $79/month — 70,000 API requests, adds visual search, background removal, barcode recognition, OCR, email support
- Pro: $349/month — 300,000 API requests, adds structured tagging V3 Pro, face recognition, priority support
- Enterprise: Custom built
Sightengine vs. Amazon Rekognition
Amazon Rekognition is AWS's computer vision service, with content moderation as one feature within a broader image and video analysis platform. Moderation is not its sole focus; Rekognition also covers face detection, celebrity recognition, text extraction, object detection, and custom label training.
Rekognition's real advantage is tight integration with the AWS stack — S3, Lambda, SNS, Step Functions, and Amazon Augmented AI (A2I) for human review. If your infrastructure already lives on AWS, you can build a fully automated moderation pipeline with human escalation paths without adding a new vendor.
| Feature | Sightengine | Amazon Rekognition |
|---|---|---|
| Image moderation | 120+ subclasses purpose-built for UGC scenarios | Three-tier taxonomy covering nudity, violence, drugs, alcohol, hate symbols, gambling; expanded in 2024 but less granular on subcategories |
| Video moderation | Synchronous frame-by-frame analysis | Asynchronous stored video analysis via S3; also supports Kinesis Video Streams for real-time streaming |
| Text moderation | Profanity, hate speech, PII detection, URL filtering, leet speak and obfuscation detection | ❌ — requires pairing with Amazon Comprehend for text analysis |
| Human review integration | ❌ | Native integration with Amazon A2I; routes low-confidence flags to human reviewers without building custom tooling |
| Custom model training | ❌ | Custom Moderation adapter; train on your own labeled images to improve accuracy on platform-specific content |
| AWS ecosystem integration | ❌ | Native; plugs directly into S3, Lambda, SNS, Step Functions; no additional vendor required for AWS-native stacks |
The core tradeoff: If you're already building on AWS, Rekognition's ecosystem integration and human review pipeline via A2I make it a compelling default choice with low integration overhead. If you're not on AWS, or if you need deeper UGC-specific classification (especially for text), Sightengine's models and broader harm taxonomy will generally outperform it.
Amazon Rekognition Pricing
Pricing is usage-based with no minimum fees or upfront commitments. Rates vary by AWS region.
Sightengine vs. Clarifai Content Moderation
Clarifai started as a computer vision API company with strong content moderation roots. It was one of the early providers that platforms like 9GAG used to automate NSFW detection at scale. Today, it has evolved into a broad full-stack AI platform covering compute orchestration, LLM inference, agentic workflows, and model hosting. Content moderation is still available, but it's one use case within a much larger platform rather than the core product focus.
That context matters when evaluating it against Sightengine. Clarifai's moderation models are proven and production-tested, but if you're looking for a dedicated moderation API with a narrow integration surface, Clarifai now comes with significant platform overhead.
| Feature | Sightengine | Clarifai |
|---|---|---|
| Image moderation | 120+ subclasses purpose-built for UGC | Pre-trained models for nudity, gore, drugs, explicit content; proven at scale but narrower taxonomy |
| Text moderation | Profanity, hate speech, spam via API | Available but not a primary strength; Clarifai's NLP focus has shifted toward LLM inference rather than UGC text classification |
| Custom model training | ❌ | Strong; train custom classifiers on your own data; supports last-layer fine-tuning, LoRA, and full fine-tuning via AutoML-style tooling |
| Deployment flexibility | Cloud API only | Cloud, on-premise, hybrid, and local runners; runs on your own GPU hardware with Clarifai's API as the control plane |
| Platform scope | Focused moderation API | Full-stack AI platform; compute orchestration, LLM hosting, agentic workflows; moderation is one of many use cases |
| Integration complexity | Low; simple REST API, minimal setup | Higher; platform has significant depth; onboarding is more involved if you only need moderation |
The core tradeoff: If you need a focused moderation API, Sightengine is simpler to integrate and maintain. Clarifai makes more sense if you need custom model training, flexible deployment (especially on-premise), or want to build moderation into a broader AI pipeline that also handles other computer vision or LLM tasks.
Clarifai Pricing
Clarifai offers two plans:
- Pay As You Go: No monthly commitment. Pay per inference request and compute usage. Up to 100,000 requests/month, 100 requests/second.
- Enterprise: Custom pricing.
Alternatives Comparison Chart
| Provider | Text Moderation | Image Moderation | Video Moderation | Human Review | Custom Models | Moderation Dashboard | Public Pricing |
|---|---|---|---|---|---|---|---|
| Sightengine | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ |
| Stream | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Hive | ✅ | ✅ | ✅ | ❌ | ✅ (AutoML) | ✅ (Enterprise) | ✅ |
| ActiveFence | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ❌ |
| Azure AI Content Safety | ✅ | ✅ | ❌ | ✅ (via A2I) | ✅ | ❌ | ✅ |
| WebPurify | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ |
| Checkstep | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ |
| Imagga | ❌ | ✅ | ✅ | ❌ | ✅ | ❌ | ✅ |
| Amazon Rekognition | ❌ | ✅ | ✅ | ✅ (via A2I) | ✅ | ❌ | ✅ |
| Clarifai | ✅ | ✅ | ✅ | ❌ | ✅ | ❌ | ✅ |
What to Consider: Sightengine Versus a Competitor
Sightengine is a capable, self-serve classification API, but the right choice depends on what you're building and where moderation fits in your stack. Before switching, consider the following:
What content types do you need to moderate?
Sightengine covers image, video, and text, but its text moderation is relatively shallow. If text is your primary moderation surface — chat messages, comments, usernames — a platform with deeper NLP or LLM-based analysis will serve you better.
Do you need a workflow layer, or just a signal?
Sightengine returns confidence scores. What you do with them is entirely up to you. If you need human review queues, policy enforcement rules, appeals management, or audit trails, you'll need to build that infrastructure yourself — or choose a platform that includes it.
How important is regulatory compliance?
If you're subject to the EU Digital Services Act, UK Online Safety Act, or similar frameworks, Sightengine provides no native compliance tooling.
Are you already on a major cloud platform?
If your infrastructure lives on AWS or Azure, Amazon Rekognition and Azure AI Content Safety integrate with minimal overhead and no new vendor relationship. The tradeoff is a narrower moderation taxonomy and less UGC-specific model training.
Do you need human judgment on edge cases?
Automated classifiers struggle with context-dependent violations, like illustrated content, cultural nuance, and indirect threats. If accuracy on ambiguous content matters, some tools provide a layer that pure API tools can't replicate.
What's your expected scale and growth trajectory?
Sightengine's self-serve tiers cap out at 200,000 operations/month on the Pro plan. If you're approaching or exceeding that, you'll need to move to enterprise pricing, at which point some platforms become more directly comparable on cost.
Sightengine Overview
Now that we've covered the alternatives, here's a closer look at Sightengine itself.
We’ll cover its strengths, limitations, and where it fits best.
Advantages of Sightengine
- Purpose-built for UGC moderation. Unlike cloud vision APIs that bolt on moderation as a secondary use case, Sightengine's models are trained specifically on real UGC scenarios. This narrows the distribution gap between training data and production data, which tends to improve accuracy on edge cases.
- Granular classification schema. Most moderation APIs return category-level labels. Sightengine returns subcategory scores, so you can, for example, allow bikini content on a fashion platform while blocking sexual display, without building a secondary classification layer yourself.
- Genuinely fast response times. Sightengine processes synchronous image checks in single-digit milliseconds on their end. For real-time use cases like profile photo uploads or chat image attachments, this matters.
- No-human-review policy by default. Content processed through the API is not reviewed by human moderators. For platforms handling sensitive or legally protected content (healthcare, legal communications), this is a meaningful privacy distinction.
- Transparent, self-serve pricing. Paid plans start at $29/month with published per-operation rates. You can get a production API key, test models, and estimate costs without talking to sales.
- Workflow engine. Beyond raw API calls, Sightengine offers a dashboard-based workflow builder that lets you define accept/reject rules once and apply them automatically.
Drawbacks of Sightengine
- No native human review or escalation path. When automated classification produces low-confidence or ambiguous results, there's no built-in mechanism to route content to a human reviewer. You'd need to build that queue yourself or integrate a separate tool.
- Text moderation is secondary. Sightengine's text moderation lacks contextual depth. It handles profanity, PII, leet speak, grawlix, and obfuscation attempts well, but it lacks the LLM-based contextual reasoning needed to catch nuanced harassment, indirect threats, or context-dependent hate speech.
- No compliance or audit tooling. For platforms subject to DSA, CSAM reporting obligations, or internal governance requirements, Sightengine provides no native tooling for audit trails, appeals, or transparency reporting.
- Limited non-visual moderation. Audio moderation exists, but it's limited to transcription and profanity detection. There's no behavioral analysis, metadata-level signals, or cross-content pattern detection.
- Small vendor footprint. Sightengine is a relatively small, bootstrapped company. For enterprise teams, this raises questions around SLA guarantees, long-term roadmap stability, and support responsiveness at scale.
Is Sightengine Right For You?
Sightengine is a strong fit for teams who want a fast, self-serve classification API with granular UGC-specific models and minimal integration overhead.
If the drawbacks outlined above are relevant to your use case, the alternatives in this guide offer a range of solutions — from lightweight API tools to full enterprise platforms.
Many offer free tiers or trials, so you can evaluate them in context before committing.