VideoLens
Open source · MIT licensed · ~1,500 video platforms supported

Turn any video into a timestamped, evidence-grounded report.

Drop a bug recording, a meeting, a demo, a tutorial. Ask anything. VideoLens returns a structured analysis with citations to specific moments in the video — for humans or AI agents.

Free. Bring your own OpenAI API key — we never store it, never see it. You stay in control of cost and data.

Local files YouTube Loom Vimeo TikTok Twitch Twitter/X + 1,490 more
What it does

Three steps from video to insight.

Most video tools wrap Whisper and stop. VideoLens combines transcription, frame-level vision, and prompt-directed analysis into one cached pipeline.

Drop any video

Local files, YouTube, Loom, Vimeo, TikTok, Twitter/X, Twitch, Reddit, Google Drive, direct URLs. Roughly 1,500 platforms via yt-dlp.

Ask anything

Three modes built in — General, Bug, Meeting — plus your free-form prompt. Each mode tunes the analyst for what matters: repro steps, decisions, frictions, claims.

Evidence at every step

Every finding cites a specific timestamp. Click any citation in the UI to jump the player to that moment. Output as PDF, Markdown, or JSON.

How it works

A cached pipeline you can trust.

Resolve the source. Extract everything. Build a timeline. Synthesize a report. Each step is cached at .videolens/cache/<hash>/ so re-runs are cheap and follow-up questions cost cents.

1 · RESOLVE

Source classification

Detects local file, YouTube, Loom, Vimeo, direct URL, generic page. Reports limitations clearly when a site isn't fully supported.

2 · EXTRACT

Audio + frames + OCR

yt-dlp fetches remote video, ffmpeg samples frames and chunks audio, OpenAI transcribes each chunk, GPT-5.4-mini describes every frame and reads any visible text.

3 · TIMELINE

Time-windowed merge

Frame summaries and transcript segments are merged into time-windowed segments — each with visual, OCR, transcript, scene type, and confidence.

4 · ANALYZE

Mode-driven synthesis

One GPT-5.5 call against the timeline, your prompt, and the active mode → structured findings, evidence citations, recommendations, and ticket-ready tasks.

Built-in modes

A different analyst for each kind of video.

🎬

General

--mode general

Broad review: what's happening, what stands out, what's worth knowing.

Use for: tutorials, demos, content reviews, any video you just want explained.

🐛

Bug

--mode bug

Bug recordings → reproduction steps, severity hint, ticket-ready summary, possible root-cause areas.

Use for: screen recordings of broken UIs, crashes, session replays of failed flows.

🗣️

Meeting

--mode meeting

Decisions, objections, commitments, follow-ups. Uses diarized transcription when available.

Use for: Zoom / Teams / Meet recordings, standups, briefings, sales calls.

🛠️
Coming next: UX (session-replay analysis), Tutorial (step extraction), Product Demo (feature inventory), Content Critique, Privacy (sensitive-info redaction). Each mode is a small prompt-fragment file — adding a new one is ~30 lines.
Quickstart

Run it locally in two minutes.

Python 3.12+, ffmpeg, and an OpenAI API key. That's the whole list.

1 · Install
# macOS
brew install ffmpeg
git clone https://github.com/shadoprizm/videolens.git
cd videolens
uv sync --extra ui
2 · Run
export OPENAI_API_KEY=sk-...

# Web UI
uv run videolens ui

# Or CLI
uv run videolens analyze ./bug.mov \
  --mode bug --prompt "What broke?"
💡
Rough cost: a 5-minute video with 20 frames ≈ $0.20 via OpenAI. A 30-minute meeting ≈ $0.50–$1.50. Per-prompt analysis cache means follow-up questions on the same video cost only cents.
Live now · app.videolens.io

Skip the install. Try it in your browser.

The hosted app is up. Drop a video, paste a prompt, get a timestamped report. You bring your own OpenAI API key — we never store it and we never pay for your calls. It's the same code as the open-source repo, just hosted.

Launch app.videolens.io

Your key, your cost

Paste your OpenAI API key in the sidebar. Calls go straight to OpenAI; you only pay them, not us.

Session-only storage

The key lives only in your browser session. Close the tab, it's gone. We don't write it to a database.

Same code as the repo

Self-host the identical app any time. Public MIT-licensed code on GitHub.

Need an OpenAI API key? Get one at platform.openai.com/api-keys · A $5–10 prepaid balance is plenty to test.

Chrome extension

Analyze the video you're already watching.

VideoLens Pro lives in your browser's side panel. Open any YouTube video or HTML5 player, pick a mode, and get the same timestamped, evidence-grounded report — without leaving the tab. Local files work too.

  • All 8 analysis modes: bug, meeting, UX, tutorial, demo, content, privacy, general
  • 100% in-browser pipeline — no server, nothing uploaded to us, ever
  • Bring your own OpenAI key; the key never leaves your device
  • Follow-up Q&A, markdown & JSON export

Heads-up: DRM-protected players (Netflix, Disney+, …) can't be captured. Live streams aren't supported.

$29 one-time

No subscription. No usage markup — analysis costs go straight to your own OpenAI account (typically $0.05–$1.50 per video).

  • 3 free analyses to try it first
  • Unlimited analyses after purchase
  • License works on up to 3 devices
  • Free updates
Buy VideoLens Pro Chrome Web Store — coming soon

Your license key arrives by email right after checkout.
14-day refund policy, no questions asked.

Roadmap

Where this is going.

Q&A loop

"Analyze once, ask many times" — follow-up questions reuse the cached timeline for cents instead of dollars.

MCP server

Native Model Context Protocol server so Claude Code, Cursor, and other agents can analyze video as a first-class tool.

Semantic search

Embeddings over processed timelines: "find where they talked about pricing", "find every error message", across your whole library.

Session-replay parsers

PostHog, Clarity, Hotjar, FullStory, LogRocket, OpenReplay — read event exports, not just rendered video.

FAQ

Questions, answered.

Everything you need to know about how VideoLens works, what it costs, and how your data is handled.

What is VideoLens?

VideoLens is an open-source video intelligence tool that turns any video into a timestamped, evidence-grounded report. You drop in a video — a local file or a link from roughly 1,500 supported platforms — ask a question, and it returns structured findings that cite specific moments in the video. It's MIT licensed and built for both humans and AI agents.

How does VideoLens work?

VideoLens runs a four-stage cached pipeline. It resolves the video source, extracts audio, sampled frames, and on-screen text (OCR), merges them into a time-windowed timeline, then runs one analysis pass against your prompt and chosen mode to produce findings with timestamp citations. Each step is cached, so re-runs are cheap and follow-up questions cost only cents.

Is VideoLens free?

Yes. The core tool is free and open source under the MIT license — self-host it or use the hosted app with your own OpenAI API key. You pay only OpenAI's usage, roughly $0.05–$1.50 per video. A one-time $29 VideoLens Pro Chrome extension adds an in-browser side-panel workflow.

What video platforms does VideoLens support?

Local files plus roughly 1,500 platforms via yt-dlp, including YouTube, Loom, Vimeo, TikTok, Twitch, Twitter/X, Reddit, and Google Drive. DRM-protected players such as Netflix and Disney+, and live streams, are not supported.

Does VideoLens store my videos or my OpenAI API key?

No. Videos are processed on your own machine, in your browser (the extension), or in an ephemeral session (the hosted app). Your OpenAI API key stays on your device or in session memory only and is sent only to OpenAI. VideoLens runs no analytics on your video content and never stores your reports.

How much does it cost to analyze a video?

Analysis costs go straight to your own OpenAI account, typically $0.05–$1.50 per video. A 5-minute clip with 20 frames is about $0.20; a 30-minute meeting is roughly $0.50–$1.50. Cached timelines make follow-up questions on the same video cost only cents.

Can AI agents use VideoLens?

Yes. VideoLens outputs structured JSON with evidence citations and ships a native Model Context Protocol (MCP) server, so agents such as Claude Code and Cursor can analyze video as a first-class tool.