Law enforcement
Authenticate video evidence and produce court-admissible forensic reports.
How the sector deploys itDeepVideoGuard
Know whether a video is real footage or an AI-generated fake. It runs many independent checks across the picture, the motion and the sound at once, then produces a single clear verdict together with an annotated report you can share, keep on file, or submit as evidence
DeepVideoGuard
Is The Footage Real?
Follow the evidence through a video
What it is
Deepfake video forensics
DeepVideoGuard helps organizations determine whether a video is authentic or shows signs of AI generated, altered, or manipulated content. It examines multiple signals across the video, including visual details, movement, facial behaviour, sound, and the consistency between what is seen and heard.
Instead of relying on a single clue, the platform brings together different layers of analysis to identify inconsistencies that may be difficult to notice through manual review alone. These findings are combined into a clear authenticity assessment, helping users understand whether the submitted footage appears real or requires further investigation.
Each analysis produces an easy to understand result supported by visual findings and a forensic report, giving investigators, security teams, media organizations, businesses, and other reviewers a practical way to verify video authenticity and document their findings.
A fake has to slip past all of them, not just one.
Try it here
Run a video through the eight modules
Drop a video here
MP4, MOV, WebM or MKV up to 200 MB
The eight modules start as soon as a file lands · 1 credit
1 credit per analysis
Run the same eight modules the platform runs, on a video of your own, with every module’s score.
3 / 3Free analyses left
See credit termsPreview of the output format. The module scores and the verdict shown here are derived in the browser from the file’s digest, not measured by the analysis engine. The SHA-256 is the one figure computed from the real bytes. Book a walkthrough to have footage of your own run through the live ensemble.
How it works
From an uploaded video to an evidence-ready verdict
- 01
Upload
Securely submit the video you want to verify for authenticity
- 02
Prepare
The video is securely prepared for analysis and integrity verification
- 03
Analyse
Visual, motion and audio signals are examined together for signs of AI generation or manipulation
- 04
Assess
The findings are brought together to determine whether the video appears authentic or potentially synthetic
- 05
Report and video
Receive a clear video authenticity result with supporting visual findings and an evidence ready forensic report
DeepVideoGuard · workspace01 Upload
Interface simulation: an illustration of the workflow, not a live analysis
- 01
Upload
Securely submit the video you want to verify for authenticity
- 02
Prepare
The video is securely prepared for analysis and integrity verification
- 03
Analyse
Visual, motion and audio signals are examined together for signs of AI generation or manipulation
- 04
Assess
The findings are brought together to determine whether the video appears authentic or potentially synthetic
- 05
Report and video
Receive a clear video authenticity result with supporting visual findings and an evidence ready forensic report
Product exclusiveness
What sets DeepVideoGuard apart
Multi signal video authenticity analysis
Interface simulation: an illustration of the workflow, not a live analysis
How it compares
Compared with a single method deepfake detector and traditional manual video review
Approach to detection
- Single method detector
- Partly: One method only
- Manual video review
- No: Human judgement alone
- DeepVideoGuard
- Yes: Many checks combined
Brings different findings into one clear result
- Single method detector
- No: A single score
- Manual video review
- Partly: Subjective opinion
- DeepVideoGuard
- Yes: One combined assessment
Reviews sound together with the picture
- Single method detector
- No: Usually picture only
- Manual video review
- Partly: Manual listening
- DeepVideoGuard
- Yes: Voice and visual review
Checks whether visible details behave naturally
- Single method detector
- No: Not covered
- Manual video review
- Partly: Trained experts only
- DeepVideoGuard
- Yes: Built in consistency check
Shows where the concern appears in the video
- Single method detector
- No: Score only
- Manual video review
- Partly: Written notes
- DeepVideoGuard
- Yes: Visual findings on the video
Report ready for evidence and documentation
- Single method detector
- No: Not available
- Manual video review
- Partly: Written statement
- DeepVideoGuard
- Yes: Structured forensic report
Identifies signs of AI generated or altered video
- Single method detector
- Partly: Varies by tool
- Manual video review
- No: Hard to see by eye
- DeepVideoGuard
- Yes: Dedicated authenticity checks
Handles higher volumes of video
- Single method detector
- Partly: Varies by tool
- Manual video review
- No: Limited by reviewer time
- DeepVideoGuard
- Yes: Automated processing at scale
The architecture
Many checks in, one clear verdict out
No single check can decide the outcome on its own
What goes in
One video
- Visual understandingScene and context
- Movement and timingMotion across frames
- Image detailFine visual patterns
- Facial appearanceFace and expression
- Lighting and reflectionsNatural light behaviour
- Voice and lip alignmentSpeech against mouth movement
- Unfamiliar manipulationStyles not seen before
- Signs of AI generationTraces left behind
Combined assessment · one result
Every check contributes to the final outcome, and each one carries a level of influence based on how dependable it has proven to be. Because the findings are weighed together, the assessment never rests on a single signal.
Authentic or synthetic
- Forensic reportPDF · prepared for review and documentation
- Annotated videoHigh definition · findings shown on screen
Use cases by sector
Use cases across sectors
Legal & courts
Establish whether submitted footage is genuine or synthetically generated.
How the sector deploys itMedia & journalism
Verify newsroom and user-submitted video before publication.
Government & elections
Counter video disinformation targeting officials and campaigns.
How the sector deploys itCorporate security
Investigate suspected deepfakes used in fraud and impersonation.
How the sector deploys itDeployment strategy
Upload a video, get a verdict and a report
01 · Submit the video
Interface simulation: an illustration of the workflow, not a live analysis
Under the hood
What the platform is made of
The structure, the processing, the security model and what you receive back.
- Architecture
- DeepVideoGuard runs as a set of independent services. A secure interface handles video submission, dedicated workers run the authenticity checks, and a protected store keeps the evidence for each analysis.
- Processing
- Every submitted video joins a managed queue and is analysed in the background. Users follow the progress as it runs, and request limits keep large volumes of video moving in an orderly way.
- Security
- Access is granted on a verified basis only. Accounts are confirmed by email, passwords are never stored in readable form, and media and reports reach only the authenticated owner.
- Outputs
- Each analysis returns a structured forensic report and an annotated video in high definition. The video shows where closer review may be needed, and the report can be confirmed as unaltered.
Frequently Asked Questions
DeepVideoGuard checks whether a video is authentic or shows signs of AI generated, altered or manipulated content. It examines several signals at once, including visual appearance, movement, facial behaviour, sound and the consistency between what is seen and what is heard. Because many independent checks run on the same footage, manipulated video has to pass all of them rather than only one. The findings are then brought together into a single authenticity assessment that is easy to read and act on.
Every completed analysis returns two things: a structured forensic report and an annotated diagnostic video in high definition. The report summarizes the authenticity assessment together with the supporting findings, in a form that is easy to review, share and keep on file. The annotated video shows where in the footage closer review may be required, rather than leaving you with a result alone. Between them, a reviewer can understand not only the outcome but the reasons behind it.
Yes. The forensic report is prepared for evidence and documentation workflows, and it carries an integrity value so it can be confirmed later as unaltered. It records the authenticity assessment alongside the supporting findings, so a reader can follow how the result was reached. Organizations use it for investigations, audit trails, compliance records and legal review, including law enforcement and the courts.
Videos can be submitted securely through the web platform or through the API, so verification fits either a manual review process or an existing system. Each submission is placed in a managed queue and analysed in the background, and you can follow the progress of the check as it runs. Because the work is queued and processed automatically, large or sudden volumes of video stay orderly. That makes the platform suitable for teams that verify video regularly rather than occasionally.
Access is granted on a verified basis only. Accounts are confirmed through email verification, passwords are never stored in readable form, and every session is checked before any video, report or result is released. Uploaded footage and finished reports are delivered only to the authenticated owner of the analysis. The platform is also hardened against attempts to reach content that belongs to another account.
The rest of the line
More in SyntheticMediaGuard
Where it runs
Industries deploying DeepVideoGuard
Each sector page covers the threat model, the controls, and the regulators that apply.
Verify video evidence with 8-module ensemble intelligence
Schedule a technical demonstration to run your video footage through our Multimodal VLM and forensic analysis engine.