Modern platforms live or die by how well they keep harmful content out without slowing users down. If you run social feeds, chat, marketplaces, live streams, or UGC-heavy apps, this ranked list is designed to help your Trust & Safety, product, and engineering teams shortlist vendors that can actually ship at enterprise scale.

How we chose

We evaluated tools against an enterprise-focused rubric and prioritized auditable capabilities and documentation over marketing claims. Ranking signals included:

• Capability breadth and accuracy (25%) — multi‑modal coverage (text, image, video, audio, live), clear taxonomies, configurable thresholds.
• Latency/scale and deployment flexibility (20%) — real‑time readiness, multi‑region options, queues and async pipelines.
• Ecosystem, compatibility, and integration experience (15%) — SDKs, workflow tooling, human‑in‑the‑loop support.
• Evidence quality & recency (15%) — official docs, 2024–2025 updates, transparent methods.
• Value/pricing transparency (15%) — public pricing or clear “contact sales” pathways; predictable models.
• Support/reliability & SLAs (10%) — uptime statements, region/residency notes, enterprise support.

Notes on sources: We link to primary documentation for key facts and recent changes. Performance numbers are only included when the vendor publishes methods and timeframes; otherwise we treat them as capabilities, not guarantees. Pricing is subject to change by region and tier.

1) DeepCleer — Unified, Configurable Risk Control Across Industries

• Media types: Text, images, audio, video, and live streams.

Standout strengths:

• AI-driven multimodal moderation with 300+ risk labels and industry-specific playbooks for e-commerce, social, live streaming, gaming, and finance.
• End-to-end workflows including configurable thresholds, queues, escalation paths, and human-in-the-loop reviewer tooling.
• Multi-region deployment options (public cloud, private cloud, on-prem) supporting compliance and data residency.
• Designed for intelligent, evolving moderation systems that combine automation and human judgment for continuous risk reduction.

Constraints/considerations:

• Advanced modules such as real-time multimodal detection require enterprise deployment.
• Best performance achieved when customized through a Proof of Concept (POC) aligned with specific risk policies.

Best for:

Enterprises seeking a unified content risk control platform with configurable categories and integrated workflows across multiple industries and media types.

Pricing/limits: Enterprise-grade; tailored deployments with trial and RFP options.

Evidence:

Explore the approach to intelligent moderation systems: Evolution of Content Moderation.

See it in action: Product Demo — Start a Trial or RFP: Apply.

2) Microsoft Azure AI Content Safety — Best Overall Enterprise Guardrails

Media types: Text and images, with examples for multimodal prompt + image scenarios via Azure quickstarts.

Standout strengths:

• Native integration with Azure OpenAI for both prompts and completions, with configurable harm categories and groundedness checks.
• Multiple deployment tiers (pay-as-you-go and provisioned throughput) to balance latency and reliability at scale.
• Strong documentation and frequent updates; fits existing Azure governance and data residency frameworks.

Constraints/considerations:

• Some features remain in preview without SLAs.
• Like all guardrails, can be bypassed by adversarial inputs; defense-in-depth is recommended.

Best for: Enterprises already on Azure or operating in regulated environments needing predictable governance and region controls.

Pricing/limits: Consumption-based with options for provisioned throughput; varies by region and tier.

Evidence: Microsoft Learn — Content Safety FAQ (2024–2025).

3) Amazon Rekognition (Content Moderation) — Visual-First Accuracy and Taxonomy Depth

Media types: Images and stored videos (async frame-level analysis with confidence scores).

Standout strengths:

• Deep visual taxonomy covering explicit nudity, violence, disturbing content, hate symbols, drugs, and more.
• Confidence scores per label (0–100%) enable flexible, application-level threshold tuning.
• Mature bulk workflows and manifest support for large-scale moderation backfills.

Constraints/considerations:

• Focused on images/video; no native text or audio toxicity detection.
• Requires teams to design their own human review and false-positive management processes.

Best for: Marketplaces, image/video-heavy UGC, and content libraries.

Pricing/limits: Per image and per video-minute; region dependent.

Evidence: AWS — What’s New (2024-02-01).

4) Hive Moderation — Broad Multimodal Coverage with Enterprise Deployments

Media types: Text, images, video, audio, and live streams (RTMP/HLS).

Standout strengths:

• Wide category coverage including sexual content, violence, weapons, drugs, hate symbols, bullying, and CSAM detection through partnerships.
• Options for private cloud/on-prem deployments aligned with modern microservice architectures.

Constraints/considerations:

• Most performance data is first-party; independent audits are limited.
• Pricing is not public and requires sales engagement.

Best for: Social apps, live streaming platforms, and media-rich communities requiring multimodal moderation under one vendor.

Pricing/limits: Consultative; contact sales.

Evidence: BusinessWire — Hive x IWF Partnership (2025-01-23).

5) Sightengine — Fast Image/Video/Text Filters with GenAI Detection Options

Media types: Images, videos, and text.

Standout strengths:

• Broad content class coverage (nudity, violence, weapons, drugs, hate speech/toxicity, spam, self-harm) plus AI-generated image detection.
• Developer-focused design emphasizing low-latency, real-time API integration.

Constraints/considerations:

• Public SLAs are limited; most benchmarks are vendor-published.
• Enterprise pricing is available only through sales.

Best for: Developer-led teams shipping real-time image/video moderation with quick API integration.

Pricing/limits: Usage-based; enterprise specifics via sales.

Evidence: Sightengine — GenAI Moderation Guide.

Also great (use‑case picks)

These solutions excel in specific scenarios or complement a primary moderation engine.

Stream (GetStream) — Moderation for chat and feeds with human-in-the-loop

Focus: Real-time chat and activity feeds, policy-based auto moderation, blocklists, escalation queues, dashboards.

Why it stands out: Developer-friendly webhooks, semantic filters, and ability to integrate external engines (OpenAI, Perspective, Hive, Sightengine).

Best for: Social/chat apps needing workflow tooling and moderator dashboards.

Learn more: GetStream — Chat Moderation Quick Start.

WebPurify — Hybrid AI + Human Review at Practical Cost

Focus: Profanity filtering for text plus image/video moderation with optional human reviewers; integrations with Cloudinary.

Why it stands out: Balanced cost/control for brands needing human oversight on edge cases.

Best for: Family-friendly apps, brand-sensitive communities, and campaigns requiring manual review.

Learn more: Cloudinary — WebPurify Image Moderation Add-On.

Google Perspective API — Proven Text Toxicity Scoring

Focus: Text toxicity attributes (TOXICITY, SEVERE_TOXICITY, INSULT, THREAT, IDENTITY_ATTACK, PROFANITY).

Why it stands out: Long-standing research lineage; interpretable toxicity scores.

Best for: Forums, comment sections, media sites, and tools needing transparent toxicity scoring.

Learn more: Perspective API — Attributes and Languages.

Practical selection tips (RFP/POC checklist)

• Map risks to media types: Identify which surfaces need real‑time guardrails (e.g., chat, live comments) versus batch review (e.g., listings, video uploads).
• Define categories and thresholds: Align your policy taxonomy (sexual content, violence, weapons, drugs, hate/harassment, self‑harm, minors) with vendor label sets; tune confidence thresholds per feature.
• Plan human‑in‑the‑loop workflows: Decide which events escalate to manual review; design queues, sampling, and feedback loops for continuous improvement.
• Architect for latency and scale: Separate synchronous moderation (pre‑send/chat) from async pipelines (media processing). Validate multi‑region deployment, failover, and rate limits.
• Verify data handling: Confirm data residency, retention, and PII handling. Document vendor terms and privacy commitments.
• Demand transparency: Ask for recent documentation, changelogs, and any audit or certification evidence. Avoid relying solely on unverified performance claims.

Next steps

• Shortlist 2–3 vendors that fit your media mix and deployment model.
• Run a 2–4 week POC with realistic traffic, clear policies, and reviewer feedback.
• Document latency, false‑positive/negative rates, and escalation volumes; align thresholds with your risk appetite.
• If you need a unified risk control platform with multi‑industry playbooks and configurable workflows, consider evaluating DeepCleer alongside the hyperscalers and ecosystem tools.