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from scanning to acting. With the release of our Scandit SDK 8.0, we’ re embedding intelligence directly into the data-capture workflow: adaptive barcode, text, and object recognition; augmented reality( AR)-guided tasks; and edge-based decision-making so frontline teams in manufacturing, warehousing, and logistics can act in the moment.
In parallel, we’ re constantly improving Scandit Express- a fast-track implementation offering designed for manufacturers who want to deploy smart data capture with minimal custom code and time to value. It’ s a great turnkey solution for businesses that have existing hard-to-modify apps or that simply don’ t have enough development resources to integrate an SDK.
At the same time, we’ re investing heavily in our AI-powered shelf-intelligence solution, ShelfView. While it’ s currently designed with grocery retail in mind, even serving CPG manufacturers with shelf-level information( e. g., share of shelf, number of facings), some of the underlying capabilities may also prove valuable in certain factory or warehouse settings over time.
What are the most common data capture challenges you see manufacturers facing today? Most manufacturers don’ t suffer from a lack of data- they suffer from a lack of reliable data captured at the frontline. We still see fragmented systems, manual workarounds, and legacy hardware that create blind spots in traceability. And whenever workers are keying in serial or batch codes manually, accuracy drops, and productivity is low. For example, 60 percent of SKUs are affected by inventory record inaccuracies. The result is a disconnect
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