AI app for it and development · no coding needed
Live and file media authenticity verification workspace
Reduce exposure to undetected synthetic media while keeping a reviewable record of each verdict.
Made for: Security, trust and safety, and IT teams verifying live calls, uploaded media and online content
What it does for you
The problem
Synthetic video, cloned voices and manipulated files pass review in live calls and shared content, and reviewers cannot show what was checked or why a verdict was reached.
What it gives you
Reviewer-confirmed authenticity verdicts linked to evidence
What you give it
Live call framesuploaded videoaudio filesforwarded imagesvoice notesplatform content
Build your own version of Fakeradar, Halo by Scam AI and more
One app with what these 4 AI tools do, yours to keep and change: Fakeradar, Halo by Scam AI, Deepfake Detector, deepeye by deepidv.
Everything these tools do, in one app
- Real-time video call detection Checks whether the person on screen is genuine during live video calls.Found in Fakeradar, Halo by Scam AI
- Platform integration Works alongside common video conferencing platforms like Zoom, Google Meet, Teams, and Discord.Found in Fakeradar, Halo by Scam AI, Deepfake Detector
- Privacy-first operation Does not record calls, access audio, or store user data.Found in Fakeradar, Halo by Scam AI
- On-device processing Runs locally without sending data to the cloud.Found in Halo by Scam AI
- One-click verification Allows users to verify authenticity with a single click.Found in Fakeradar
- Detection of deepfakes and static photos Identifies synthetic video and static photo spoofing attempts.Found in Fakeradar
- Multiple deepfake generator support Detects content from several deepfake generators, with ongoing additions planned.Found in Fakeradar
- Quality check filters Filters out bad lighting, shaky video, heavy compression, or faces too far from the camera to reduce false positives.Found in Halo by Scam AI
- Windows Graphics Capture Reads the meeting window directly, working across desktop apps and browser-based calls without virtual camera setup.Found in Halo by Scam AI
- Automated model fine-tuning Fine-tunes the detection model against new deepfake methods via an automated data collection pipeline.Found in Halo by Scam AI
- Audio and video analysis Scrutinizes both audio and video files for authenticity.Found in Deepfake Detector
- Expert verification services Uses expert analysis to determine the probability of media being AI-generated or authentic.Found in Deepfake Detector
- Noise and music remover Removes background noise and music to provide cleaner media analysis.Found in Deepfake Detector
- Browser extension Enables detection on popular platforms like YouTube, WhatsApp, TikTok, Zoom, and Google Meet.Found in Deepfake Detector, deepeye by deepidv
- Content upload for evaluation Allows users to upload content for immediate evaluation and detailed insights.Found in Deepfake Detector
- WhatsApp integration Accepts forwarded images, video, or voice notes and returns a verdict within seconds.Found in deepeye by deepidv
- No file uploads required Runs detection in the background without requiring manual uploads or a separate dashboard.Found in deepeye by deepidv
- Optional premium module Lets users run the tool's detection, Scam.AI's detection, or both.Found in deepeye by deepidv
- Cloned voice detection Detects cloned voices during live phone calls.Found in deepeye by deepidv
How it works, step by step
- Check whether the person on screen is genuine during live video calls
- Run alongside Zoom, Google Meet, Teams and Discord
- Operate without recording calls, accessing audio or storing user data
- Process on-device without sending data to the cloud
- Verify authenticity with a single click
- Detect synthetic video and static photo spoofing
- Support several deepfake generators with ongoing additions
- Filter bad lighting, shaky video, heavy compression and distant faces to reduce false positives
- Read the meeting window directly via Windows Graphics Capture without virtual camera setup
- Fine-tune the detection model against new deepfake methods through an automated data collection pipeline
- Analyze both audio and video files for authenticity
- Route uncertain cases to expert analysis for a probability assessment
- Remove background noise and music for cleaner media analysis
- Detect on YouTube, WhatsApp, TikTok, Zoom and Google Meet through a browser extension
- Accept uploaded content for immediate evaluation and detailed insights
- Accept forwarded images, video or voice notes on WhatsApp and return a verdict within seconds
- Run detection in the background without manual uploads or a separate dashboard
- Let users run the tool's detection, a partner detection module, or both
- Detect cloned voices during live phone calls
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned reviewer-confirmed authenticity verdicts linked to evidence with source references and unresolved questions
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Live and file media authenticity verification workspace with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Live and file media authenticity verification workspace with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links4 KB
- questions.mdQuestions to answer before you build3 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare29 KB
- prompt-vps.mdThe same build on your own server (Docker)29 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria14 KB
- demo/index.htmlThe working demo on sample data198 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Reduce exposure to undetected synthetic media while keeping a reviewable record of each verdict. For security, trust and safety, and IT teams verifying live calls, uploaded media and online content, convert live call frames, uploaded video and audio files, forwarded images and voice notes, and platform content into reviewer-confirmed authenticity verdicts linked to evidence. The benefit is a testable hypothesis, measured through confirmed verdicts per review hour and false positives after reviewer correction; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect live call frames, uploaded video and audio files, forwarded images and voice notes, and platform content, then follow this sequence: 1. Check whether the person on screen is genuine during live video calls. 2. Run alongside Zoom, Google Meet, Teams and Discord. 3. Operate without recording calls, accessing audio or storing user data. 4. Process on-device without sending data to the cloud. 5. Verify authenticity with a single click. 6. Detect synthetic video and static photo spoofing. 7. Support several deepfake generators with ongoing additions. 8. Filter bad lighting, shaky video, heavy compression and distant faces to reduce false positives. 9. Read the meeting window directly via Windows Graphics Capture without virtual camera setup. 10. Fine-tune the detection model against new deepfake methods through an automated data collection pipeline. 11. Analyze both audio and video files for authenticity. 12. Route uncertain cases to expert analysis for a probability assessment. 13. Remove background noise and music for cleaner media analysis. 14. Detect on YouTube, WhatsApp, TikTok, Zoom and Google Meet through a browser extension. 15. Accept uploaded content for immediate evaluation and detailed insights. 16. Accept forwarded images, video or voice notes on WhatsApp and return a verdict within seconds. 17. Run detection in the background without manual uploads or a separate dashboard. 18. Let users run the tool's detection, a partner detection module, or both. 19. Detect cloned voices during live phone calls. Resolve uncertain cases with qualified reviewers, approve reviewer-confirmed authenticity verdicts linked to evidence, and measure confirmed verdicts per review hour and false positives after reviewer correction against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Detection signals are probabilistic; final authenticity and fraud judgments remain human. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve source attribution, chain of custody and usage permissions. Reviewers approve substantive verdicts and disclosure scope. Detection signals are probabilistic; final authenticity and fraud judgments remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One approved input format, a bounded representative case set and the first two task modules: check whether the person on screen is genuine during live video calls; run alongside Zoom, Google Meet, Teams and Discord. Support the remaining modules with operator review: operate without recording calls, accessing audio or storing user data; process on-device without sending data to the cloud; verify authenticity with a single click; detect synthetic video and static photo spoofing; support several deepfake generators with ongoing additions; filter bad lighting, shaky video, heavy compression and distant faces to reduce false positives; read the meeting window directly via Windows Graphics Capture without virtual camera setup; fine-tune the detection model against new deepfake methods through an automated data collection pipeline; analyze both audio and video files for authenticity; route uncertain cases to expert analysis for a probability assessment; remove background noise and music for cleaner media analysis; detect on YouTube, WhatsApp, TikTok, Zoom and Google Meet through a browser extension; accept uploaded content for immediate evaluation and detailed insights; accept forwarded images, video or voice notes on WhatsApp and return a verdict within seconds; run detection in the background without manual uploads or a separate dashboard; let users run the tool's detection, a partner detection module, or both; detect cloned voices during live phone calls. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Zoom, Google Meet, Teams, Discord, YouTube, WhatsApp and TikTok via browser extension and Windows Graphics Capture. Cloud asset storage, design-file import/export and publishing destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Detection setup and sources, Live call and file review, Verdict record and delivery. Use a thumbnail gallery for cases, a large central review canvas with the media and signal timeline, and a right-hand panel for quality flags, model signals and reviewer comments. Let users compare signals side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant frame or segment. Make the task-specific outcome reviewer-confirmed authenticity verdicts linked to evidence visible beside its evidence, review state and value baseline.
