Category: Blog

When organizations decide to implement AI solutions, they face an important and sometimes confusing choice: should they build their own system, buy an existing one, or go for a mix of both?

The saying “Data is the New Oil” has been around for a while, and just as oil powered the industrial age, data drives the modern digital world.

Imagine exploring through the vast sections of a large global e-commerce site with millions of products. The magic behind those instant, spot-on product recommendations? Vector databases.

Imagine exploring through the vast sections of a large global e-commerce site with millions of products. The magic behind those instant, spot-on product recommendations? Vector databases.

Efficiently retrieving relevant information from vast datasets is crucial and has multiple industry use cases. Vector embeddings are revolutionizing how we search and interact with data.

We have successfully used document chunking to enhance our clients’ data processing capabilities across numerous use cases, delivering exceptional results.

We have successfully used document chunking to enhance our clients’ data processing capabilities across numerous use cases, delivering exceptional results.

Not all large language models (LLMs) are made equal. It is important to select the one that meets your business needs.

These days, everyone wants to implement Generative AI (Gen AI) but an approach that works well for one business does not work for other businesses. A lot of Gen AI success depends on the data maturity level of your organization.

The recent Databricks Data+AI Summit 2024 buzzed with exciting announcements, and the one that grabbed our attention at Konverge AI is LakeFlow!

Today, almost all businesses want to leverage the power of Generative AI (Gen AI) using Large Language Models (LLMs).

Manufacturing leaders realize that the potential of AI in their industry is significant for making production and supply chain smoother, faster, and far more efficient.

Recently, I tried to utilize an airline’s AI-powered chat assistant to book a flight ticket, primarily enticed by the 10% discount it offered.

In the AI era, mid-market enterprises and mega-corporations stand out as prime candidates to harness AI’s potential.

Since AI took the spotlight, enterprises worldwide have been exploring its potential to redefine business efficiency and value, aiming to gain a competitive edge.

Don’t Let an AI Project Fail you. This blog gives you essential tips for a successful AI journey

Don’t Let an AI Project Fail you. This blog gives you essential tips for a successful AI journey

Artificial intelligence (AI) has reinvented the entire retail industry with its inclusion across retail operations.

Almost all the prospects I have a conversation with have a few AI use-cases thought out. In my previous blog, I focused on how to find the correct use case to begin your AI journey with.

Just recently we celebrated the 4th anniversary of Konverge AI. As we reflected on our 50+ AI implementations, we thought about creating a blog series based on our learnings, mistakes and experiments.

Anyone who is even remotely connected with AI or has completed even minimal research will be aware of the following three alarming stats