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From the field

Questions plant teams ask us

Manufacturers planning a plant-wide data foundation ask us the same things. Here are their questions, in their words, with what MaestroHub does today and a real screen from a running instance.

Where it fits

It sits on what you already run

We already have an MQTT broker. Why would we need another layer on top?

A broker moves messages; it does not know what a value means, whether it is any good, or who wrote it. MaestroHub keeps a meaning, a quality verdict and the writer on every value, permissions per topic, and a buffer when a destination is down.

Do we have to replace our OPC servers, SCADA and broker?

No. MaestroHub reads the OPC servers you already run and connects to SCADA platforms and other brokers as sources and destinations. Nothing below it has to move on day one.

A vendor line sending °F, read by everyone in °C.
  • Can one platform take data from PLCs, MES, maintenance and lab systems across all our shops?More than 100 connectors bring every source into one plant structure by site, area, line and machine, with a workspace per shop or domain.
  • Which PLCs and protocols do you read? We have old lines and mixed brands.Siemens S7, EtherNet/IP, Modbus, MELSEC, Omron, TwinCAT, OPC UA and OPC DA, and more. PROFINET, DNP3, IEC 61850 and OPC HDA are not supported today.
  • Every shop names and measures things differently. How do we make them comparable?Give each signal a meaning and a unit, once. A line that sends °F reaches every reader in °C on the same topic, and the device never changes.LiveBeta
  • Can we define assets, equipment types and processes, or only signals?Today the plant structure holds sites, areas, lines and machines, and meanings sit on signals. Equipment types are not available yet.
  • Do you follow ISA-95? Is it an OPC UA server? Sparkplug B?The namespace follows ISA-95-shaped levels as a convention. MaestroHub is an OPC UA client, not a server, and publishes and listens as a Sparkplug B edge node.

Security and IT approval

Your servers, your rules

Can it run entirely on our own servers, with nothing sent to you, even with no internet?

Yes. You install it on your servers, edge devices or your own cloud account, and the licence is checked offline. A new installation sends nothing to us until an administrator agrees, and air-gapped sites can switch it off.

Will it pass our IT security review?

Single sign-on over OIDC, SAML and LDAP, roles in every workspace, permissions per topic, stored credentials encrypted per installation, and TLS. MFA comes from your identity provider; there is no built-in MFA.

Built-in roles separate who connects machines, who builds pipelines and who only reads.
  • Which certifications do you hold?The company holds ISO/IEC 27001:2022, which you can check yourself. It covers how we build and support the software, not the product. We do not hold SOC 2 or IEC 62443.
  • Can it write back to our machines safely?Writes need an explicit permission per connection and are recorded in the audit trail. They are never replayed late from a buffer, and an approval step can hold one until a person decides. It is a data path, not a safety-rated control loop.

Running it

From one line to every plant

What architecture do you recommend for a plant-wide data foundation?

Collect close to the machines, standardise once in one plant structure, and distribute per use case to specialised stores.

We have many plants. Can we manage them centrally and roll one setup out to the next site?

Each site can be its own workspace in one installation. A site's connections, pipelines, topics and dashboards export as one bundle that imports into the next site, with a dry run first. Central push to many installations is not available yet.

Collect close to the machines, standardise once, distribute per use case.
  • What happens if the server dies?On Kubernetes, services run as replicas and a failed node's connections move to another replica. A single machine has no redundancy; its buffers protect the destinations, not the machine.
  • Will it handle our volume?We publish one measured benchmark with its method, machines and limits on the performance page. We size with you on your hardware during a pilot.
  • What hardware and operating system does it need?Linux or macOS on amd64 or arm64, Windows on amd64, as a binary or in Docker; Kubernetes for Enterprise. No special hardware.
  • Do we need a box in every plant?No. Run it at the line, in the plant DMZ or centrally. An edge instance keeps working when the uplink is down and forwards later.
  • How do upgrades work, and can we go back?Patch releases replace the binary or image. Releases that change stored data are checked first on a copy, applied all or nothing with a backup, and can be restored.

Can we trust the numbers?

Every value carries its proof

How do you measure data quality?

Every value is good, uncertain or bad, with a reason. A sensor that freezes is flagged even when the PLC still says good, and a source that goes quiet shows as late with the failing connection named.

Can we trace a value back to the machine it came from?

Any value walks back through the pipeline run and function version to the machine address it was read from, and records who wrote it: a person, an API client or an AI agent.

The PLC says good. MaestroHub stores it as uncertain: frozen for an hour.
  • How do we know a data stream has stopped?Each connection has a health state, and one alert per outage goes to Teams, Slack or a webhook. With meanings, silent sensors are listed too.
  • Something stopped working. Can we see who changed what, and undo it?Every change to connections, pipelines, topics, users and roles goes into a tamper-evident audit trail. Pipelines and functions keep versions you can compare and revert.

Your stores and your systems

Standardise once, publish everywhere

Can we publish the standardised data to our time-series, vector and graph databases?

A pipeline per target writes to InfluxDB, TimescaleDB, ClickHouse and others, to PostgreSQL with pgvector, to Neo4j, and to Kafka and the lakehouse.

What happens to the data when one of those stores is down?

Every target has its own buffer on disk. An outage at one store becomes a pause, not a loss, and the buffer is delivered when the store returns.

One store down: its buffer grows, nothing is lost.
  • We already have a historian. Can we still report on last month or last year?Yes. Your historian stays. MaestroHub keeps 1 to 32 days per topic by design and writes to the long-term store you run, where monthly and yearly reports belong.
  • We have no MES. How do you join SAP orders with machine data?Orders come in through SAP IDoc, Event Mesh, HANA or the S/4HANA APIs, and a pipeline joins them with the machine counter by order and time. There is no RFC or BAPI connector.
  • Can we keep our own dashboards and BI?Yes. Any MQTT client can subscribe within its permissions, the REST API serves recent and historical values, and pipelines can write into the database your BI tool reads.
  • Can you deliver to our cloud data platform in batches?Values are grouped by count or size and written as Parquet to OneLake, Databricks, Snowflake, BigQuery, S3 and others. Batching by time is not available yet.

Process flow and graph

Your plant as a graph, linked to live data

Can we model our process flow and the relationships between machines?

MaestroHub publishes the plant structure, the meanings and the process flow to your graph database, keyed by the same topics, so a graph question comes back with values and quality.

The process flow in Neo4j, written every two minutes by a MaestroHub pipeline.

Trying and buying

Try it before you decide

Can we try it ourselves before we buy?

Yes. Download it and it runs an evaluation you can extend, with a factory simulator for live data without hardware. For a pilot we propose one line, no production writes and six weeks.

How is it licensed?

Per site, not per tag and not per user. Prices are on our offerings page.

Every answer on this page links to the docs, where you can follow the steps on your own evaluation copy.

  • You are a young company. What if you disappear, and who owns our data?Your data stays in your environment and your stores, configuration exports as open JSON, and releases are signed with an SBOM you can verify without us.

AI agents

Governed agent access

Can our AI assistants use this data safely?

Agents connect over MCP with their own access token. They see only what that token allows, and every value they write records who wrote it.

Can they use our own private model, or our Copilot?

Any MCP client works, including one driven by a model you host, and MaestroHub calls no model unless you configure one. Copilot Studio has a setup guide.

Each agent connects as its own client, with its own permissions.

Questions come from manufacturers we work with and are published without names. Screens from MaestroHub on our demo plant. Full answers, with the steps: docs.maestrohub.com/questions. For volume, see the measured benchmark on the performance page.

Have a question that is not here?

Ask us. We answer on a running instance, and the good questions end up on this page.

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