FOR THE FIRST QUERY YOU SAVE
Start from a pattern, not a blank editor.
Eight query patterns for live device data, from a simple average to OEE and batch traceability. Copy one, point it at your data, and ask your AI to adapt it.
New to OpenX? Key terms →
FOUR QUESTION SHAPES
- Aggregate
- What was the average, the peak, the total?
- Threshold
- Which readings went over the limit?
- Compare
- How does this device compare with that one?
- Trend
- Is it rising, week over week?
Most questions are one of these four. The eight patterns build on them.
THE EIGHT PATTERNS IN THE LIBRARY
Questions teams ask every week.
Each pattern is a starting point written in KQL for Azure Data Explorer. Adapt it to your devices and fields, then save it as a warm query.
Time-series aggregation
The average, minimum or maximum of a reading over a window, like the last eight hours.
Threshold
Every reading that went over a limit, with when and where.
Device comparison
The same reading across devices, side by side.
Trend
How a reading moves over time, including week over week.
OEE
Overall equipment effectiveness by line, from availability, performance and quality.
Downtime Pareto
Which causes account for most of the lost time.
Batch traceability
The readings behind a batch, for its history and its review.
Energy cost split
Energy use and its cost, divided across lines or sites.
IF YOU KNOW THE QUESTION BUT NOT THE KQL
For people who know the question, not the query language.
Engineers and operations leads
Start from the pattern closest to your question, and let an AI adapt it to your fields.
Data teams
A shared starting point, so every line's OEE is worked out the same way.
App builders
Save a pattern as a warm query, and your app has a parameterised route to call.
WHAT A PATTERN BECOMES
Saved once, it is an API.
A pattern on its own is a query. Saved as a warm query, it takes parameters, gets its own API route under your access rules, downloads as CSV, and is something your AI can read.
- Parameters turn one pattern into many: by line, by site, by time window.
- A later step can filter by keys read from a Cosmos DB container.
- An AI connected over MCP can draft, check and sample a query before a person saves it.
FROM PATTERN TO ANSWER
Three patterns, three jobs done.
OEE for the MES
- 01Start from the OEE pattern.
- 02Add a line parameter and save it as a warm query.
- 03The MES dashboard calls its route.
Batch history for QA
- 01Start from the batch traceability pattern.
- 02Filter the readings by lot keys from a Cosmos container.
- 03QA reads one answer per batch.
An AI adapts it
- 01Ask your AI to adapt the threshold pattern to your sensors.
- 02It checks and samples the query over MCP.
- 03A person saves it.
WHERE EACH PATTERN SHOWS UP
Patterns by the work they serve.
MANUFACTURING
OEE and downtime Pareto, from the docs' manufacturing walkthrough.
LIFE SCIENCES
Batch traceability and threshold checks, from the pharma walkthrough.
ENERGY AND BUILDINGS
Energy cost split across lines, from the energy walkthrough.
Pick a pattern. Save your first query.
Every pattern is in the docs, ready to copy.
MORE OF OPENX
AI governance →
Over MCP, AI proposes and a person accepts. Only a person deploys.
OpenX MCP Server →
A few tools let any MCP-capable AI read your workspace and propose changes to it.
API Manager →
Your workspace is already an API. Decide who may call it and what each caller reaches.
Warm queries →
Save a question over live data and serve the answer to dashboards, apps and AI.
Provenance →
A record you can prove, kept in your own cloud, with corrections and signatures.
Your cloud →
Connect your Azure, build the landing zone, and the rest of OpenX runs inside it.
Databases →
A Cosmos DB store in your subscription, with a governed API for each container.
App Identity →
Your own sign-in directory, identities for your jobs, and access in one window.
Licenses →
Sell what you build on your own Stripe, and turn a subscription into a plan's rights.
IoT →
IoT Hub and Data Explorer in your Azure, feeding queries, APIs and AI.
Communications →
Send mail through your own relay, with the password in your vault and sends on record.
App building →
Data, sign-in, access, an API and billing: your app's backend, already there.