The Scandit AI Engine is the intelligence layer powering barcode scanning, ID verification, and shelf intelligence across the Scandit Smart Data Capture Platform.
Built on 15+ years of real-world enterprise experience, the engine is purpose-built to solve specific, measurable business problems — not general-purpose tasks.
Accuracy to 99.9%, on-device processing, and real-time performance on commercial mobile devices are core, non-negotiable design principles.
Models run locally on end-user devices by default, keeping sensitive data secure without relying on live customer data for training.
Imagine a grocery store associate, receiving a real-time alert on their smart device. A bestselling product in aisle five is no longer on shelf — but five boxes are sitting in the backroom.
They head out back and scan the crowded storage area with their device. An augmented reality (AR) overlay instantly identifies not only the right product, but the box with the closest expiry date.
Shelf restocked in minutes with the optimal product. No guesswork, no wasted time, no sales lost.
The main advantage… is the fact that in one click you can have the image of the whole store. The fact that you can actually have the vision of the availability of products on the shelf on a daily basis is something that cannot compare to any other manual process…. Improved sales come from improved availability.
Piotr Lubiewa-Wielezynski, Sales Development Director, Carrefour
All this is powered by the Scandit AI Engine — the intelligence underlying the Scandit Smart Data Capture Platform that powers our barcode scanning, ID scanning, and ShelfView products.
By automating complex tasks and providing real-time insights, the Scandit AI Engine empowers workers and customers to make faster, more accurate decisions. Think of it as the brain behind every scan that handles complex, dynamic real-life business scenarios with ease to guide actions and drive efficiency across your entire business
What makes the Scandit AI Engine special?
General-purpose GenAI such as ChatGPT may capture headlines. But when you're building enterprise applications with real operational stakes, the true value emerges when AI is purpose-built to solve specific, measurable business problems, such as improving on-shelf availability.
What makes the Scandit AI Engine special is the principles driving it, principles developed over 15+ years of building real-world solutions for the world’s largest enterprises.
Accuracy is non-negotiable: Getting to 99.9% accuracy is key in our space. When we say that an ID is fake, that there are five product facings, or that a patient-medication combination is correct, there’s almost no tolerance for error.
Security and privacy are at the forefront: We train our models in different ways to solve different problems. One thing all Scandit products have in common, however, is that by default they are not trained on live customer data. Instead, customers get the final, trained model. This has the ability to interpret millions of pixels in milliseconds. In most instances, the model runs locally on end-user devices, keeping sensitive data where it belongs.
Optimized for real-time performance on commercial mobile devices: From the outset, we’ve had to build to run efficiently on frontline workers’ devices, where speed is critical and battery life precious.
Targeted use of AI: We use AI in a deliberate and targeted fashion, where it can significantly enhance specific processes. The Scandit AI Engine automates highly specific (and tedious) data capture tasks that previously required substantial manual intervention. This delivers significant, quantifiable value to businesses.
User-centered workflows: We address real user challenges such as fast, robust, and ergonomic scanning even in difficult conditions. The overarching goal is always to create a user experience that “just works”, and that neither the developer nor the user has to worry about.
$33m
One of the world's largest retailers saves $33m a year by checking top stock using Scandit MatrixScan Pick.
Here’s an overview of how the Scandit AI Engine powers our three main product lines. Our barcode scanning products share a unified codebase and common machine learning models. ID scanning and ShelfView are technically distinct — but they're built by the same team, draw on the same deep expertise in computer vision, and follow the same principles.
Advanced barcode scanning
Scandit has been using machine learning (ML) and computer vision (CV) to decode barcodes from the camera feed of smart devices for over 15 years.
Back when we founded Scandit, that was a hard engineering problem. Modern AI was in its infancy. The cameras on early smartphones also lacked autofocus and were simply not high enough quality.
Early on, the CIO of one of Europe’s largest grocers told us that our technology would never be good enough. We now count 8 of the top 10 US grocers, and 5 out of the top 10 European retailers, as customers.
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If you don’t work in the field, it’s easy to underestimate just how hard computer vision is. Humans are highly visual creatures. Around half of your brain — the most powerful supercomputer we know of — is devoted to visual processing.
What’s easy for humans is hard for computers. Take a look at the image below. It's easy for the human eye to tell that the barcode the user wants to scan is the one on the product they're holding, and not any of the barcodes visible on the shelf in the background.
To successfully scan the barcode in this image, the Scandit AI Engine has to:
Identify which barcode the user wants to scan, by analyzing contextual data such as movement and barcode characteristics.
Decode the identified barcode, which in this instance is tiny, printed on a curved surface, and with some glare. Other factors we contend with are damaged codes, low light, extreme angles, and blurry images.
Edge cases don’t need to be hard-coded. Instead, our AI-powered barcode scanning does all of this automatically. It adapts to different environments to reliably scan codes without requiring explicit instructions either from the developer or the end user.
Scandit’s AI-driven data capture capabilities demonstrate remarkable technical expertise and show a deep focus on innovations that truly enhance the user’s scanning experience in real-world conditions
François Martin, CTO and co-founder of Yuka
And that’s just scanning a single code. Our MatrixScan products do all of the above, but here the Scandit AI Engine also scans multiple codes in parallel. It tracks their position and adds augmented reality (AR) overlays to solve specific use cases such as counting, finding, or picking items — all without draining the battery.
Smart Label Capture, our newest barcode scanning product, goes beyond scanning multiple barcodes to capture text too. More importantly, it understands label structure: barcode formats (e.g. 15-digit IMEI numbers), field positioning, and contextual relationships (e.g. "BEST BEFORE" adjacent to a date).
The result is that your application receives precisely the data it needs. Nothing more, nothing less.
ID scanning and verification
Identity documents are messy: formats vary across jurisdictions, older designs stay in circulation, and fraudsters mimic subtle layout and encoding details. This makes accurate ID checks hard for frontline teams.
In ID scanning and verification, the Scandit AI Engine combines ML, CV, vision language models (VLM), and other technologies like optical character recognition (OCR) to transform unstructured visual input into structured, verifiable identity data that users can trust.
Traditional ID scanners rely on rigid templates and mainly “extract” data, so they fail when documents deviate from specs or when fakes exploit inconsistencies. For example, US driver’s licenses all use PDF417 barcodes, but encode fields differently by state.
The Scandit AI Engine works differently. Instead, it mirrors how counterfeit art is detected. Counterfeit art is detected not by looking at the subject itself, but by examining brush strokes, techniques, and materials to assess whether they align with an authentic work.
2 million
One of the largest US food delivery companies validates over 2 million IDs monthly using a Scandit-powered worker app
Similarly, the Scandit AI Engine doesn’t simply capture and decode individual data values. Instead, it analyzes structural characteristics — how fields are stored, how barcodes are generated and printed, and how visual elements are laid out — to accurately capture data and detect fakes.
ShelfView
Our shelf intelligence solution, ShelfView, is a specialist solution that analyzes images of store shelves captured using smart devices, fixed-position cameras, and robots. Similarly to how LLMs are trained, we ingest vast datasets to understand retail shelves comprehensively and accurately. It lets retailers see what is really on their shelves, not just what their inventory system says.
Scene parsing identifies trays, shelves, products, and shelf labels.
Products are identified down to the SKU level with image recognition.
OCR and barcode scanning are used on shelf labels to extract product and price information.
Together, they create a precise digital representation of the shelf (often called a realogram). Associates then receive prioritized alerts for missing or misplaced products, pricing, and promotional errors, so issues can be resolved before customers notice them.
What's next for the Scandit AI Engine?
The future of AI lies in domain-specific models tailored to unique industry needs. Ultimately, the Scandit AI Engine is moving towards a situation where you don’t scan barcodes, scan IDs, scan objects, or scan text. You just… scan.
Holistic scene analysis ingests multiple data sources and context and returns exactly the data and insights you need for your specific context — whether you’re a consumer, store associate, delivery driver, or operations manager — without you having to switch tools or explicitly instruct it in what you want.
In many ways, the Scandit AI Engine is like a self-driving car—except that instead of the context being the open road, the context is your business.
A self-driving car uses cameras and sensors to scan its surroundings, processes this data through advanced machine learning algorithms, and uses this information to brake, steer, and navigate roads safely. The Scandit AI Engine uses the cameras on smart devices to scan and interpret barcodes, text, and objects in real time, and provides immediate feedback and guidance based on what it detects — be it alerts about incorrect prices, low stock, or fake IDs.
In both cases, the AI does more than just "see". It understands and reacts to the environment, enhancing decision-making and efficiency. Ultimately, the Scandit AI Engine is the intelligence layer between business environment and user that connects the digital and physical worlds.
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