In previous posts, we defined our architecture and selected our technology stack. Now is the time to build the “Brain” of the operation. This post covers the deployment of the core AI services on our GPU-enabled virtual machine. We will configure two main components: 1. Initial Server Setup First, we launch our VM based on … Read more
Processing purchase orders is often treated as a back-office burden, but it is the pulse of the supply chain. While traditional OCR solutions rely on rigid templates and manual data entry, modern Generative AI allows us to build a system that is flexible, autonomous, and—most importantly—self-healing. This post outlines the architecture for our AI-Assisted Purchase … Read more
This document describes the process for creating a reusable, deterministic Ubuntu 22.04 QCOW2 base image optimized for GPU-accelerated AI workloads. The resulting image is intended to be cloned and customized by automation/orchestration tooling. 1. Base OS Installation Why avoid the HWE kernel in the base image 2. System Update 3. SSH Configuration (Remote Root Access) … Read more
1. Why PCI Pass-through? The primary goal is to use the Tesla L4/P4 at 100% capacity within a Virtual Machine for high-speed document parsing/inference without the complexity of vGPU. 2. Host Configuration We isolate the GPU hardware, so the Guest VM can claim it exclusively. Identify the Hardware Kernel & GRUB Setup We use the … Read more
PostgreSQL 16 is the ideal choice for this environment because it delivers major improvements in performance, parallel query execution, index efficiency, and write-ahead logging throughput—all of which directly benefit Git metadata workloads and AI/ML-related query patterns. PG16 also includes enhanced vacuum performance, faster sorting, and better handling of high-concurrency workloads, making it extremely well-suited for … Read more