AI That Understands Visual Truth

Visionyx AI analyzes images and video using advanced computer vision models to detect manipulation, deepfakes, and synthetic media — so teams can verify authenticity with confidence.

Explore features
Built for media, marketplaces, security teams, and compliance workflows. GPU-accelerated inference by design.
Newsrooms
Marketplaces
Security
Fintech
HR
eCommerce
Deepfake detection Authenticity score Video forensics Developer API
Authenticity score Higher = more likely real
87%
AI-generation probability
Face swap
Manipulation detected
Explainable signals
For reviewers: artifacts, compression anomalies, model signatures (roadmap)

The rise of synthetic media

AI-generated images and videos are growing exponentially. Verification is harder than ever — and trust is now a technical problem.

Deepfakes

Identity spoofing across interviews, video calls, and social platforms — increasingly convincing at scale.

Manipulated media

Edits that change evidence and narrative — often invisible without forensic analysis.

AI-generated images

Product photos, documents, and visuals that look authentic — but were never captured by a camera.

AI-powered visual analysis

Score authenticity, detect manipulation, and integrate into your pipeline via a developer-first API.

Deepfake detection

Detect face swaps, lip-sync artifacts, and identity spoofing patterns in video.

Authenticity scoring

Clear probability score with risk flags and explainable signals for reviewers (roadmap).

Video forensics

Frame-level analysis for recompression anomalies, edits, and synthetic generation traces.

Developer API

Integrate checks into moderation, KYC, QA, or incident response workflows.

Enterprise-ready

Role-based access, audit trails, and privacy-aware processing options (roadmap).

GPU-accelerated inference

Optimized for throughput and latency — batch processing and streaming pipelines.

Built with advanced AI

Transformer-based vision models, large-scale datasets, and GPU pipelines for training and inference.

Technology highlights

  • Vision Transformers + hybrid architectures for robust representation
  • Multi-signal ensembles for synthetic-media detection
  • GPU accelerated inference (batch + streaming workloads)
  • Continuous evaluation, dataset iteration, and model monitoring

Roadmap

Q2
2026 — Training & dataset expansion Scale training pipelines, improve coverage, and harden evaluation benchmarks.
Q3
2026 — Private beta API Onboard early partners and validate workflows and performance targets.
Q4
2026 — Platform launch Dashboard + API availability, documentation, and initial enterprise features.

Use cases

Designed for teams that need reliable signals on whether visual content can be trusted.

Media & journalism

Verify user-submitted media and reduce the risk of publishing manipulated visuals.

Fraud detection

Flag synthetic identity media, document tampering, and spoofing attempts.

Marketplace verification

Detect AI-generated product photos and reduce counterfeit or misleading listings.

Security & investigations

Automated first-pass authenticity signals for evidence review and triage.

HR & interviews

Mitigate deepfake interview fraud and identity spoofing during remote hiring.

KYC & compliance

Support review teams with scoring + explainable indicators for decisions.

FAQ

A few quick answers for partners and early adopters.

Do you offer an API? +

Yes — access is provided to a small set of early partners. Share your use case and expected volume to get onboarded.

What kind of content can you analyze? +

We focus on image authenticity scoring, deepfake detection, and video forensic signals. Coverage depends on model evaluation milestones.

How do you handle privacy and data? +

We align on data handling and retention per partner needs, and plan privacy-aware processing options with audit logs for enterprise workflows.

Build trust into your visual pipeline

Get early access or request API details for your workflow. We’re onboarding a small set of partners.