AI Detector | isFake.ai - Detect AI-generated text, images, video, and audio

What

isFake.ai is a multi-modal AI detection product that checks text, images, audio, and video for signs of AI generation or manipulation. Its core workflow is simple: upload a file or paste text, let the system analyze for synthetic patterns, and review a report with confidence scores and visual evidence such as highlighted fragments, heatmaps, waveforms, and frame-level markers.

The product appears positioned as a practical authenticity-checking tool for students, educators, journalists, creators, businesses, and other users who need to assess whether content may be AI-generated. The site consistently frames results as probabilistic rather than definitive, which suggests it is meant to support human review rather than replace it.

Features

• Text AI detection — analyzes writing for linguistic and statistical patterns associated with tools like ChatGPT, Claude, and Gemini, then shows token- or paragraph-level probability signals.
• Image AI detection — evaluates images for synthetic artifacts and provides pixel-level heatmaps to indicate regions that may be AI-generated or altered.
• Video AI detection — reviews footage for deepfake indicators such as frame inconsistencies, lighting mismatches, and facial or lip-sync glitches, with timeline or frame-level analysis.
• Audio AI detection — checks MP3, WAV, and AAC files for signs of voice cloning, manipulation, or synthetic speech using waveform-based analysis.
• Explainable reporting — returns confidence scores plus visual breakdowns so users can inspect why specific fragments, frames, or regions were flagged.
• Case library and educational content — includes real-world examples, guides, and blog content that help users interpret detection outputs and understand common deepfake scenarios.

Helpful Tips

• Treat outputs as risk signals, not proof — the site explicitly says detection is probabilistic and not a confirmation of authorship or intent.
• Use stronger review standards for edge cases — heavily edited AI content, mixed human-AI rewriting, short text samples, and low-resolution video are listed as limitations.
• Favor human review for consequential decisions — in education, journalism, or investigations, combine detector results with source checks, metadata, and contextual verification.
• Look for explainability, not just a top-line score — tools that show paragraph, token, frame, or waveform evidence are generally more useful for auditability than tools that only output a percentage.
• Match the detector to the media type — organizations dealing with multiple content formats may benefit from a unified workflow, but should still validate performance separately for text, image, audio, and video use cases.

OpenClaw Skills

Within an OpenClaw ecosystem, isFake.ai could likely serve as an evidence layer inside content verification and trust workflows. A likely use case would be an OpenClaw agent that ingests user-submitted media, routes each file to the relevant detector, summarizes the reported confidence and highlighted evidence, and prepares a review brief for moderators, editors, teachers, or investigators. The site mentions an API in navigation, but the provided content does not describe its capabilities, so any automation scenario should be treated as a likely integration path rather than a confirmed native workflow.

OpenClaw skills built around this product could include newsroom verification agents, academic integrity triage assistants, social media deepfake review pipelines, and enterprise media screening workflows. In practice, that combination could help professionals move from manual spot-checking to structured authenticity review: one agent could classify media type, another could extract evidence from detector outputs, and a third could create escalation reports for human decision-makers. For industries dealing with misinformation, reputational risk, or content authenticity, this likely improves consistency and speeds up first-pass review without removing the need for expert judgment.