Multimodal by default
Review frames, face motion, voice cues, and file forensics in one place so investigators are not left stitching signals together manually.
Video authenticity for trust-critical workflows
See through manipulated video before it shapes the story.
Vsafer.ai helps teams review uploaded or live video for synthetic tampering, voice anomalies, and file inconsistencies—then turns the result into a decision-ready report.
Video-first analysis
Explainable signals
Private deployment options
Human review ready
Illustrative analysis · briefing_video.mp4
Sample interface
Live scan
Flagged moments
Frames inspected
742
Flagged segments
19
Evidence layers
4
Exportable report
PDF
Built for
Trust & safety teams
Built for
Newsrooms & fact-checking
Built for
Enterprise security
Built for
Investigations & legal review
Product
A calmer, clearer authenticity workflow
Instead of returning a black-box verdict, Vsafer is positioned as a review system: scan the file, inspect the evidence, route the case, and keep the result usable for humans.
Explainable findings
Show flagged segments, suspicious intervals, and evidence summaries that help teams understand why a file is being escalated.
Workflow-friendly output
Turn each scan into JSON, case notes, or a shareable summary so moderation, editorial, security, and legal teams can act on the same signal.
Flexible deployment
Support cloud, private cloud, and isolated environments for teams that need authenticity checks without forcing a single operating model.
Detection
One decision, multiple evidence layers
Vsafer is presented as a layered detector: not just whether something looks wrong, but where and why the media breaks continuity.
Frame and face analysis
Spot temporal drift, edge artifacts, and unnatural continuity breaks
Use frame-by-frame analysis to surface the places where synthesis or manipulation tends to lose coherence across motion, face geometry, lighting, and lip movement.
- Consecutive-frame consistency checks
- Landmark drift and facial geometry changes
- Lip-sync and micro-expression anomalies
Lower risk
Higher risk
Voice and speech analysis
Inspect spectral artifacts and speech patterns that do not line up cleanly
Look for cloned-voice signatures, synthetic timbre, and alignment mismatches between speech, mouth motion, cadence, and expected acoustic texture.
- Waveform and spectrum anomalies
- Speaker consistency across the clip
- Speech-to-visual alignment cues
Suspicious timbre shift · 00:13–00:17
File and origin checks
Trace container anomalies, recompression patterns, and missing provenance clues
Inspect the media wrapper itself for codec irregularities, timestamp gaps, suspicious edits, and other signs that a file has moved through a synthetic or altered pipeline.
- Codec, bitrate, and recompression checks
- Container-level metadata review
- Timeline and provenance mismatch detection
codech264 → h264expected
audio streamaac remuxedreview
timestamp pathgap detectedrisk
edit chainre-encoded twicereview
Decision and report layer
Turn model output into something a reviewer can use and share
Collect the evidence into one review packet so an analyst, editor, moderator, or investigator can make a call without reverse-engineering the model output.
- Structured summary and confidence bands
- Flagged segments and reviewer notes
- Exportable reports for downstream workflows
Summary
Likely manipulated
Evidence groups
Frames
Voice
Metadata
Reviewer note
Escalate before distribution. Multiple evidence layers point to synthetic manipulation.
Use cases
Designed for the places where video trust breaks first
Different teams see different risks, but the buying pattern is the same: fast screening, clearer evidence, and a review path that feels operational, not experimental.
Newsrooms and fact-checking
Check sourced footage before publication, identify suspicious edits, and give editors a clearer reason to hold or publish.
- Verify inbound media quickly
- Review evidence with editorial context
- Create a shareable decision trail
Platforms and marketplaces
Screen user-submitted video for manipulation before it reaches feeds, listings, creator surfaces, or moderation escalations.
- Queue suspicious uploads automatically
- Support moderation with structured output
- Reduce manual triage time
Executive and enterprise communications
Review sensitive internal or external video communications when impersonation risk, fraud, or misinformation is a concern.
- Protect high-trust communications
- Screen recorded or streamed content
- Route issues to security teams
Investigations and legal review
Build a repeatable process for examining digital video evidence and preserving the reasoning behind each authenticity decision.
- Bundle findings into case-ready summaries
- Support auditability and handoffs
- Preserve context around flagged segments
API
Easy to picture inside an existing workflow
The site now frames Vsafer as API-friendly and operations-friendly: send a file or URL, receive structured findings, and forward suspicious cases wherever your team already works.
REST endpoints for upload, scan, and retrieve
Async jobs and webhook callbacks for larger pipelines
JSON output for trust & safety, security, or editorial review
Evidence-first summaries that humans can understand
POST
/v1/video/check
{
"asset_url": "https://cdn.example.com/briefing.mp4",
"mode": "async",
"webhook_url": "https://ops.example.com/vsafer-hook",
"policy": "editorial_review"
}{
"job_id": "scan_4021a",
"status": "completed",
"risk_score": 0.82,
"verdict": "likely_manipulated",
"findings": [
{
"type": "lip_sync_drift",
"range": "00:13-00:17",
"severity": "high"
},
{
"type": "voice_synthesis_cue",
"range": "00:14-00:16",
"severity": "medium"
}
],
"next_action": "escalate_for_human_review"
}
Operations
Enterprise signals without losing product clarity
Deepfake competitors sell trust with deployment flexibility, explainability, and operational depth. This version brings those signals into the page without making the experience feel cluttered or overbuilt.
Review queues
Send suspicious files into a workflow your team can triage quickly.
Private environments
Position Vsafer for teams that need cloud, private cloud, or isolated setups.
Case notes
Keep analyst reasoning attached to the evidence, not buried in side channels.
Exportable outputs
Pass findings downstream as JSON, summaries, or formal reports.
Policy route
editorial_review
Upload
Scan
Review
Export
Decision
Hold for analyst confirmation
Escalation reason
Multiple evidence layers triggered
Analyst note
File shows temporal inconsistencies around the speaker’s mouth movement and a likely synthetic voice signature during the same interval.
FAQ
Questions a buyer will ask on the first visit
These answers keep the page grounded in workflow, explainability, and deployment concerns instead of generic AI language.
Does Vsafer only check video?
Video is the headline use case, but the positioning also supports adjacent signals like voice analysis and file-level forensics so teams can reason about authenticity with more than one evidence layer.
Will the result be understandable to non-technical reviewers?
That is the point of the new design system. Instead of surfacing only a probability score, the page presents Vsafer as a product that explains flagged segments, severity, and recommended next steps.
Can this fit moderation, editorial, or security workflows?
Yes. The site is framed around structured outputs, queues, and API integration so it can make sense for moderation teams, newsroom verification, enterprise security, or investigative review.
What if a customer needs a private environment?
The redesigned page intentionally signals deployment flexibility, including cloud and private environments, because that expectation shows up repeatedly across enterprise-focused deepfake competitors.
Get started
Protect reality before the video ships.
Use this page as a sharper foundation for Vsafer.ai on desktop, tablet, and mobile—ready for a Cloudflare Pages upload.