We build industrial AI around the information engineers actually need: machine evidence, plant context, secure access and local intelligence.
PHOENIX brings together machine evidence, plant-system context, domain expertise and secure local AI so industrial teams can move from isolated monitoring to decisions about what the plant can reliably produce. Our focus is not simply collecting more data. It is connecting asset health to maintenance execution, production commitments, capacity and the business consequence of lost availability.
High-resolution vibration and asset-health sensing provide direct evidence of what equipment is actually doing.
PHOENIX CIP connects approved maintenance, production, controls, historian, engineering and enterprise information.
LabSource runs local LLMs, RAG, engineering agents, analytics and coding inside the customer-controlled environment.
A vibration spectrum alone does not know the production schedule. A work order alone does not know what the machine is doing. A generic LLM does not know the plant. PHOENIX is designed to combine these sources safely so AI can reason against the real operating environment.
Critical Infrastructure Protection, Vault-managed credentials and governed tools are foundational — not optional add-ons.
The goal is useful engineering output: diagnostics, evidence, calculations, reports, workflows and decisions.
On-prem infrastructure keeps models, plant knowledge, RAG indexes and sensitive workflows under customer control.
Engineered and deployed for American industrial operations.
336-763-2882
sales@phoenix-unifiedsystems.com
PHOENIX is built around the idea that machine condition only becomes business intelligence when it is understood against what the plant is trying to produce, the maintenance work required, the logistics needed to execute that work, the domain knowledge of local experts and the wider operating context.
Start with the production requirement, product mix, schedule and capacity target.
Use machine condition and reliability evidence to identify risks to that production requirement.
Connect PM planning, work orders, history, parts, labor and execution constraints to the capacity decision.
