Umbra-Noesis · Hardware Layer
PCe Systems is the hardware layer of Umbra-Noesis — documented configurations where storage, GPU, memory, and OS are arranged to treat local AI inference as a first-class workload, not an afterthought.
What it is
A standard PC is optimized for general computing — browsers, office apps, occasional gaming. Running local AI inference on top of that is like running a lathe in a kitchen: technically possible, but nothing is built for it. PCe Systems defines how to arrange hardware so local inference, persistent memory, and AI-native workflows are what the machine is sized and tuned for.
Each PCe profile is a documented, repeatable build specification — not a proprietary locked device. The blueprints define storage layouts, GPU configurations, memory allocation, and OS tuning so the same architecture can be reproduced across workstations, laptops, field rigs, and future licensed kits.
Low-latency local inference as a first-class, always-available workload
Resilient storage layouts for long-term cognitive archives
Predictable, consistent performance across deployment environments
Documented builds — reproducible, shippable, licensable
Recommended Specifications
Baseline for EVE OS + EVAA local inference
CPU
8-core modern processor — AMD Ryzen 7 / Intel Core i7 or equivalent
RAM
32 GB minimum · 64 GB+ for multi-model or concurrent workloads
GPU
Dedicated GPU — 8 GB VRAM minimum · 16 GB+ recommended for larger models
Storage
NVMe primary — 1 TB+ · Secondary archive storage recommended for memory persistence
Platform
x86_64 Linux · EVE OS reference build · Ubuntu 22.04 LTS / Debian 12 base
Connectivity
Wired ethernet preferred · WiFi 6 minimum for mobile builds · offline-capable by design
Deployment Tiers
Lab · Research
High-performance builds
High-end desktop or workstation configurations for deep model testing, memory architecture development, and long-horizon experimentation. Full hardware headroom — sized for the most demanding local inference workloads.
Field · Mobile
Mobile & remote builds
Laptop and compact desktop configurations for working from boats, trucks, remote job sites, and locations where cloud connectivity is unreliable or nonexistent. Local-first by necessity — fully operational offline.
PCe Kits
Licensed builds — roadmap
Future turnkey hardware kits and licensed build specifications derived from the PCe reference architecture. Reproducible configurations that can be shipped, deployed, or licensed to operators building on the Umbra-Noesis stack.
Roadmap
PCe_FE Reference Build
Internal reference build — the baseline Personal Cognitive Environment used for all EVE OS and EVAA development and validation.
Internal — ActiveBlueprints & Profiles
Documented configuration specs for lab, field, and rack deployments. Reproducible build guides covering hardware selection, OS tuning, and inference setup.
In DevelopmentPCe Product Line
Future kits, reference builds, and licensed designs for operators building on the Umbra-Noesis architecture. Turnkey hardware matched to EVE OS certification.
RoadmapStack Integration
EVE OS
The operating system tuned to the PCe profile — storage, GPU, and memory allocated for cognition as infrastructure, not an application.
EVAA Cognition
The resident AI engine — runs against PCe hardware directly, with the full GPU, memory, and storage budget available for local inference.
Umbra Link
Each PCe node carries a Node ID through Umbra Link — enabling identity-aware routing and optional mesh connectivity between units.
The principle
Your hardware.
Built for the work.
Most AI systems are built in the cloud and squeezed onto your device. PCe Systems inverts that — the hardware is sized and tuned for local inference first, and everything else fits around it.