360 NACH Ai: how it works.
Operations-focused analysis, built on a general vision-language model — not a separately trained proprietary business model.
What is actually trained?
The underlying model is pretrained by its provider. 360 NACH Ai does not currently fine-tune model weights or train a new model on a private business-video dataset. We cannot verify or list the provider’s complete training data.
What we add
Operations-focused instructions draw on Lean, Six Sigma, Theory of Constraints and 5S. Industry checklists guide attention toward queues, movement, handoffs, downtime and safety concerns. This is instruction-based specialization, not additional model training.
From footage to report
Your browser extracts ten timestamped snapshots. Only those images and the context you enter go to AI analysis. A structured report connects observed evidence to prioritized bottlenecks, practical actions and metrics to check.
How it differs from a generic video description
| Focus | A generic description task | 360 NACH Ai’s approach |
|---|---|---|
| Question | What appears in this scene? | Where could workflow friction be occurring? |
| Context | Often a broad visual summary | Your industry and operational context |
| Output | Objects and activities | Evidence, waste categories, priority and an action plan |
| Follow-up | A descriptive caption | Suggested effort, timeframe and a metric to monitor |
This compares task designs, not every competing product. Other tools may offer similar or stronger capabilities; no comparative benchmark has been established.
Limits worth knowing before you act
Ten snapshots can miss rapid events and cannot establish continuous cycle times, causation or live-feed performance. Flow scores and recoverable-time estimates are directional, not audited measurements. Cost estimates depend on your inputs and are not guaranteed savings. Review findings with staff and measure the process before making changes.
Snapshots are sent to an external AI provider. Full video files stay on your device in the upload flow; that does not mean snapshots are never retained by the provider. Remove sensitive information and obtain permission from people shown. The app does not implement a training pipeline for uploads.
What genuine custom training would require
A future custom-trained version would need authorized footage, expert-labeled bottlenecks and outcomes, a separate evaluation set, fine-tuning infrastructure and measured performance against a baseline. Those steps are not completed or claimed for the current product.
Try your own footage