Generative AI

This is Part 3 of a three-part series (links at the bottom). In Part Two, we moved from concept to execution by building the foundation of a Retrieval‑Augmented Generation (RAG) system. We set up a Postgres database with pgvector, defined a schema, wrote a script to embed and chunk text, and validated vector search with cosine similarity. In […]

In 2025, MedTech leaders are redefining innovation by architecting intelligent ecosystems that span the entire product lifecycle. As AI in medical device development becomes a strategic imperative, forward-thinking organizations are aligning digital investments with business-critical outcomes: Faster time to market Stronger regulatory readiness Scalable clinical impact This blog explores how AI-powered transformation is reshaping every […]

Nowadays, the topic of artificial intelligence is everywhere. Let’s face it!. Who, even out of curiosity, has asked a question to generate an image, refine ideas, or seek answers in one of the many artificial intelligence applications on the market?   Now, parallel to this conversation, there are numerous myths about the arrival and use […]

The world of digital experiences is evolving more quickly than ever before, and let’s be honest, artificial intelligence (AI) is more than just a trendy term these days. It’s becoming a business necessity. AI is no longer a “nice to have” for companies that use Sitecore as their Digital Experience Platform (DXP). It’s turning into […]

Managing cloud infrastructure effectively requires consistent and meaningful tagging of resources. Manual tagging is prone to errors and difficult to scale. In this blog, I’ll show you how to use Amazon SageMaker and Python to automatically apply intelligent tags to your EC2 instances using either rule-based logic or AI-powered enhancements. What You Will Learn How […]

As we all know, in the world of reels, Photos, and videos, Everyone is creating content and uploading to public-facing applications, such as social media. There is no control over the type of images users upload to the website. Here, we will discuss how to restrict inappropriate photos. The AWS Rekognition Service can help you […]

Abstract This article explores how artificial intelligence can transform technical evaluation processes in talent acquisition, particularly in the software development field. Through the Dessert & Learn session, two complementary approaches are presented: a basic one using prompts in Copilot for automated code analysis, and a more advanced one using intelligent agents built with n8n and the RAG […]

Generative AI is moving from eye‑catching demos to real operational impact. Yet the leap from a clever model call to a production‑grade, human‑aware workflow is non‑trivial. This post distills recent field research into a pragmatic blueprint for building GenAI workflows that automate business processes without sacrificing oversight, auditability, or tech‑stack flexibility. Why “Workflow Thinking” Matters GenAI […]

Implementing predictive analytical insights has become ever so essential for organizations to operate efficiently and remain relevant. What is important while doing this though is to be agile and adaptable. This is much so because what holds valid for a period can easily become obsolete with time. And what is characteristic of a specific group […]

The rules of digital engagement and SEO are changing fast. As Generative AI platforms and large language models (LLMs) become the go-to tools for information and decision-making, traditional SEO strategies are being upended. Search engines are no longer the only gateway to brand discovery. Increasingly, consumers are turning to AI-powered assistants to ask questions, compare […]

This is Part 2 of a three-part series (links at the bottom). The GitHub repo can be checked out here. Postgres RAG Stack brings together Postgres, pgVector, and TypeScript to power fast, semantic search. In Part One, we covered the theory behind semantic search: how embeddings convert meaning into vectors, how vector databases and indexes enable […]

This is Part 1 of a three-part series (links at the bottom). Traditional search engines and databases match based on keywords. These systems are fine when you’re looking for an exact or partial string match but fail when the goal is to find content that’s conceptually similar, not just textually identical. Vector search bridges this […]