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Description

Conventional weather forecasting often fails to accurately predict atmospheric events on the ground, leaving a significant gap in reliable information. Helios weather analytics effectively address this issue by providing rapid and precise local ground weather insights, allowing organizations that depend on location-specific data to make informed real-time decisions for their operations. Developed by L3Harris, the Helios environmental intelligence platform offers crucial details about hyperlocal weather conditions that are frequently overlooked by traditional weather services. Utilizing advanced Artificial Intelligence (AI), Helios identifies weather occurrences and their impacts on essential ground infrastructures through an extensive network of terrestrial cameras. This timely and specific information is vital for organizations whose decisions are influenced by changing weather conditions. The platform is built on a scalable cloud AI processing system that facilitates effective imagery management, while also offering an open API and web application for seamless content delivery. By ensuring access to hyperlocal weather data, Helios empowers users to better protect their interests and respond swiftly to environmental changes.

Description

Planalytics utilizes sophisticated statistical techniques along with artificial intelligence (AI) and machine learning (ML) to analyze extensive sales data and leverage years of unparalleled expertise in retail demand forecasting, thereby enhancing accuracy. An important consideration for any retail organization is the fluctuating demand influenced by weather conditions. To address this, Planalytics offers tailored, localized demand modifications that accurately assess the consumer's interaction with weather patterns. Their analytics, which have been validated in real-world scenarios, are relied upon by retail companies operating across more than 75,000 locations. Retailers have the option to seamlessly incorporate Planalytics into their existing software and AI/ML frameworks as a quick-to-implement value-enhancing layer. This integration represents a swift method to unlock untapped potential from current demand forecasting systems, enabling businesses to reap the financial benefits associated with optimized inventory management, promotional strategies, advertising efforts, markdowns, and additional areas. By harnessing these advanced analytics, retailers can significantly improve their operational efficiency and responsiveness.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

BleuPage Yes 
Island Pacific SmartSuite No 
Logility No 
Mi9 Retail No 

Integrations

BleuPage No 
Island Pacific SmartSuite Yes 
Logility Yes 
Mi9 Retail 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 Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

L3Harris

Founded

2020

Country

United States

Website

www.l3harris.com/all-capabilities/helios

Vendor Details

Company Name

Planalytics

Founded

1996

Country

United States

Website

www.planalytics.com/planalytics-predictive-demand-analytics/

Product Features

Product Features

Predictive Analytics

AI / Machine Learning No 
Benchmarking No 
Data Blending No 
Data Mining No 
Demand Forecasting No 
For Education No 
For Healthcare No 
Modeling & Simulation No 
Sentiment Analysis No 

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