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Articles by Valentyn Kropov
Stop Optimizing The Wrong Layer Of Your AI Bill
Valentyn Kropov, СTO at N-iX, a global technology partner for Pragmatic AI Software Engineering. My team has been working with a global technology leader in industrial manufacturing to build a shared AI gateway for tens of thousands of engineers using multiple approved AI providers. As adoption scaled, so did a less visible problem—small costs multiply fast once thousands of people are doing it at once. It's a bit like every employee in a company using a taxi instead of the bus.
Why Pure Agentic AI Fails In Enterprise Settings And What Works Instead
Valentyn Kropov, СTO at N-iX, a global technology partner for Pragmatic AI Software Engineering. I keep seeing the same pattern in agentic AI conversations with enterprise teams. They start with “pick a model, wrap it in an agentic framework and point it at our data.” They treat model selection as a strategic decision and the integration work as somebody else's problem.
Council Post: Four Steps To Improving Transaction Speed In The Payment Industry
Share to Facebook Share to Twitter Share to Linkedin Valentyn Kropov, Chief Technology Officer at N-iX—a trusted software development partner for global businesses and Fortune 500 leaders. getty The banking industry is currently experiencing a profound transformation fueled by technological advancements and the rapid growth of digital transactions.
Council Post: Cut The Unnecessary Tech Spending With These Four Questions
Valentyn Kropov, Chief Technology Officer at N-iX—a trusted software development partner for global businesses and Fortune 500 leaders. Technology plays a key role in helping businesses make a profit; however, often, companies are uncertain about how to optimize their IT resources and cut the unnecessary spendings that take a chunk of their budget.
Council Post: How Technology Leaders Can Prepare And Succeed During An Economic Recession
Valentyn Kropov, Chief Technology Officer at N-iX—a trusted software development partner for global businesses and Fortune 500 leaders. The world is on the brink of economic recession. Sixty-eight percent of the prominent economists surveyed by the Financial Times have agreed that we will see a significant economic decline in 2023 with potentially the highest levels of inflation in the last 40 years. So, what should technology leaders do to prepare their businesses for the recession?
Five Essential Inventory Management Techniques For The Warehouse (And One Practice To Stop Immediately)
Inventory management starts — and only starts — with a warehouse management system (WMS). As most warehouses have used this technology for years, it stands to reason this technology should be plug-and-play, requiring little thought after the initial investment and set up. Theoretically. In practice, most out-of-box WMSs are not capable of managing the volume and complexity of workloads required in today’s retail environment.
Retail Modernization: Unlocking Actionable Insights
Disparate systems and siloed data make it nearly impossible for retailers to effectively run analytics that provide insight into the business and its customers. Modernizing legacy infrastructures and moving data to a centralized location within a cloud platform lets retailers reduce IT spend (from costly maintenance), leverage advanced technologies to transform structured data into actionable insights, and turbocharge productivity.
Four Ways to Assess Your Retail Loyalty Program
Loyalty programs are one of the best ways for retailers to engage and retain customers. This is not news —in fact, there are 3.8 billion loyalty program memberships in the US alone. However, not all loyalty programs are equal. US households actively participate in an average of nine loyalty programs—despite subscribing to more than 20.
R vs. Python: The Data Science Wars - Dataconomy
Choosing the right language for data analysis can be almost as complicated as actually learning the language. For many reasons, R and Python are two of the most popular: R is often praised for its great features for data visualization, as it was developed with statisticians in mind; plenty of programmers love multi-purpose Python for its so-simple-a-child-could-do-it syntax. The fact is, your time is limited.
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