AI Insights Blog

How to Build a Multimodal AI Full-Stack Application – A Proper Guide

In the era of advanced Artificial Intelligence, where models can not only understand text but also analyze images, audio, and videos, multimodal AI applications have become the next big leap in modern software development.

Why and where to Use LoRA / QLoRA and RAG?

Modern Large Language Models (LLMs) are increasingly central to AI systems — powering everything from enterprise chatbots to multimodal assistants and autonomous agents. However, running, fine-tuning, and maintaining these massive models can be resource-intensive and expensive, especially for Europe

How to Develop an MCP Server From Scratch

The Model Context Protocol (MCP) is fast becoming a foundational standard in the AI / agent ecosystem. It defines a uniform way for large language models (LLMs) or AI agents to access external tools, resources, and prompts via a well-defined protocol. MCP servers act as bridges between agents

What Is MCP Server and How It Works

In the landscape of AI agents and tool-enabled language models, MCP (Model Context Protocol) is emerging as a foundational standard. MCP Servers act as bridges that allow large language models (LLMs) or agent clients to call tools, access resources, and interact with external systems in a structured

Optimizing LLMs: LoRA, QLoRA, SFT, PEFT, and OPD Explained (2025 Edition)

Europe’s AI ecosystem is evolving rapidly. From the AI research hubs in Brussels and Ghent to pan-European innovation centers in Germany and France, optimizing Large Language Models (LLMs) is at the core of building cost-efficient, GDPR-compliant, and high-performance AI systems

How to Build AI Agents for Free

You can build powerful AI agents for free using open-source libraries, community platforms, and free-tier cloud services. Tools like LangGraph, LangChain, Hugging Face, and n8n make it possible to prototype and deploy agents without spending a single dollar.