Edgify
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About
Edgify is an edge-based artificial intelligence platform specifically designed for retail environments. It allows businesses to deploy, update, and manage computer vision models directly on local hardware such as self-checkout kiosks, scales, and security cameras. Unlike cloud-dependent systems, this solution processes information locally on the device where the data is collected. This approach is intended to provide real-time decision-making capabilities, which are essential for tasks like identifying shrinkage and monitoring transactions in high-traffic retail settings. The platform includes features such as barcodeless product recognition and scan avoidance detection. Product recognition aims to simplify the self-checkout experience by identifying items without barcodes, while scan avoidance helps detect incidents like barcode-switching or missed scans. Additionally, the system can be used for back-of-house waste management by identifying discarded items to maintain accurate inventory records. The technology is designed to train itself using local data, allowing it to adapt to specific store environments without requiring significant manual intervention or infrastructure changes. This tool is primarily targeted at large-scale retailers and grocery chains looking to automate loss prevention and improve operational efficiency. It is suitable for roles such as IT directors, loss prevention specialists, and operations managers who require a low-latency, privacy-focused solution. Because data processing occurs on-device, it serves organizations that need to maintain strict data security or those operating in locations where cloud connectivity may be unreliable or expensive. What distinguishes this platform from other AI solutions is its decentralized architecture. By moving the intelligence to the edge, it reduces the bandwidth costs and latency issues associated with centralized cloud processing. The platform has been deployed across over 2,000 stores and 9,000 devices, processing a high volume of samples to maintain a reported precision rate of 98.58%. It offers a low-code integration method, making advanced computer vision accessible to traditional retail businesses.
Pros & Cons
Operates independently of cloud connectivity, ensuring 24/7 uptime even during internet outages.
Achieves a high precision rate of 98.58% across millions of recorded data samples.
Reduces infrastructure costs by running on existing in-store hardware like scales and scanners.
Enhances customer privacy by processing and training on data locally at the edge.
Scales seamlessly across thousands of devices without requiring centralized server upgrades.
Primary focus is currently limited to the retail sector, which may not suit other industries yet.
Requires initial integration with existing in-store hardware systems and checkout workflows.
Pricing information is not publicly listed and requires a custom demo request to obtain.
Specific hardware compatibility requirements for edge devices are not detailed on the public site.
Use Cases
Grocery store IT directors can deploy AI to self-service scales to automatically recognize produce, speeding up the checkout process.
Loss prevention managers can use the scan avoidance feature to flag suspicious transactions and barcode-switching in real-time.
Inventory managers can implement the waste management module to record discarded items in the back-of-house, improving stock accuracy.
Retail operations teams can scale AI intelligence across thousands of stores without investing in expensive centralized cloud infrastructure.
In-store security teams can utilize 24/7 monitoring to identify risky behaviors and improve overall safety for customers and staff.
Platform
Task
Features
• on-device model training
• edge-based ai processing
• distributed device scaling
• low-code integration
• inventory waste management
• real-time loss prevention
• scan avoidance detection
• automated product recognition
FAQs
How does Edgify handle data privacy?
Edgify uses a privacy-first approach by processing data and training AI models locally on edge devices. This ensures that sensitive information does not need to be transmitted to the cloud for processing.
Can Edgify work without an internet connection?
Yes, the system is designed to run and make real-time decisions directly on edge devices without depending on the cloud. This allows for constant performance even in environments with poor connectivity.
What kind of retail losses can the tool prevent?
The platform identifies scan avoidance behaviors, such as barcode-switching and non-scans at checkout. It also monitors back-of-house operations for waste management to ensure accurate inventory tracking.
Does it require new hardware?
No, Edgify is designed to integrate with the systems you already use, such as existing in-store scales and self-checkout kiosks. It runs directly on these devices to scale without massive infrastructure changes.
How accurate is the product recognition?
According to the platform's data, it has processed over 400 million samples and achieved a precision rate of 98.58%. This high level of accuracy helps eliminate false positives during the checkout process.
Pricing Plans
Enterprise
Unknown Price• Real-time edge processing
• Barcodeless product recognition
• Scan avoidance detection
• Waste management tracking
• Local model training
• Privacy-first architecture
• Cross-device scaling
• Existing hardware integration
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
No ratings available yet. Be the first to rate this tool!
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