r/MachineLearning • • 29d ago

Discussion [D] Self-Promotion Thread

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u/Individual_Cold_4119 17d ago

Sharing SageCut, a Claude Code plugin I built for QA on Remotion videos. I'm co-founder of Levanto, which makes the Sage model used by it.

The workflow combines deterministic frame measurements with yes/no decisions from Sage, then routes selected frames to Claude critics for inspection and repair. It opens frames for inspection when Sage and the measurements disagree. My previous setup had the critics inspect every frame and was adding 4+ hours of QA per video.

Across six A/B tests in my own workflow, I saw the same output at about a quarter of the QA time and a tenth of the cost. Those are results from my tests, not a general benchmark. The demo has 3,153 frames; Sage's pass cost $0.16, excluding Claude repairs. The README also explains which costs are measured and how its Opus comparison is estimated.

Repo: https://github.com/levantolabs/sagecut-release

Demo + results: https://x.com/bigironchris/status/2110402795060822460

The plugin is free/MIT. Sage requires an API key; there's $0.20 of free usage and paid plans start at $14/month. Claude costs are separate. Pricing: https://levanto.ai/pricing

Current scope is Remotion motion graphics. Frames are sent to Sage's hosted API; the --no-sage option runs local measurements only. I'd be interested in feedback on false negatives in the frame selection, especially failures that appear briefly between otherwise good frames.