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support

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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

Syrup provides AI-driven insights for planning and inventory allocation specifically tailored to the fashion and apparel industry. By adhering to the principle of minimizing waste, Syrup’s intelligent recommendation system enables brands to maximize their full-price sales while effectively reducing surplus stock. The impact of your historical sales data is significantly enhanced through the incorporation of real-time transactions and current events. Any relevant data source that contributes valuable insights can be seamlessly integrated into Syrup’s platform. Let the complexities of data analysis be handled by advanced algorithms, allowing our sophisticated machine learning models to predict seasonal trends with increasing accuracy. Just like a skilled tailor understands the uniqueness of each garment, Syrup’s algorithms are customized to meet the distinct requirements of each brand, offering flexibility to adapt as circumstances change. Speed up the decision-making process with Syrup’s instant recommendations for inventory allocation, replenishment, rebalancing, and reorder strategies. Additionally, Syrup can help recover lost revenue by enhancing the sell-through rate of full-priced items. Make informed and rapid inventory planning choices with the assistance of automated recommendations, ensuring your brand remains competitive and responsive in a fast-paced market. This innovative approach not only streamlines operations but also fosters sustainable practices within the fashion industry.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon Q Yes 
Amazon Q Business Yes 
Amazon Web Services (AWS) Yes 
Microsoft Dynamics 365 No 
NetSuite No 
NewStore No 
SAP Cloud Platform No 
Salesforce No 
Shopify No 
Snowflake No 

Integrations

Amazon Q No 
Amazon Q Business No 
Amazon Web Services (AWS) No 
Microsoft Dynamics 365 Yes 
NetSuite Yes 
NewStore Yes 
SAP Cloud Platform Yes 
Salesforce Yes 
Shopify Yes 
Snowflake Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/aws-supply-chain/

Vendor Details

Company Name

Syrup

Website

syrup.tech/

Product Features

Supply Chain Management

Demand Planning No 
Electronic Data Interchange No 
Import / Export Management No 
Inventory Management No 
Order Fulfillment No 
Order Management No 
Sales & Operations Planning No 
Shipping Management No 
Supplier Management No 
Transportation Management No 
Warehouse Management No 

Product Features

Inventory Management

Alerts/Notifications No 
Barcoding / RFID No 
Forecasting No 
Inventory Optimization No 
Kitting No 
Manufacturing Inventory Management No 
Mobile Access No 
Multi-Channel Management No 
Product Identification No 
Reorder Management No 
Reporting/Analytics No 
Retail Inventory Management No 
Supplier Management No 
Warehouse Management No 

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