Physical AI Assurance

Software can optimize. EIOS decides what it may physically cause.

EIOS converts fragmented evidence, physical dependencies and current state into a site-specific operating boundary for autonomous control.

See the system Technical thesis

The missing layer

One physical truth layer. One operating boundary.

Optimizers choose actions. Policy runtimes enforce rules. EIOS determines what those rules must be for the actual physical environment.

Exploded physical truth layer showing building systems and dependencies

Exploded physical truth layerDeck asset · product reveal

EvidenceOne-lines, points, sequences, control scope

ModelVerified dependencies, confidence, unknowns

PreflightAction under normal and degraded states

PolicyAllow, limit, escalate or deny

State-dependent authority

Same action. Different state. Different permission.

The agent is not dumb. It is optimizing against an objective that does not contain the whole environment.

Tap to inspectOperational permission is state-dependent

Typed physical authority graph

The technical object is a graph, not a dashboard.

A proposed action is evaluated through resources, physical states, operating policies, downstream consequences and enforcement targets, with source evidence attached to every important edge.

Tap to inspect full authority graphTyped nodes · state transition · enforcement

EIOS should know what it knows, what it inferred, what matters if an assumption is wrong, and the cheapest next evidence needed to resolve dangerous uncertainty.

What is actually hard

Four engines, one boundary.

01 · Evidence compiler

Convert messy one-lines, point lists, sequences and configs into typed physical facts.

02 · Provenance and uncertainty

Separate verified facts from inference and expose what remains unknown.

03 · Counterfactual engine

Same proposed action, different physical state, different permission.

04 · Policy compiler

Translate the operating envelope into machine-readable constraints for existing enforcement systems.

Moat candidate: the correction corpus — how real environments differ from their evidence, and which differences matter for autonomous authority.

Product 01 · Preflight

Before autonomous control goes live, derive the boundary.

Read-only evidence. No production control. Preflight returns what automation may do, what depends on unverified assumptions, what requires escalation and what should never be autonomous.

PREFLIGHT→VERIFY→MONITOR→AUTHORITY

Preflight is the entry product. The long-term asset is the independent physical truth and authority layer across systems and vendors.

Falsification

One bounded system. Try to break the thesis.

If EIOS cannot derive a material operating constraint that the current stack does not already encode, the thesis fails.

Design partner Technical discussion

EIOS: The Energy Intelligence Operating System for Buildings

VoltOS Capacity Guard for electrified buildings

Code aligned capacity evidence and constraint enforcement, so electrification can proceed with fewer unnecessary service upgrades, subject to engineering and AHJ requirements.

Decision grade evidence pack

Continuous constraint enforcement

Living compliance record

Request Info

The Problem

Buildings are stuck at the CapEx cliff, unable to electrify without costly upgrades.

Electrification projects stall when engineers and utilities size to conservative assumptions and require service upgrades. Typical upgrade paths can cost $200K to $1M plus and take 12 to 24 months. VoltOS provides a code aligned measurement and evidence pathway and, where deployed, an enforcement layer that keeps authorized flexible loads inside an approved operating envelope.

Upgrade quotes routinely cost $200K to $1M+ per building
Timeline to complete: 12 to 18 months of utility coordination and construction
Electrical capacity limits block EV charging, heat pump, and battery installations
Engineers rely on outdated NEC assumptions that don't reflect actual building usage
Buildings cannot meet electrification mandates or tenant EV charging requirements.

The hidden truth? Capacity often exists, it is just invisible to traditional methods..

VoltOS closes that gap.

Anchor 1

How VoltOS Works

We measure real capacity, not theoretical assumptions. Proving electrical capacity does not require expensive construction.

VoltOS uses power electronics grade measurement to quantify headroom at the service and produce a decision grade evidence pack.

Step 1:

Instrumentation and Data Capture

Non invasive measurement at the service, plus optional interval data sources, depending on site conditions

Step 3:

Evidence pack for permitting and engineering review

Decision grade report package designed for permitting workflows and professional review where required.

Step 2:

Load study period

Continuous load study per code aligned pathway, with the period and method selected to match the jurisdiction and the engineering workflow.

Step 4:

Capacity Guard

Activation

Ongoing constraint enforcement, audit trail, and compliance record

Outcome: In many cases, VoltOS supports a code aligned path that can materially reduce upgrade scope, cost, or timeline, subject to engineering and AHJ requirements.

Safety and scope boundaries

We enforce only flexible loads explicitly authorized for control
We do not control life safety loads
We support code aligned workflows and professional review where required
VoltOS is designed to fail safe, with safe default behavior on connectivity loss

We provide tooling, telemetry, and enforcement logic, final design approval remains with the project engineer and AHJ

Why Now

Electrification mandates are accelerating, but building service capacity is not. Commercial buildings face growing pressure from three converging forces:

Electrification mandates: Cities and states requiring EV charging, heat pumps, and building decarbonization
EV charging requirements: California, New York, and other jurisdictions now mandate EV charging in commercial buildings
Outdated engineering methods: Engineers often apply conservative NEC based assumptions that overstate peak load.

Utilities require capacity upgrades before approving new electrical loads. But those upgrades cost hundreds of thousands of dollars and take many months.

VoltOS proves whether the upgrade is truly needed — or if the building already has headroom. In many cases, buildings can electrify immediately using their existing service.

The bottleneck isn't the grid. It's visibility.

Current Status

System architecture and security baseline defined
Commissioning workflow v0 complete
Integration targets selected, EVSE and building systems
First paid studies in pipeline

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Product

From capacity audit to full building intelligence

EIOS starts with VoltOS to solve the bottleneck that blocks electrification, capacity evidence and safe enforcement. Over time, VoltOS expands from commissioning into continuous constraint management and system of record

Capacity Audit

Electrify without costly upgrades

Capacity Enforcement

Real-time load

control

EIOS Platform

Institutional Capacity Data Platform

Delivered as edge telemetry plus cloud software. Edge enforces safe defaults, cloud provides audit trail, reporting, and integrations.

Timeline of

Compounding

Moats

From Capacity Intelligence to Full Building Operating System

VoltOS compounds defensibility through compliance workflow adoption, enforcement logs, and an integration library that reduces deployment time per site. Over time, the evidence packs and operating envelope history become a difficult to replace system of record.

Timeline of compounding moats:

Year 1: Technical moat

Year 2: Data moat

Year 3 to 4: Regulatory moat

Year 5: Infrastructure moat

End state: EIOS becomes the system of record and enforcement layer for how electrified buildings operate inside approved electrical constraints.

Software can optimize. EIOS decides what it may physically cause.

One physical truth layer. One operating boundary.

Same action. Different state. Different permission.

The technical object is a graph, not a dashboard.

Four engines, one boundary.

Before autonomous control goes live, derive the boundary.

One bounded system. Try to break the thesis.

The Problem

VoltOS closes that gap.

How VoltOS Works

Safety and scope boundaries

Why Now

Current Status

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