When processing thousands of supplier certificates, Safety Data Sheets (SDS), and packaging recyclability reports, generative AI is great for speed—but terrible if left unsupervised.
Here are 3 core rules we follow when building AI-assisted compliance tools:
Q: Where should the AI live in the stack?
A: Strictly at the extraction stage, never at the validation stage. Use Vision Transformers or LLMs to extract unstructured data from PDFs into structured JSON.
Q: How do you verify accuracy?
A: Pass extracted data through a deterministic rule engine. The rule engine checks numbers against hard regulatory thresholds (e.g., ingredient concentration limits). AI extracts; code validates.
Q: What happens when confidence is low?
A: Implement a Confidence Score Threshold. High-confidence data processes automatically; low-confidence fields flag instantly with direct link-backs to the exact paragraph in the source document for human review.
The takeaway: AI should eliminate manual typing for regulatory teams, not make final compliance decisions.
