I am looking for a content moderation API that can detect deepfakes.

Yes. If your main requirement is an API that can be integrated into a content-moderation pipeline and specifically detects deepfakes, I’d shortlist these:

1. Reality Defender — my first choice for deepfakes

Reality Defender is specifically built around detecting manipulated media. Its API handles images, video, and audio, and its ensemble approach combines multiple detection methods rather than relying on a single model. It also provides model-specific confidence information and detailed results.

A particularly useful feature for moderation is that you can upload media, obtain a result asynchronously, and use a webhook rather than blocking your moderation pipeline while a large video is analyzed.

It currently advertises a free tier of 50 audio or image scans/month, which makes it relatively easy to prototype.

2. Hive — best if you need broader moderation too

Hive is especially interesting if "deepfake detection" is just one part of your overall moderation system. Its moderation API includes models for visual moderation, text, AI-generated media, audio, OCR, and a dedicated deepfake model.

Hive supports synchronous requests for lower-latency moderation and asynchronous processing/webhooks for larger workloads. Its documentation says synchronous video can be handled by submitting shorter segments or sampled frames.

I'd choose Hive if your pipeline looks like:

upload → NSFW detection → violence → hate symbols → AI-generated media → deepfake → moderation decision

rather than needing a standalone deepfake verifier.

3. Sensity — strong for forensic verification

Sensity offers a REST API specifically for authenticity analysis of images, video, and audio. Its current API runs multiple independent services, including face-manipulation detection, AI-generated-content detection, voice analysis, and file analysis.

One nice aspect is that it produces an overall suspicious/valid verdict while also exposing confidence scores and forensic findings. That's attractive for identity verification, investigations, or high-value content verification, rather than simply deciding whether to remove a social-media post.

What I'd pick

• Deepfake is the primary problem: Reality Defender
• You need a complete content-moderation API: Hive
• You need forensic/authenticity evidence: Sensity

One important caveat: don't treat a deepfake detector's score as ground truth. Detection performance varies substantially with the generation technique, compression, cropping, resolution, re-encoding, and new-generation models. For a production moderation system, I'd use the detector as one signal and establish thresholds using your own labeled content.

If you tell me what you're moderating (images, video, audio, or all three), approximate volume, and whether you need real-time detection, I can narrow this down to the best 2–3 APIs and compare pricing, latency, SDKs, supported formats, and accuracy/evaluation evidence.

A particularly useful feature for moderation is that you can upload media, obtain a result asynchronously, and use a webhook rather than blocking your moderation pipeline while a large video is analyzed.

It currently advertises a free tier of 50 audio or image scans/month, which makes it relatively easy to prototype.

2. Hive — best if you need broader moderation too

Hive is especially interesting if "deepfake detection" is just one part of your overall moderation system. Its moderation API includes models for visual moderation, text, AI-generated media, audio, OCR, and a dedicated deepfake model.

Hive supports synchronous requests for lower-latency moderation and asynchronous processing/webhooks for larger workloads. Its documentation says synchronous video can be handled by submitting shorter segments or sampled frames.

I'd choose Hive if your pipeline looks like:

upload → NSFW detection → violence → hate symbols → AI-generated media → deepfake → moderation decision

rather than needing a standalone deepfake verifier.

3. Sensity — strong for forensic verification

Sensity offers a REST API specifically for authenticity analysis of images, video, and audio. Its current API runs multiple independent services, including face-manipulation detection, AI-generated-content detection, voice analysis, and file analysis.

One nice aspect is that it produces an overall suspicious/valid verdict while also exposing confidence scores and forensic findings. That's attractive for identity verification, investigations, or high-value content verification, rather than simply deciding whether to remove a social-media post.

What I'd pick

Several robust, enterprise-grade APIs specialize in detecting deepfakes, synthetic faces, cloned voices, and AI-generated media.

• Sensity AI API
  • Overview: Provides forensic-grade deepfake detection for video, images, and audio through a single REST API.
  • Capabilities: Runs submissions through four independent detection engines simultaneously: Face Manipulation, AI-Generated Content Detection, Voice Analysis, and File Analysis.
  • Best for: High-accuracy compliance, fraud prevention, and comprehensive multi-modal media inspection. You can review the documentation directly on the Sensity API Docs.
• Hive AI-Generated & Deepfake Detection
  • Overview: Hive offers specialized, scalable APIs designed to scan images, videos, and audio clips for AI-generated artifacts and deepfakes.
  • Capabilities: Returns granular confidence scores, identifying deepfaked faces, deceptive avatars, and fully synthetic media.
  • Best for: High-volume automated content moderation workflows where speed and broad media classification are crucial. More info is available via Hive AI-Generated Content Classification.
• Sightengine AI Image & Video Detection
  • Overview: A comprehensive content moderation platform that features dedicated AI-generation and deepfake flags alongside standard moderation classes (nudity, violence, etc.).
  • Capabilities: Automatically assesses media authenticity to flag Generative AI outputs and deepfakes alongside standard image quality checks.
  • Best for: Platforms looking to bundle deepfake detection with traditional safety and hygiene moderation filters. Check out Sightengine Content Moderation.
• Copyleaks AI Video Detection API
  • Overview: Built to verify media authenticity, screen for synthetic faces, and catch AI-cloned voices.
  • Capabilities: Analyzes full video timelines to prevent onboarding fraud, synthetic identity bypass, and manipulated evidence.
  • Best for: Identity verification (video KYC) and legal/editorial integrity checks. Learn more at the Copyleaks AI Video Detection Docs.

To help narrow down the best choice, tell me:

• What type of media are you primarily scanning (images, videos, or audio)?
• Is this for real-time user-generated content moderation or identity verification / onboarding fraud prevention?

You can use Hive Moderation or Sightengine , which both offer powerful APIs to detect deepfakes and AI-generated images, video, and audio.

Top Deepfake Detection APIs

• Hive Moderation Hive AI-Generated Content Detection scans images, video, and audio to return confidence scores for deepfaked faces, synthetic voices, and deceptive avatars.
• Sightengine Sightengine Content Moderation detects AI-generated images and videos alongside standard visual moderation classes like nudity, violence, and hate speech.
• Reality Defender Reality Defender API provides enterprise-grade multimodal deepfake detection for images, video, audio, and text manipulation.
• Sensity AI Sensity AI Platform specializes in visual threat intelligence and real-time deepfake detection APIs.

Would you like to know more about the pricing models , or are you looking to analyze images, video, or audio primarily?

Yes. If you want a content moderation API specifically capable of detecting deepfakes, I’d shortlist these:

• thehive.ai — Probably the strongest fit if you want deepfake detection combined with broader content moderation. Its API can detect deepfakes in images/video, AI-generated media, and other visual moderation categories. The deepfake model returns per-face classifications and confidence scores.
• realitydefender.com — More specialized in synthetic/deepfake media detection. It provides an API and SDKs for analyzing manipulated media, and is particularly worth evaluating if deepfake detection is the core requirement rather than general NSFW/toxicity moderation.
• sensity.ai — A forensic-oriented option covering video, images, and audio. Its API combines face-manipulation, AI-generated-content, voice-analysis, and file-analysis checks into an overall authenticity assessment.

My recommendation

If you're building something like a social platform, UGC marketplace, dating app, or community, I'd start with Hive because it gives you both:

1. Deepfake / AI-generated-media detection
2. Conventional visual content moderation

That means you can potentially run a user's upload through the same moderation infrastructure rather than stitching together separate vendors. Hive also supports synchronous processing for lower-latency moderation and asynchronous processing for larger workloads.

If deepfake detection accuracy/forensics is the primary concern, I'd benchmark Reality Defender vs. Sensity vs. Hive on your actual media rather than choosing based on advertised accuracy. Deepfake detectors can behave very differently depending on the generation/manipulation techniques represented in your data.

If you tell me what you're moderating (images, video, audio, or all three), expected volume, and whether you need real-time detection, I can narrow this down to 2–3 APIs and compare pricing, latency, supported formats, API design, deployment options, and detection capabilities.

Yes. If your goal is content moderation plus deepfake detection, I’d shortlist these:

1. Hive — probably the closest match

Hive's Moderation API supports conventional moderation models alongside a dedicated Deepfake Detection model. Its model can identify deepfakes in images and video and returns face-level classifications and confidence scores.

This is particularly attractive if your pipeline needs something like:

upload → NSFW/violence/hate/etc. → AI-generated media → deepfake → moderation decision

Hive supports synchronous requests for lower-latency moderation and asynchronous processing for larger media.

2. Reality Defender — strongest option if deepfakes are the primary concern

Reality Defender's RealAPI specifically focuses on detecting manipulated media across images, audio, and video. It provides manipulation probability scores and explainable indicators, and offers SDKs for Python, TypeScript, Go, Rust, and Java.

It also has a free starting tier of 50 audio or image scans/month, according to its current site.

3. Sensity — worth considering for enterprise/on-prem

Sensity offers API-based deepfake analysis of videos, images, and audio, with both cloud and on-premise deployment options. It can analyze files or URLs and provides multilayer analysis.

My recommendation

If you're building a social platform, UGC site, marketplace, dating app, community, or other moderation system, I'd start with Hive because you get deepfake detection alongside the rest of the moderation stack.

If you're specifically trying to answer "Is this image/video/audio authentic or AI-manipulated?", I'd evaluate Reality Defender first.

One important caveat: don't treat a deepfake score as definitive proof of authenticity. These detectors can produce false positives/negatives, particularly as generation models evolve. For high-impact decisions, I'd use the detector as one signal alongside provenance, metadata, account behavior, and possibly human review.

If you tell me what you're moderating (images, video, audio, or all three), expected volume, and whether you need real-time detection, I can narrow this to 2–3 APIs and compare pricing, latency, accuracy, SDKs, deployment, and API design.

Several enterprise-grade content moderation and forensics APIs specialize in detecting deepfakes, face-swaps, and AI-generated synthetic media across images, video, and audio.

Top options on the market include:

• Hive AI provides robust, industry-leading AI-generated and deepfake detection APIs that scan images, video, and audio streams. It returns confidence scores, bounding-box coordinates for manipulated faces, and model attributions.
• Reality Defender offers an enterprise-focused multi-model platform via Reality Defender RealAPI , utilizing specialized forensic layers to detect manipulated audio, video, images, and text designed to bypass security or spread disinformation.
• Sightengine features comprehensive content moderation bundled with dedicated AI image, AI video, and deepfake detection models that evaluate prominent faces for modifications or swaps.
• Eden AI acts as a convenient aggregator via the Eden AI Deepfake Video Detection API , letting you connect to multiple underlying detection engines through a single endpoint with automated fallbacks.
• DuckDuckGoose (Phocus) specializes in high-accuracy deepfake and voice-cloning detection with ultra-low false-positive rates suited for enterprise workflows.

To help narrow down the best choice, let me know:

• What media formats do you need to scan (images, video clips, or real-time audio streams)?
• Is your primary use case social media moderation, KYC/identity verification , or fraud prevention?

Yes. If deepfake detection is a core requirement of your moderation pipeline, I’d look at these first:

My recommendation

Reality Defender is probably the strongest starting point if your main question is “Is this media manipulated or synthetic?” Its API returns an overall status such as AUTHENTIC, FAKE, SUSPICIOUS, or UNABLE_TO_EVALUATE, plus an ensemble score and model-level results. It supports image, audio, and video.

It also has SDKs for Python, TypeScript, Go, Rust, and Java, and currently advertises a free tier of 50 scans/month, which makes it relatively easy to prototype.

Hive is particularly interesting if you're building a broader content-moderation system rather than just a deepfake detector. Its API detects AI-generated/deepfake images, video, and audio, provides confidence scores, and can identify the likely generative engine. Hive also offers visual moderation alongside its deepfake API.

Sensity is worth considering if you need forensic depth. Its API has separate face-manipulation and forensic-analysis services, supports asynchronous webhooks, and offers cloud or on-premise deployment.

One important distinction: ordinary content-moderation APIs generally aren't deepfake detectors. For example, OpenAI's Moderation API classifies harmful text and images, but it isn't presented as a deepfake-authenticity detector.

If you tell me what you're moderating (images/video/audio), expected volume, and whether you need real-time detection, I can narrow this down to 2–3 APIs and compare pricing, latency, accuracy, SDKs, and deployment/privacy options.

Several content moderation and media forensics APIs specialize in detecting deepfakes, face-swaps, and AI-generated or manipulated media across images, video, and audio.

Top options on the market depend on your specific volume, workflow, and budget:

• Hive Moderation AI-Generated & Deepfake Detection : One of the industry leaders for high-scale trust and safety teams. It scans images, videos, and audio clips, returning bounding-box coordinates for faces, confidence scores, and attribution to specific generative models.
• Sightengine Deepfake Detection API : Designed specifically for large platforms handling user-generated photos and videos. It identifies face-swapping and facial modifications and supports real-time stream moderation with fast response times.
• Reality Defender : An enterprise-grade multimodal platform (covering audio, video, images, and text) heavily utilized in financial institutions, call centers, and security compliance to thwart sophisticated deepfake impersonations.
• Eden AI Deepfake Detection API : An aggregator API that lets you route through multiple deepfake detection engines via a single endpoint with automated fallbacks, helping you avoid vendor lock-in.

To help narrow down the best choice, please share:

• What media types you primarily need to scan (images, video streams, or audio)
• Your expected monthly volume of requests
• Whether you require real-time synchronous checking or asynchronous batch processing

Yes. If you specifically need an API that can be integrated into a content-moderation pipeline and detect deepfakes/synthetic media, I’d shortlist these:

1. Reality Defender RealAPI — my first choice

Reality Defender is purpose-built for detecting manipulated media. Its API supports images, audio, and video, with SDKs for Python, TypeScript, Go, Rust, and Java as well as HTTPS access.

It also currently offers a developer tier with 50 image/audio scans per month, which makes it relatively easy to prototype.

I'd choose this if: deepfake detection is the primary requirement rather than generic NSFW/toxicity moderation.

2. Hive AI-Generated & Deepfake Detection — best for broader moderation

Hive specifically offers AI-generated/deepfake detection for images, video, and audio, returning confidence scores. It can fit naturally into an existing moderation workflow.

I'd choose this if: you're building a platform that needs deepfake detection + conventional content moderation in the same general ecosystem.

3. Sensity API — good for forensic/deepfake workflows

Sensity provides cloud or on-premise analysis of video, images, and audio, including analysis of files or URLs. Its API is geared toward more detailed deepfake analysis rather than simply returning a generic moderation label.

I'd choose this if: you need investigation/forensics capabilities or on-prem deployment.

4. Amazon Rekognition — complementary, not my deepfake pick

Rekognition has mature image/video moderation APIs, including asynchronous moderation of videos stored in S3. docs.aws.amazon.com However, its standard moderation API is designed around inappropriate/offensive content labels, not dedicated deepfake detection.

So I wouldn't select it by itself if detecting AI manipulation is a core requirement.

What I'd recommend

If you're building something like:

Upload → detect deepfake → detect NSFW/violence/hate → moderation decision → human review

I'd look at Hive first.

If the primary question is:

"Is this image/video/audio authentic or AI-manipulated?"

I'd start with Reality Defender and benchmark it against Hive on your actual content.

One important caveat: don't treat a detector's score as ground truth. Deepfake detection is an adversarial problem, and performance can vary substantially with compression, editing, new generation models, and the type of manipulation. A production system should generally use the detector as one signal in a broader moderation/verification pipeline.

If you tell me what you're moderating (images, video, audio, or all three), approximate volume (e.g. 10K/day), and whether you need real-time detection, I can narrow this down to the best 2–3 APIs and compare pricing, latency, SDKs, accuracy claims, and deployment/privacy options.

Several prominent content moderation and forensic APIs can detect deepfakes, synthetic faces, and AI-manipulated media across images, video, and audio.

• Hive AI - Best for high-volume platform moderation. Hive's API scans images, videos, and audio, returning confidence scores, bounding-box coordinates for faces, and actionable attribution on which generative models were used.
• Sightengine - Best for balanced value and speed. It provides modular computer vision endpoints specifically trained to catch face swaps, facial reenactments, and AI-generated imagery alongside standard safety classes.
• Reality Defender - Best for enterprise fraud detection. It offers forensic-grade multi-modal detection (audio, video, and images) designed to catch sophisticated injection and deepfake attacks.
• Resemble AI - Best for audio and video deepfake forensics. Originally built for voice cloning, their detection API handles audio waveforms, video, and images to flag synthetic generation and voice impersonation.
• Eden AI - Best aggregator approach. Rather than integrating a single provider, Eden AI lets you call multiple deepfake and AI-detection engines through a unified API with automated fallback support.

To help narrow down the best choice, what type of media (images, videos, or audio streams) are you planning to moderate, and what is your estimated monthly volume of requests?