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The retail industry is continuously evolving, and businesses need to adapt to these changes to stay competitive. One of the most significant technological advancements in recent years is the use of Artificial Intelligence (AI) in various retail processes. In this blog post, we will discuss the value of AI in retail, specifically focusing on the NLSQL software and its use case in a real-life retail example.

AI has numerous applications in the retail industry, from inventory management to customer service. One such use case is the implementation of AI-powered analytics and decision-making tools, such as NLSQL software. This software can help retail businesses make data-driven decisions, identify anomalies, and optimise their operations.

To illustrate the value of AI and NLSQL in retail, let's consider the story of a convenience store selling whole salmon for 8 GBP per kg. The store enjoyed healthy salmon sales, reaching £25k/month per store. However, a …

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Discover another AI use case example for Retail

In today’s fast-paced business environment, staying ahead of the curve is essential for success. One way to achieve this is by leveraging the power of AI-driven data analytics and anomaly detection. At NLSQL, we are committed to helping businesses harness the power of AI to make better-informed decisions, and we are excited to announce the launch of our new standalone product, AI Anomaly Detector.

Employees often face the daunting task of finding valuable insights hidden within vast amounts of data, akin to finding a needle in a haystack. This challenge can be overwhelming and time-consuming, especially when anomalies are not immediately obvious. To address this challenge head-on, we developed AI Anomaly Detector, a powerful tool that works alongside our existing AI Data Analytics offerings.

AI Anomaly Detector: Proactively Identifying Data Anomalies AI Anomaly Detector is designed to perform regular anomaly checks on your data. Upon detecting any anomaly, it notifies …

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NLSQL visited Ryadh for a personal negotiation and public presentation of NLSQL Healthcare BI software for Board Members of Al Borg Diagnostics Laboratories and Elaj Group in Saudi Arabia.

Digital transformation with innovative technology adoption is a key part of Saudi Vision 2030.
Saudi Arabia Government strategy leads to Middle East region leadership in technology and non-oil industry revenue share growth. As part of this program, Elaj Group reviewed and invited the best innovation technology company, which will create a high impact on the main industries in upcoming years.
An offline event with 4 of the most promising companies was held in Riyadh, Saudi Arabia.

Denis from NLSQL had a chance to participate in both P2P negotiations and offline public technology presentations. NLSQL adoption in the Middle East market will improve operational excellence and bring even more insights for all organisations levels in real-time. This will provide Saudi Arabia companies …

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Try 30 Days NLSQL trial for your database now

Intelligent Apps and AI-powered language models have become essential tools for large enterprises to streamline analytics and automate tasks. However, with the increasing reliance on these technologies, concerns about data security and the protection of sensitive information have also grown. In this blog post, we will discuss the main security concerns associated with NLSQL usage in large enterprises and how a secure software architecture on Azure, incorporating the NLSQL API service, can help overcome these concerns.
Main Concerns about Confidential and Sensitive Data Transfer are related to sensitive or confidential information transfer outside the corporate IT ecosystem for proper use based on your company use case.

To address these concerns, a secure software architecture can be implemented using Azure and the NLSQL API service. This approach offers several advantages:
1. No sensitive data transfer: With the NLSQL API service, there is no need to transfer sensitive or confidential data outside …

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In this blog post, we compare the data analytics capabilities of NLSQL and ChatGPT-4o using a dataset of import-export trade balance transactions from the US worldwide by product groups. We used an open dataset from the census, covering the years 2008-2023. Our test began by sending a full dataset as a CSV file to the latest ChatGPT-4o model and asking the question, "What are the top 5 products in export to China last year?"

ChatGPT-4o Response: The ChatGPT-4o response can be seen in the screenshot provided in this blog post. The top 5 products from highest export to lowest were:

1. Civilian aircrafts, engines, equipment, and parts
2. Semiconductors
3. Industrial Machines
4. Passenger cars
5. Crude Oil

NLSQL Response: NLSQL responded with a different set of top 5 products, which is actually correct and can be verified using the original CSV file filters. The top 5 products according to …

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NLSQL Open Demo containing import-export trade balance transactions worldwide