AI-powered barcode scanning means workers always capture the barcode they intend to scan, even when it's damaged, crowded, or out of reach.
Traditional scanners trigger on any code in view, forcing workers to bend, cover nearby labels with a finger, or retype values from damaged barcodes. The Scandit AI Engine reads context and user intent in real time, so the right barcode is captured the first time.
What you'll see
- Reading a damaged barcode with OCR: when a label is too damaged to decode, the scanner falls back to the human-readable text and returns the value anyway.
- Selecting the right code in a crowd: in dense environments the interface adapts automatically and shows an aimer, so workers point at the barcode they want instead of covering the others.
- Scanning at a distance: intent anticipation captures the intended barcode from a natural working distance, with no bending and no string of wrong scans.
- Handling duplicate barcodes: analyzes user behavior and context to determine whether a duplicate scan represents a new item with the same code, or an accidental re-scan of the same item.
Key features
- Automatic OCR fallback for damaged or unreadable barcodes
- Adaptive aimer that appears only in dense, crowded environments
- Intent anticipation that ignores background and peripheral codes
- Smart duplicate filtering that separates intentional re-scans from accidental ones
- Enabled by default in SparkScan and Barcode Capture, with no manual configuration
Why it matters
These improvements compound at scale. Across an entire fleet of workers scanning millions of barcodes a day, AI-powered scanning removes the small mistakes that slow workflows and pollute downstream data.
Get started
See the full feature set in the AI-powered barcode scanning documentation, see the Barcode Scanner SDK, or start a free trial.