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

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.

Hugging Face Image-to-Video Model Integration in FastAPI and Django

rise of generative AI has already transformed how we create text, images, and even music. But in 2025, one of the fastest-growing innovations is AI-powered video generation. Instead of relying on expensive camera crews and long editing cycles, businesses and creators are now turning still images.

How Hugging Face Powers the Future of AI Agents

AI agents are rapidly becoming central to the next wave of innovation—autonomous assistants, reasoning bots, multi‑step workflows, agents that interact with tools/APIs, perform tasks inside UIs, coordinate with humans, and more.