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Radometech

AI in "Retail"

Artificial Intelligence in Retail Industry is being applied in new possible ways across the entire life cycle of the industry; from product to service - from production to customer service interactions.

Business Challenges

 

The Retail Industry is constantly changing and there are always new challenges faced by the players in this competitive industry. Customer preferences will always change, sometimes even faster than one can imagine. Apart from seasons and trends, several other factors such as economic circumstances, advertisements, and competition in the retail industry have huge impact on consumer demand. Retail has complex operations and managing its internal communication is not an easy task. Inefficient communication between divisions can disrupt the business processes.

 

 

 

How can AI help?

For decades, traditional analytics have worked perfectly fine for the data-driven retail industry. However, Artificial Intelligence (AI) and Machine Learning (ML) has opened new doors for data driven approach which leads to deeper business insights. Combining rich customer and casual data with the power of ML is enabling retail companies to optimize supply chains, pricing and trade promotions with highest level of accuracy. By implementing AI, retailers are able to handle the number of models deployed in each store resulting in a reduction in supply chain costs while helping to deliver an optimal experience for customers.

 

 

 

Use cases

Demand Prediction: A highly accurate demand forecast is the only way retailers can predict which goods are needed for each store location and channel on any given day—which in turn is the only way to ensure high availability for customers while maintaining minimal stock risk. Machine Learning makes it possible to consider their impact at a detailed level, by individual store or fulfillment channel.

 

Customer Recommendation: Recommendations typically speed up searches and make it easier for users to access content they’re interested in, and surprise them with offers they would have never searched for. Recommendation System, which uses ML algorithm, has seemed to be an integral part of any retailers, e-commerce sellers, and merchandisers not only due to its simplicity but also due to its ability to unlock business values that is usually hidden within massive chunks of transaction data.

 

Price Predictions: Sometimes retailers face challenges when it comes to making a decision on price changes. For most of them, seasonal trends and tendencies are given priority in making those decisions. Using predictive analytics here can help identify the best time to start decreasing or pushing prices in the other direction. AI can monitor features such as a pricing map of the market and compare demands to find out what the prices should be like.

 

Supply Chain Management & Logistics: AI helps retailers understand exactly how their supply chain is operating, make improvements throughout and eliminate waste and overhead costs. AI has numerous applications across the retail supply chain including but not limited to autonomy, modeling, forecasting and optimizations which can reduce supply chain delays, optimize demand and foster capacity planning and significantly reduce costs.

 

Customer Service and Compaints Resolution: The use of artificial intelligence in customer service is not only revolutionizing the customer support function but also improving customer loyalty and its brand reputation. Thanks to the availability of tools like AI-powered customer service bots, companies in the B2C industry segment are increasingly entering an age of automated customer service that is boosting the brand experience for customers. 

 

 

 

Why choose us?

It’s no secret that adopting AI technology is key for retailers to succeed. Still, some organizations aren't yet investing. Why? Uncertainty about how to begin, a perceived skills gap, and general conservativeness in the use of technology are the primary barriers.

 

We at RadomeTech believe AI is crucial for every business entity. Thus we have a developed a tool which lets the user have the power of Artificial Intelligence and Machine Learning !

 

Get Started

Copyright Radome Techologies and Services Pvt Ltd 2020

Use Cases

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TELECOMMUNICATION

According to sources, 19% of Telecom companies are adopting AI by 2023 and 58% of Service providers see AI crucial for Network Management.

ANALYSE PERFORMANCE DATA
AUTOMATION OF NETWORK MANAGEMENT
SPOT ANOMALIES IN NETWORK TRAFFIC
IMPROVE NETWORK CAPACITY PLANNING

OIL & GAS

Oil  & gas is one of the most lucrative industries, it is also one of the most dangerous. According to experts, 50% of Oil & gas industries say they have already begun AI to help solve challenges at their organisations.

OPTIMIZE PRODUCTION AND MAINTENANCE COST
ENHANCE QUALITY ASSURANCE
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DEFECT DETECTION
ABILITY TO MAKE BETTER DECISIONS

REAL ESTATE

Experts believe that 16% of the Real Estate companies are adopting AI in their businesses by 2023 and are expected to see a marginal profit of around 50%

IMAGE RECOGNITION & ANALYSIS
ANALYSE PATTERNS
RISK FORECASTING
OPTIMIZE SCHEDULES
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What we do.

We craft unisex leather bags and accessories for those, who appreciate premium handmade products, durable quality and urbane style.

AI for Healthcare

In the complex world of Healthcare, AI tools can support healthcare providers to provide faster service, diagonse issues and analyse data to identify trends or genetic information that would predispose someone to a particular disease.

AI ASSISTED MEDICAL DIAGNOSIS
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MEDICAL RISK PREDECTION
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AUTOMATED WORKFLOW ASSISTANCE
MEDICAL IMAGE ANALYSIS
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Use Case

Aircrafts require a vast spectrum of parts to operate ranging from high cost repairable parts to low cost fast moving consumables Apart from the fact that certain parts are highly expensive, failure to have the necessary part readily available can also translate into expensive AOG (aircraft on ground) incidents.

Manufacturing

Experts believe that about 40% revenue boot will be there upon adopting to AI in Manufacturing. Around 50% of the manufacturers are planning to Invest on AI for their processes.

DETECTS FAULTS
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REDUCE UNPLANNED DOWNTIME
PREDICTIVE MAINTENANCE
Quality control

Retail

According to sources, 85% of customer interaction in retail will be managed by AI by 2023 and a revenue growth of 10% on adopting AI in the business process.

DEMAND FORECASTING
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SUPPLIER PERFORMANCE PREDECTION
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OPTIMIZE INVENTORY
ROUTE OPTIMIZATION