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AI

Data and AI as the Key to Unlocking Financial Inclusion

Of the many things one might take for granted, access to banking and financial services may not immediately come to mind. But as a thought experiment, imagine trying to buy a home or a car without the ability to take out a loan. Try depending on cash payments from your employer, or relying on alternative banking solutions like short-term payday loans, check-cashing services, and prepaid debit cards.

7 Best AI Tools for Productivity

Artificial Intelligence (AI) is quickly becoming the go-to for businesses looking to up their game. Its advances have led to a suite of AI-powered tools that make running a company smoother—from automating redundant tasks to whipping up stunning visuals to redefining customer service. We’ll introduce you to the best AI tools for productivity and provide strategies to integrate AI into your daily operations.

How to Build a Smart GenAI Call Center App

Building a smart call center app based on generative AI is a promising solution for improving the customer experience and call center efficiency. But developing this app requires overcoming challenges like scalability, costs and audio quality. By building and orchestrating an ML pipeline with MLRun, which includes steps like transcription, masking PII and analysis, data science teams can use LLMs to analyze audio calls from their call centers. In this blog post, we explain how.

Application Modernization Solutions: Transform Your Enterprise with Cigniti's AI-led Approach

Revitalize your business with our expertise in Application Modernization. IDC predicts that 75% of legacy applications will demand modernization investment by 2024. The imperative to modernize your legacy applications has evolved from being an option to an absolute necessity. Unlocking the genuine value of digital requires a critical focus on modernizing legacy infrastructure. Despite this urgency, numerous companies hesitate or lack clarity when updating their current applications.

How to use generative AI for exploratory testing? (With examples)

Generative AI is bringing a new era of “convenience” with ChatGPT, from OpenAI, taking center stage in our daily lives. From aiding in solving complex problems to generating content, this large language model has become a helpful companion for various testing-related tasks. As generative AI is becoming increasingly present in our daily lives, we should understand how to use it and account for its limitations.

Six Key Predictions for Artificial Intelligence in the Enterprise

As we head into 2024, AI continues to evolve at breakneck speed. The adoption of AI in large organizations is no longer a matter of “if,” but “how fast.” Companies have realized that harnessing the power of AI is not only a competitive advantage but also a necessity for staying relevant in today’s dynamic market. In this blog post, we’ll look at AI within the enterprise and outline six key predictions for the coming year.

Set Analysis Redux: Do More with Qlik Episode 47

Set analysis in Qlik is a powerful data filtering and aggregation technique that allows users to create custom data subsets for analysis. It enables users to define complex criteria, known as set expressions, to isolate specific data points or dimensions within their Qlik applications. This feature is instrumental in performing advanced data manipulation, and it just got even easier with Qlik’s new AI enhancements.

AI in exploratory testing: benefits and challenges

Exploratory testing is a dynamic, flexible methodology emphasizing simultaneous learning, testing strategy, and execution. Unlike traditional scripted testing, exploratory testing enables testers to actively explore software applications using their intuition, creativity, and experience. By assuming the end-user role, testers interact with the software in real-time, identifying potential issues and uncovering usability problems that scripted tests might overlook.