ENERGY MONITORING - HYBRID

Hybrid Track: Monitor Without Replacing

You have meters. You have a BMS. Now add OpenX beside them.

You are not replacing your BMS or swapping meters. You are adding a workspace where meter data lands, is organized on surfaces, and is read through saved queries.

What you will have

• One consumption view across your meters and sources
• Saved queries for cost allocation and sustainability
• API endpoints for your reporting tools
• Any AI over MCP, reading the same queries

All without touching your existing metering.

Phase 1: Connect your data

Step 1.1: Add a connection

On the canvas

1. Open your workspace.
2. Drag a Connection node from the Node Bank onto the canvas.
3. In its inspector's Settings tab, set the Connection ID (tick Is IoT Edge Device if an IoT Edge gateway sends for it). There is no connection string to enter: the connection sets up its own device identity.
4. Save, then Deploy. Deploy registers the connection as a device on Fathym's shared IoT hub, or your own once your workspace has its IoT fabric.
5. Open the inspector's Connection Info tab. It shows the credentials your gateway or BMS integration uses to send data (device, MQTT, AMQP and HTTP details).

Or ask Azi

Step 1.2: How your sources reach OpenX

Source	How it reaches OpenX
Smart meters, submeters	Sent through a gateway to the connection's device (MQTT, AMQP or HTTP)
BMS	Through an edge gateway to the connection's device
Utility feeds (API or CSV export)	An API Source polling an HTTP endpoint

When data arrives, it shows in the Live Stream panel.

Phase 2: Create consumption surfaces

Surfaces organize your energy data. A connection feeds a surface when you draw a line from it to the surface.

Step 2.1: A building surface

Ask Azi in the main panel:

"Create a surface for building energy monitoring, fed by the building meters connection."

She proposes a Building-Energy surface wired to the connection. Accept it; a surface is live as soon as it is accepted.

Step 2.2: Line-level surfaces

For finer allocation, add a surface per area:

Surface	Fed by	Purpose
Production-Line-1	Line 1 meters	Line-specific consumption
HVAC-Systems	Chiller and air-handler meters	Building systems
Lighting	Lighting circuits	Area lighting

Phase 3: Build cost allocation queries with Azi

In the main Azi panel, Azi proposes each warm query together with the surface it sits on; accept it and it is live. Inside the Warm Query Manager, she drafts the query instead and you save it with the canvas Save icon.

Step 3.1: Daily consumption

"Create a warm query for total electricity consumption by day over the last 30 days."

Data
| where EnqueuedTime > ago(30d)
| extend Payload = todynamic(RawData)
| where tostring(Payload.meterType) == "Electric"
| summarize TotalKWh = sum(todouble(Payload.kWh)), PeakKW = max(todouble(Payload.kW)) by bin(EnqueuedTime, 1d)
| order by EnqueuedTime asc

Step 3.2: Cost allocation by area

"Build a query that allocates electricity cost to each area based on consumption."

Data
| where EnqueuedTime > ago(1d)
| extend Payload = todynamic(RawData)
| where tostring(Payload.meterType) == "Electric"
| summarize Consumption = sum(todouble(Payload.kWh)) by Area = tostring(Payload.area)
| extend CostPerKWh = 0.12 // your rate
| extend AllocatedCost = Consumption * CostPerKWh
| order by AllocatedCost desc

Step 3.3: Peak demand

"Create a query for our top 10 peak demand hours in the last month."

Data
| where EnqueuedTime > ago(30d)
| extend Payload = todynamic(RawData)
| where tostring(Payload.meterType) == "Electric"
| summarize PeakKW = max(todouble(Payload.kW)) by Hour = bin(EnqueuedTime, 1h)
| top 10 by PeakKW desc
| project Hour, PeakKW, DayOfWeek = toint(dayofweek(Hour) / 1d) // 0 = Sunday

Phase 4: Call your queries over REST

Every warm query is a REST endpoint.

Step 4.1: Find your endpoint

1. Open APIs -> API Manager and its Warm Queries tab.
2. Under Configured Queries, each saved warm query has its own card, with ready-to-copy cURL, TypeScript and Python.
3. Get a key from APIs -> API Keys.

Step 4.2: Call it

curl -X GET 'https://openx.fathym.com/ox-api/warm-queries/daily-consumption' \
  -H 'Authorization: Bearer YOUR_TOKEN'

Step 4.3: Where it plugs in

Integration	Use
ERP	Monthly cost allocation posting
Dashboard	Consumption display
Sustainability platform	Emissions reporting
Alerting	Peak demand notifications

See APIs for Power BI and Grafana.

Phase 5: Connect any AI over MCP

The OpenX MCP Server is at https://openx.fathym.com/ox-api/mcp. Sign in through the browser:

• Claude.ai or ChatGPT: add a custom connector, paste the URL, sign in with OpenX, pick the workspace and tick the rights to share.
• Coding agents: run fai mcp install https://openx.fathym.com/ox-api/mcp --name openx and sign in when the browser opens.

Setup for each client is in Bring Any AI. Then ask:

"What's driving our electricity costs this month compared to last month?"

The AI reads your saved queries with call_api. If it wants to build something new, it proposes it with manage_proposals, and a person accepts.

What you built

Component	Status
Meter connection	Built on Deploy, sending data
Consumption surfaces	Organized by building and line
Allocation queries	Three saved warm queries
API endpoints	One per warm query
MCP	Any client reading the same queries

Before and after

Before	After
"The meter showed this"	The saved query behind the number, there to read
Spreadsheet reports	Reports that call the same saved queries
Manual allocation	One allocation query, the same for everyone

Next steps

If you want to...	Go to...
Try the full track	Full track
See query patterns	Query Patterns
Connect more AI clients	Bring Any AI
Explore manufacturing	Manufacturing