Social media decision
NoViolation
A competent developer can build a useful, smaller replacement (audio+visual checks, transcript-based rules, PDF appeal) in about a week and modest monthly operating cost; you lose the vendor's tuned models, UX polish, and ongoing policy maintenance but not core functionality.
Visit website↗$15/mo
$180/yr
Read off the official pricing page.
$100one-off40 h to build
$50/mo6 h/mo upkeep
On cash alone, building overtakes the subscription at 4 seats.
No open-source build does this yet
Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.
What a replacement has to do
- User uploads video → extract audio and frames → run audio transcription and keyword/policy checks → run visual detectors for gestures/symbols → aggregate findings into a report and appeal text/PDF → display results in web UI.
What it still won’t have
- Proprietary tuned detection models and ongoing labeled-update cycle
- Polish of the commercial appeal assistant and PDF templates
- Scale, performance optimizations and dashboard polish for many simultaneous users
- Threat intelligence / up-to-date mapping to TikTok policy nuances maintained by the vendor
- Brand trust and the convenience of packaged scan-packs/subscriptions
What remains hard
- Product polish and ongoing maintenance
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 4 seats.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a minimal self-hosted TikTok violation scanner: use Python (FastAPI) backend, React frontend, Postgres for scan history, S3-compatible blob storage, FFmpeg for frame/audio extraction, OpenAI/Whisper or local Whisper/WhisperX for transcription, and a YOLO/Detections model (e.g., YOLOv8 or VideoPipe components) for visual detections. Core features in scope: video upload UI, FFmpeg-based extraction job, transcription + keyword/policy rule engine, visual detection pipeline that flags gestures/symbols, aggregation into a results page and a generated PDF appeal with suggested text, simple per-user scan counter. Out of scope: multi-tenant billing integration, mobile apps, advanced UI polish, large-scale queuing. Include error handling, retries for extraction/transcription jobs, automated tests for pipeline steps, and Docker-compose deployment manifest.
How we checked
How the score was reached
- Build verdict base78
- 2 cited sources+1
- Price verified on pricing page+3
- Evidence score82
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.
How scoring works →Cited sources · 2
Every page the run actually retrieved.
- official productNoViolation - TikTok Violation Checker
- official pricingPricing - NoViolation.ai
Integrity checks
What held up, and what did not.
