Neural Defend platform
Compare deepfake detection software by workflow.
Neural Defend is a media authenticity platform for applications, investigation teams, video meetings, and customer calls. It does not present one universal AI deepfake detector. Start with the task, then choose the product that fits where evidence enters your workflow.
The live products include a deepfake detection service through the NeuroVerify API and an investigation workspace. One product is Beta, and one is Coming Soon.
A product signal informs the next step. It does not make the final customer decision.
Start with your task
Where does the evidence need to be checked?
Pick the closest workflow. The selector shows the matching product, its current status, and why it belongs at that point in the decision path.
NeuroVerify
An application or agent needs a result before it continues.
Use NeuroVerify when software needs structured risk and signal fields during onboarding, claims, recovery, approvals, or platform workflows.
Authorized image or video through the current public API contract
Structured status, risk, and signal fields
Customer policy or reviewer
One family, four operating roles
Choose the deepfake detector that fits the operating role.
Each deepfake detection tool has a defined interface, status, and handoff. Some checks belong inside software. Others need a reviewer or a live-session response.
NeuroVerify
LivePlace an authenticity check inside onboarding, claims, recovery, approval, platform, or agent workflows.
Structured risk and signal fields return to customer policy.NeuroDetect
LiveGive authorized reviewers a workspace for examining suspicious images, audio, video, and documents.
Evidence-linked findings support an analyst-owned conclusion.NeuroCall
BetaSurface an authenticity signal for authorized customer-call streams and contact-center response paths.
Agents and fraud policy control the response.NeuroMeeting
Coming SoonPlan participant audio and video analysis for selected meetings, with participant-level signals for the host.
The host will be able to request another check and review the session trail.The shared platform flow
How the deepfake detection platform hands off evidence.
Each product has a different interface, but the responsibility boundary stays consistent. Neural Defend supplies evidence or a risk signal. The customer retains the decision.
Receive media
An application, workspace, meeting, or call supplies authorized media.
Inspect signals
The selected product examines relevant visual, audio, temporal, or document signals.
Return evidence or risk
The product surfaces structured fields, linked findings, or a live alert.
Customer decides
Customer policy, an agent, a host, or an authorized reviewer chooses the action.
Synthetic media detection platform coverage
Product scope and public API scope are separate facts.
A modality is a kind of media, such as an image, video, audio recording, or document. This view describes each product surface; the developer contract is called out separately below.
| Product | Operating role | Image | Video | Audio | Document |
|---|---|---|---|---|---|
| NeuroVerifyLive | Application / API | Product + public API | Product + public API | Video audio track | Product scope |
| NeuroDetectLive | Investigation workspace | Review | Review | Review | Review |
| NeuroCallBeta | Call security | Not applicable | Not applicable | Live stream | Not applicable |
| NeuroMeetingComing Soon | Meeting protection | Not applicable | Planned live participant | Planned live participant | Not applicable |
The published endpoints cover images and videos.
A video response can contain separate video and audio-track fields. The public contract does not publish standalone document, audio, or C2PA validation endpoints. Confirm any additional interface during evaluation.
Continue from product fit
Review the foundation, boundary, and test plan.
Product selection is the first decision. Technical architecture, deployment constraints, result handling, and failure behavior still need to be confirmed for the intended workflow.
Understand the shared detection foundation.
See how media analysis, integration interfaces, and the wider product family fit together.
Explore the technologyChoose the operating boundary during evaluation.
Review integration and deployment paths, then confirm product-specific availability and requirements.
Review deployment pathsTest the workflow, outputs, and fallback.
Bring representative authorized media, the decision path that consumes the result, and the fallback for no usable result.
Prepare an evaluationLimits that belong in the decision
A media signal answers a narrow question.
It helps a person or system assess whether submitted media shows signs of generation, manipulation, spoofing, or other supported risk. The surrounding claim still needs its own evidence and policy.
A result does not identify a person, infer intent, establish fraud, or determine whether a statement or claim is true.
Low risk means the analyzed signals did not cross the applied threshold under those conditions. It is not proof that the media is authentic.
Customer policy and authorized people define thresholds, fallback behavior, additional checks, review, and final action.
Choose with your workflow
Evaluate the product where the decision actually happens.
Bring representative authorized media, the people or system that receive the result, and the fallback when no usable result is available. The evaluation can then define product fit and a responsible response path.