Video import

Record a walkthrough, import it, and your AI coworkers can reference it while they code. Design rationale, bug reproductions, architecture explanations — all searchable and accessible to every AI coworker on your team.

Supported sources

Import from the tools you already use:

How it works

You record. SageOx does the rest. Every recording goes through an extraction pipeline that turns video into structured, searchable artifacts.

The pipeline runs automatically after upload. When it finishes, extracted artifacts commit to your Team Context — the shared knowledge base every AI coworker reads at session start.

What gets extracted

Each recording produces structured artifacts:

discussions/2026-03-20-ux-review/
├── transcript.vtt        # timestamped speech with speaker labels
├── summary.json          # chapters, decisions, action items
├── keyframes.json        # frame images + vision descriptions
└── metadata.json         # title, participants, duration

Your AI coworkers consume these artifacts to understand what was discussed, what decisions were made, and what the UI looked like. They don't watch the video — they read the structured output.

Import methods

Web app (recommended)

The fastest way to import a single recording:

1. Go to your team's Media section
2. Click Import and paste a Loom, Figma, or Cap URL
3. Or click Upload to drag and drop a local file

Processing starts automatically. You'll see progress in the pipeline view.

CLI

Import directly from your terminal without leaving your editor:

ox import https://www.loom.com/share/abc123 --title "Sprint Planning"
ox import --status rec_01234567 --watch  # track progress

See Video Import via CLI for details.

Supported formats

Recording tips

For best results:

• Narrate as you go — Transcript quality drives extraction quality. Silent recordings produce no searchable context.
• Keep it focused — 5-10 minutes is ideal. Split longer sessions by topic.
• Use descriptive titles — Your AI coworkers search by title. "Sprint 12 Checkout Flow Redesign" beats "Recording 47".

See Cap Setup for optimal export settings.

Use cases

How AI coworkers use recordings

When Claude Code starts a session, it receives your Team Context including:

• Transcript text — Searchable narration from your recordings
• Keyframe descriptions — AI-generated descriptions of visual content
• Summaries — Chapters, decisions, and action items extracted from each recording

Your AI coworker can cite specific recordings when explaining decisions or implementing features based on recorded design intent.

Getting started guides

What's next

• Web Recorder — record directly from your browser
• Discussions — all ways to capture team knowledge
• Team Context — where imported recordings live
• Distillation — how recordings become team memory