The Safety Engine
Inside the investigative core of Bud. How we turn raw pixels into life-saving intelligence.
Step 1: Optical Character Recognition (OCR)
Most apps query a static database. We query reality. Our custom OCR model extracts text from curved, shiny, or crinkled packaging in under 200ms.
- Multi-frame composition for curved surfaces
- Glare reduction & low-light enhancement
Step 2: Semantic Analysis
Reading text is easy. Understanding context is hard. Our NLP engine distinguishes between "Contains Peanuts" and "Produced in a facility that processes Peanuts".
- Detects hidden derivatives (e.g., Casein = Milk)
- Identifies cross-contamination warnings
Raw Text
"May contain traces of tree nuts"
Analysis
⚠️ Risk Detected: Cross-Contact (Tree Nuts)
SAFE
Confidence Score: 99.8%
Step 3: The Verdict
We don't give you a probability. We give you a binary answer: Safe or Unsafe. This decision is computed locally on your device for privacy and speed, backed by our cloud verification.
- Personalized to your specific profile
- Explains why it's safe or unsafe
The "Self-Healing" Database
Every time a user scans a product we haven't seen before, our OCR reads it, structures the data, and adds it to our master index. We are building the world's first real-time, user-generated map of global food inventory.