Unified Graph-RAG in a Single Postgres Engine
Our production benchmarks confirm that consolidating Hybrid Graph-RAG into a single PostgreSQL instance via pgvector and Apache AGE reduced cross-service network... Read more.
Production Metric: 14.2% Semantic Decay
After processing 2.8 million unstructured retail fragments, we observed that 14.2% of records passing traditional NOT NULL and regex constraints contained semantic... Read more.
Cost-Aware Agentic Workflows with PydanticAI
Introduction: The Hidden Price of Autonomy The Architecture of a Cost Guardrail Implementing Usage Limits with PydanticAI PydanticAI provides the primary library-level... Read more.
Specialized Judges: Scaling RAG Evaluation with Prometheus-2 and PydanticAI
Our production benchmarks utilize the Feedback Collection and Preference Collection datasets to establish the performance delta between generalist and specialized... Read more.
The Future of Automation is Local: Why German Firms are Trading the Cloud for On-Premise AI
In early 2026, the AI landscape reached a crossroads. On one side, we have the “reasoning giants”: GPT-5.4 and Gemini 3.1 Pro. These models offer unprecedented... Read more.
From Generalist to Specialist: Benchmarking the 25x Speedup of Fine-Tuned “Tiny Compilers”
We measured a 96.7% reduction in inference latency by migrating our EDI logic from Llama 4 (70B) to a fine-tuned Llama 3.2 (1B) “Tiny Compiler.” In high-volume... Read more.
The LLM-as-a-Compiler Pattern for High-Precision EDI Pipelines
As we look toward the next phase of industrial AI, the German Mittelstand is poised to move beyond “AI as a Chatbot” and toward the LLM-as-a-Compiler... Read more.
Part 4: The Human Interface — Enterprise RAG Deployment for 100+ Users
1. Introduction: From Prototype to Enterprise Building a Retrieval-Augmented Generation (RAG) system that works on a laptop is a common starting point, but it is... Read more.
Part 3: The Validation Layer — Reranking, Cross-Encoders, and Automated Evaluation
1. Introduction: Why Vector Search Alone Isn’t Enough In Part 2, we optimized our system for Recall—using expansion and routing to ensure the “needle”... Read more.
Part 2: The Multi-Step Retriever — Implementing Agentic Query Expansion
1. Introduction: The Death of the “Simple Search” In Part 1, we defined the blueprint for a production-grade Agentic RAG system. We moved away from passive retrieval... Read more.