Article archive
This is a comprehensive list of all our blog posts produced throughout the years. We are dedicated to create high quality content around data and AI. If you find our texts helpful, please let us know, it means the world to us.
Our content is mainly of technical nature and covers - among other things:
- Machine Learning
- Large Language Models
- Data Architecture
- Data Warehousing
- Text-to-SQL with a semantic layer: NVIDIA Auto Ontology tested
- Confluence to LLM Wiki: Our Self-Maintaining Company Wiki
- Copilot Studio: Use SharePoint Lists as a Knowledge Source
- Running GLM-4.7-Flash Locally with OpenCode
- Orchestrating Complex Tasks with Microsoft Agent Framework Workflows
- Microsoft Agent Framework: Build Enterprise AI Agents in Python
- BigQuery MCP Server: Google's Remote Server vs. MCP Toolbox, Tested
- RAGFlow 1.0 Tutorial: Setup, PDF Parsing and Real Test Results
- LLM Sampling with FastMCP: Using Client LLMs for Scalable AI Workflows in your MCP
- Automating MCP Server Creation from OpenAPI and FastAPI
- FastMCP Tutorial: Build an MCP Server in Python, Step by Step
- What Is Langfuse? Open-Source LLM Observability, Self-Hosted
- Integrating n8n with Open WebUI: Building advanced AI chatbots and workflows
- Building High-Quality AI Agent Systems: Best Practices
- Building Powerful AI Agents with smolagents: A Minimalist Approach
- DeepSeek R1 On-Prem Setup: Run Advanced AI Models on Your Hardware with SGLang
- Building Better AI Applications with LLM Tracing using Opik
- Building AI Agents with n8n: Postgres Tools, Memory and Human Approval
- Enhancing Self-Made Agent with Memory: Keeping Context for Better Conversations
- Advanced Self-Made Agent: Building a Smarter, Multi-Step AI Agent
- How to Build AI Agents Without Frameworks: A Step-by-Step Guide
- Azure AI Search RAG Tutorial: Build RAG on Azure with Python
- Azure OpenAI Content Filters: The Good, The Bad, and The Workarounds
- Crawl4AI Docker Tutorial: Crawl Websites for LLMs via REST API
- Late Chunking: Improving RAG Performance with Context-Aware Embeddings
- DSPy Tutorial: Build Better AI Systems with Automated Prompt Optimization
- What is LibreChat? Features, setup and Open WebUI comparison
- How to create LLM tools from any Python SDK using langchain-autotools
- How to crawl websites for LLMs - using Firecrawl
- Azure AI Studio: How to evaluate and upgrade your models, using the Prompt Flow SDK
- RouteLLM: Cut LLM Costs by Routing Prompts to the Right Model
- RAG, Embeddings and Vector Search with Google BigQuery
- Document Extraction with GPT-4o: Parse PDF, Word and Excel Files
- How to classify, describe and analyze images using GPT-4o vision
- Open WebUI: What It Is, How to Install It and What It Costs
- What is the VertexAI model garden - a practical example: Deploying Llama 3.1 and Claude 3.5 Sonnet
- Fine-tune OpenAI's GPT-4o mini LLM AI model
- Neo4j LLM Knowledge Graph Builder: How to Create Knowledge Graphs for RAG
- BigQuery Text-to-SQL: Query Your Database in Natural Language
- How to finetune LLMs
- LLM Document Extraction: Pull Structured Data from Complex PDFs
- Using AI directly from your database - with PostgreSQL and pgai
- KAN: Is this the end of feedforward networks?
- LLM Safety with Llama Guard 2
- How to use AI to create a PowerPoint presentation?
- Vertex AI Agent Builder: What It Is, with a Slack Search Example
- BitNet: LLM Quantization at its Extreme
- Chat with your Confluence: A Step-by-Step Guide using Airbyte, Langchain and PGVector
- Advanced RAG: Improving Retrieval-Augmented Generation with Hypothetical Document Embeddings (HyDE)
- GenAI: Technological Masterpiece or Ecological Disaster?
- 11 Proven Strategies to Reduce Large Language Model (LLM) Costs
- How to boost your database performance with OpenAIs new v3 embeddings
- Introduction to Retrieval Augmented Generators (RAG): Enhancing Virtual Assistants with Domain-Specific Knowledge
- Advanced RAG: Increase RAG Quality with ColBERT Reranker and llamaindex
- Advanced RAG: Recursive Retrieval with llamaindex
- vLLM with HTTPS: Self-Host an LLM Behind a Caddy Reverse Proxy
- RAG Evaluation with Ragas: How to Measure RAG Pipeline Quality
- Integrating enterprise knowledge with LLMs