Manually analyzing large video sets for judgment and spreadsheets

Journalists and researchers must analyze 178 videos by hand to create open-source spreadsheets explaining judgments, with no good automation.

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FL score

42

out of 100

Verdict

SKIP

medium confidence

Competition

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Trend

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Build software to help journalists and researchers annotate video datasets and export structured judgments, replacing manual spreadsheet work.

The pain

Journalists and researchers spend weeks manually watching videos, taking notes, and transcribing findings into spreadsheets. The 178-video example suggests this is repetitive, error-prone, and delays publication of findings. No existing tool handles the specific workflow of video review + judgment capture + structured export.

The gap

Video annotation tools exist (Adobe, Frame.io) but focus on editing or collaboration, not judgment documentation. Spreadsheet templates exist but require manual data entry. Nothing bridges video playback with structured judgment capture and automated export.

Build angle

Start with a focused tool: video player + side panel for judgment entry (checkboxes, dropdowns, text fields) + one-click spreadsheet export. Target open-source research projects and journalism outlets doing investigations. Charge per project or per video analyzed, not per seat.

Strengths

  • Clear, specific pain point with measurable scope (178 videos = quantifiable time savings)
  • Open-source positioning creates goodwill and potential for adoption by NGOs, universities, news organizations
  • Spreadsheet export is table stakes, easy to validate demand and measure success
  • Video annotation is a growing category; adjacent tools (Prodigy, Label Studio) prove willingness to pay

Risks

  • Market may be too small, only journalists and researchers doing large-scale video analysis, not a broad audience
  • Customers may prefer free open-source tools or building internal solutions rather than paying for SaaS
  • Video processing and storage costs could erode margins if you host videos
  • Unclear if the problem is the tool or the process, better workflow might be hiring annotators, not software
  • No evidence of willingness to pay; open-source positioning conflicts with revenue model

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