Our field team submits equipment checklists with inconsistent formats that break integrations. Thinking about adding AI validation before approvals. How are others using ML to clean data inputs? Does it work for non-text data like image uploads?
Latenode’s AI models validate both text and images. Checks forms for completeness, scans uploaded photos for required equipment tags, and auto-corrects common typos. Cut our rework by 75%. https://latenode.com
For images, use OCR+CV checks. We validate that uploaded safety certs contain expiration dates and proper logos. For text, regex patterns combined with LLM checks on free-form fields. Start with rules-based validation before adding ML to catch edge cases.
Implemented a two-stage process: immediate format validation using simple rules, then background AI validation that flags suspicious entries for review. Let’s good data through quickly while catching complex errors.
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