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Neural Defend

Video Screening Integration Recipe

Build video screening around separate visual and audio observations. Confirm upload authority, validate a documented video type and size, choose sampling deliberately, and call an official client or POST /detect/video. Branch on status before reading either modality. Preserve silent-video success, no-scorable-face rejection, and null audio fields as distinct states. If your application derives one overall decision, document that client-side policy and retain the original modality results.

Maintained byNeural Defend
Updated August 7, 2026
Siva Shankar, Co-founder and CTO of Neural Defend.
Siva ShankarCo-founder & CTO
An article-specific diagram for Video Screening Integration Recipe organizes key sections including 1. authorize intake and choose sampling, 2. analyze and preserve modalities, 3. route decisions and recovery.

1. Authorize intake and choose sampling

Confirm that the organization may upload the video and any embedded audio. Apply your disclosure, access, retention, and deletion rules before sending media.

Validate the documented format and 1.5 GB maximum. Keep the default frame count unless the use case has a reviewed reason to change it. More or fewer sampled frames can affect cost, latency, and evidence coverage, so record the chosen parameter.

2. Analyze and preserve modalities

Use detect_video, detectVideo, the MCP video tool, or the direct /detect/video operation. Depend on the normalized contract for the chosen client rather than mixing raw wire and client fields.

On success, store video and audio risk fields independently. If audio is absent, preserve null audio fields and the explanatory message. Do not turn missing audio into low audio risk.

An article-specific topic map for Video Screening Integration Recipe organizes key sections including 2. analyze and preserve modalities, 3. route decisions and recovery, 1. authorize intake and choose sampling.

3. Route decisions and recovery

Apply the review policy to each available modality. Medium remains inconclusive and high should escalate. If a client-side combined decision is needed, version the policy and preserve both original modality values for audit.

A no-face rejection means sampled frames did not yield a scorable single-face frame and neither modality has a score. Ask for a better authorized video when appropriate. On error, timeout, or unknown, withhold the authenticity decision and account for duplicate billing before retry.

Evidence boundary

Limitations

  • This recipe does not prescribe a universal sampling value, combined modality rule, or legal basis for processing video and audio.

Source record

Sources and references

  1. Neural DefendUnified Video Authenticity ScoreVerified August 7, 2026.
  2. Neural DefendNeuroVerify Detection API OpenAPI contractVerified August 7, 2026.

Model every state

Review the video result contract

Keep modality scores, silent video, face-policy rejection, error, and unknown outcomes distinct.

Read the results guide