AI Content Detection ✦ Images · Video · Audio

Was This AI Generated?
Now You Can Know.

Detection for the age of synthetic media.

FakeMind examines every image, video, and audio file with deep-learning detection — pixel-level analysis, deepfake screening, and source-model attribution — and returns an explainable verdict with a confidence score in seconds.

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Image · Video · Audio EU AI Act Art. 50 Explainable verdicts Seconds per file

FakeMind Scanner — Image · Video · Audio

AI Detection

Deepfake

Source ID

The Problem

Seeing Is No Longer Believing.

Generative AI can now produce a photorealistic face, a convincing selfie, a full video clip, or a cloned voice in seconds — of a person who never existed and an event that never happened. Every process that trusts a photo, a video, or a recording is now exposed.

🪪

Synthetic ID Portraits

Identity documents built around a generated face. The portrait matches no real person, defeats reverse-image search, and passes casual visual inspection — because there is no original to compare against.

Fuels synthetic identity fraud

🎭

Deepfake Selfies & Video

Generated "selfie with ID" submissions and injected camera feeds that defeat liveness checks. Remote onboarding, video verification calls, and face-match steps all inherit the same blind spot.

Targets KYC & remote onboarding

📸

Fabricated Proof Photos

Generated evidence: damage photos for insurance claims, proof-of-residence snapshots, delivery confirmations, receipts. Photorealistic, metadata-clean, and produced faster than any review team can keep up with.

Hits claims, disputes & moderation

How It Works

Three Signals. One Verdict.

FakeMind's detection engine is trained on a massive corpus of real and AI-generated media. Every image, video, and audio file is scanned for the statistical fingerprints of generation, screened for deepfake manipulation, and matched against known generator families — combined into one explainable verdict.

SIGNAL 01

AI DETECTION

AI-Generation Detection

Deep-learning classifiers read the pixel-level fingerprints that generators leave behind — frequency-domain signatures, texture statistics, upsampling artifacts. Every file gets a calibrated confidence score for AI-generated versus authentic, even when all metadata has been stripped by screenshots, re-uploads, or chat-app forwards.

Vision AI classification Frequency & texture analysis Confidence score on every file Works on metadata-stripped files

SIGNAL 02

DEEPFAKE

Deepfake Screening

A dedicated check for manipulated people: face swaps, re-enactment, and synthetic portraits spliced into real scenes. It runs on stills and frame-by-frame on video — built for the "selfie with ID" submissions and injected camera feeds aimed at remote onboarding and verification flows. For audio, spectral analysis flags cloned and synthetic voices.

Face-swap detection Frame-by-frame video analysis Synthetic portrait flagging Voice-clone signatures

SIGNAL 03

SOURCE ID

Source Attribution

Detection doesn't stop at "AI or not". FakeMind matches the statistical signature against dozens of known generator families to identify the likely engine behind a fake — turning a score into a story an investigator can act on, and keeping pace as new generators ship.

60+ generator families Likely-engine ranking Image, video & audio engines Continuously updated

Aggregated Verdict

Every signal contributes to a single verdict with a confidence score and a per-signal breakdown — generation probability, deepfake findings, and the likely source — so a reviewer can always see why, not just what.

● GREEN — Likely Authentic ● YELLOW — Uncertain, Review ● RED — Likely AI-Generated

Beyond Stills

Video Lies at 30 Frames a Second.

FakeMind extends its full detection engine to video: frames are sampled and scanned individually, then temporal checks look for the inconsistencies that generators leave between frames — flicker in fine detail, unstable identity, physics that almost works.

Frame sampling · Per-frame detection · Temporal consistency

📹

Deepfake Video Calls

Injected camera feeds and face-swapped live video used to impersonate customers and executives in remote verification and approval flows.

🎬

Generated Clips

Fully synthetic video fabricated from a text prompt — fake incident footage, fake testimonials, fake "evidence" that never had a camera behind it.

🔁

Face Swaps & Re-enactment

A real recording with a replaced face or puppeteered expressions. The scene is genuine; the person in it is not. Temporal analysis catches the seams.

Audio

Voices Are the Easiest Thing to Fake.

A few seconds of recorded speech is enough to clone a voice. FakeMind analyzes the waveform itself — spectral fingerprints of synthetic speech, voice-clone signatures, segment-by-segment scoring — to flag generated audio before anyone acts on it.

Spectral analysis · Voice-clone signatures · Segment-level scoring

📞

Cloned Voice Calls

A cloned executive voice authorizing a transfer, a cloned customer passing a call-center voice check. Real-time voice fraud is now a commodity attack.

🎙️

Fake Voice Messages

Voice notes and voicemails submitted as instructions, approvals, or evidence — a convincing recording of words that were never spoken.

🎧

Spliced & Synthetic Narration

Generated speech stitched into otherwise-real recordings: sentences added, words replaced, consent fabricated. Spectral seams give it away.

In Action

See What FakeMind Catches

A "selfie with ID" submitted to a digital onboarding flow. The document scan is genuine — but the portrait belongs to no one. Here's what FakeMind finds in seconds.

◆ Digital Onboarding

Identity Verification — Selfie With ID

⚠ SYNTHETIC PORTRAIT

Selfie Portrait SYNTHETIC SIGNATURE

⚠ AI-GENERATED

Source Signature GENERATOR FAMILY MATCH

? IDENTIFIED

ID Document Scan NO SYNTHESIS SIGNAL

✓ CLEAN

File Integrity STRUCTURE VALID

✓ CONSISTENT

Signal 1 — AI-Generation Detection SYNTHETIC · 96%

Frequency-domain and texture analysis of the portrait shows statistical signatures consistent with generated imagery — no camera sensor pattern, synthetic upsampling artifacts present.

Signal 2 — Deepfake Screening FLAGGED

The portrait region carries the hallmarks of a fully synthetic face rather than a photographed person — consistent with the fabricated "selfie with ID" pattern targeting remote onboarding.

Signal 3 — Source Attribution FAMILY MATCH

The statistical signature matches a known diffusion-generator family with high confidence — evidence that strengthens the case file beyond a bare probability score.

Final Verdict

● RED — AI-Generated · 96% Confidence

Flagged with per-signal evidence and logged to the audit trail

Capabilities

Built to Answer One Question. Reliably.

Everything in FakeMind serves the verdict: is this media authentic or generated? Fast enough for live workflows, explainable enough for auditors and courts.

🧠

Deep-Learning Detection

Purpose-built classifiers trained on a massive corpus of real and generated media, continuously updated as new generators emerge — a calibrated confidence score for every file.

🎞️

Images, Video & Audio

One pipeline for all three. Stills are scanned directly, video is frame-sampled with temporal checks, and audio is analyzed spectrally for synthetic speech.

🔎

Explainable Verdicts

Every verdict ships with a per-signal breakdown and a confidence score. Reviewers see what fired and why — never just a black-box number.

⚖️

Compliance Reporting

EU AI Act Article 50 makes "was this generated?" an audit question. FakeMind produces the machine-verified answer and the disclosure line item to match.

🔗

API & Batch Processing

A REST API drops FakeMind into onboarding flows, claims systems, and moderation pipelines. Batch endpoints handle high-volume screening.

📝

Immutable Audit Trail

Every upload, verdict, and human decision is logged with evidence. Investigators get a defensible record, not a screenshot of a score.

👥

Human Review Workflow

Uncertain verdicts route to reviewers with the full per-signal evidence. Overrides require a reason and land in the audit trail.

🛡️

Private by Design

Your media is never used to train models and never shared. Deployment options are designed around data sovereignty from day one.

⚡

Seconds, Not Minutes

Verdicts in seconds per image and near-real-time for sampled video — fast enough to sit inline in a live onboarding or claims flow.

Regulatory Alignment

"Was This Generated?" Is Now a Legal Question.

Since August 2026, Article 50 of the EU AI Act requires AI-generated content to be disclosed and machine-readably marked. Organizations that accept photos, video, and voice recordings from the public now need a documented answer — for every file.

EU AI Act — Article 50

Synthetic Content Disclosure

Providers must mark AI-generated content machine-readably; deployers must disclose it. Any regulated workflow that ingests public media inherits the burden of checking.

✓ FakeMind produces the machine-verified answer

Evidence

Audit-Ready Logging

A verdict without a record is worthless in an audit. Every check FakeMind runs is logged with its per-signal evidence, timestamp, and confidence — retained for inspection.

✓ Immutable trail with per-file evidence

Beyond the EU

A Global Standard Question

Platform integrity rules, insurance regulators, courts weighing photographic evidence — the same question is arriving everywhere. A documented detection step is becoming baseline diligence.

✓ One pipeline, every jurisdiction's paper trail

Request a Demo

See FakeMind in action. In a 30-minute call, we'll scan real and generated media live, walk through the evidence-backed verdict, and map FakeMind onto your intake flow — onboarding, claims, moderation, or newsroom verification.

This call is for:

Fraud and risk teams facing synthetic identities
KYC and digital onboarding providers
Compliance officers preparing for EU AI Act audits
Claims, trust & safety, and verification teams

⏱ 30-minute call • No commitment required • Live detection demo

✓

Request Received

Our team will contact you within 24 hours.

About Us

Built by the Team Behind DocMind

FakeMind is a product of boxMind.ai, the AI innovation arm of AEG — Allied Engineering Group, a trusted name in financial technology and security infrastructure since 1994. It grew out of DocMind, our document fraud detection platform for banks — where customers kept asking one question: was this generated?

boxMind.ai

AI Innovation Lab

boxMind.ai is the AI research and product division behind FakeMind and DocMind. We specialize in purpose-driven AI systems that solve real-world problems for financial institutions and enterprises — from document fraud detection to synthetic media verification — all designed to respect data sovereignty.

Visit boxMind.ai →

AEG — Allied Engineering Group

30+ Years in Financial Technology

Founded in 1994, AEG is one of the top SWIFT Service Bureaus worldwide — fully accredited and compliant with SWIFT's Standard Operation Practice. For three decades, AEG has delivered enterprise-grade connectivity, compliance, and security solutions to banks and financial institutions globally.

SWIFT IBM Cisco Kaspersky Rapid7 Bottomline SafeNet Fircosoft

Visit AEG →

Was This AI Generated?Now You Can Know.