Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Reduce the risks of overstock and stock-outs to enhance customer satisfaction while simultaneously decreasing costs associated with excess inventory.
Easily obtain visibility throughout your supply chain without the need for replatforming, hefty upfront licensing fees, or binding commitments.
Leverage machine learning (ML) to make better-informed decisions in your supply chain by utilizing actionable insights powered by advanced analytics.
Gain an understanding of the overall condition of your supply chain network, complemented by ML-driven insights regarding potential inventory issues, including both excessive stock and stock shortages.
Rapidly deploy AWS Supply Chain utilizing ML models that can comprehend, extract, and convert diverse data sources into a cohesive data lake.
Examine suggested actions that can help alleviate risks, and utilize integrated contextual collaboration features to expedite the agreement and implementation of decisions.
Improve the accuracy of demand forecasts to minimize stock shortages, while also enhancing demand planning precision with ML models that progressively refine their predictions over time, leading to better inventory management.
This comprehensive approach not only streamlines operations but also fosters a more responsive and resilient supply chain.
Description
The BoxLens platform offers an integrated solution that combines hardware, software, analytics, and actionable insights to provide comprehensive visibility into essential supply chain metrics. Utilizing a blend of artificial intelligence and established business rules, it suggests various actions for users to take. The system automatically updates the next steps based on the actions executed, ensuring that all activities are documented for future analysis and enhancement of algorithms. Users can access a consolidated dashboard that highlights key performance indicators (KPIs) related to the supply chain. Additionally, it features real-time telemetry that syncs with the client's ERP data, along with alerts for any deviations or undesirable occurrences. Notifications can be sent through multiple channels, including dashboards, SMS, email, voice calls, or WhatsApp. The platform performs diagnostic evaluations of supply chain metrics in relation to relevant ERP data and operational conditions. Furthermore, it predicts possible supply chain disruptions in real-time, employing machine learning models that draw from historical data to forecast future trends. This capability allows for proactive planning at the source and timely interventions during operations. Moreover, it provides standardized templates that facilitate operations, quality assurance, and management reporting, thereby enhancing overall efficiency. In essence, BoxLens not only streamlines supply chain processes but also equips businesses with the tools needed to adapt and respond to dynamic market conditions.
API Access
Has API
API Access
Has API
Integrations
Amazon Q
Amazon Q Business
Amazon Web Services (AWS)
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/aws-supply-chain/
Vendor Details
Company Name
Tagbox Solutions
Founded
2016
Country
Singapore
Website
www.tagbox.co/boxlenstm/
Product Features
Supply Chain Management
Demand Planning
Electronic Data Interchange
Import / Export Management
Inventory Management
Order Fulfillment
Order Management
Sales & Operations Planning
Shipping Management
Supplier Management
Transportation Management
Warehouse Management
Product Features
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization