DataOS for Manufacturing
Improve operational performance. Accelerate AI with the data you have.

Q: What does natural language querying mean in practice?

An engineer types a question like 'why did failure rates spike last week?' or 'which machines are running above normal vibration right now?' and gets an answer in seconds from live production data. No SQL required, no dashboard ticket, no waiting for a data team response.

DataOS connects data across MES, ERP, quality, supply chain, and operational systemsto create a trusted foundation for manufacturing operations, analytics, and AI.

See what’s possible in 30 minutes.

Bring your biggest data challenges. We'll show you how leading manufacturers connect data and improve operational performance.

Recognized by experts. Proven by results.

“In just eight weeks, we had a data infrastructure in place that allowed us to transform how we use data. Today, millions of live telemetry events flow through the platform to power GenAI applications with a 30-second SLA.”

– Global Head of Technology, Lenovo

Manufacturing Data Is Everywhere. Operational Understanding Is Not.

Manufacturing data lives across MES, ERP, quality systems, supply chain platforms, and plant applications. Without a shared operational foundation, teams spend more time reconciling information than acting on it.

Data is disconnected

Data exists across machines, systems, and plants, but critical relationships between events, assets, and processes remain hidden.

Answers take too long

Simple operational questions often require data from multiple systems, teams, and reports, delaying decisions when timing matters most.

Definitions are inconsistent

Different plants, systems, and teams use different definitions, making it difficult to measure performance and identify improvement opportunities.

Decisions rely on instinct

Without a trusted operational view, teams fall back on experience and intuition instead of current operational data.

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With DataOS, operations run on trusted data.

See what changes when every team, plant, and system works from the same operational foundation.

Traditional
Operations

Reports show what already happened
Failures discovered after the line stops
Engineers spend hours searching for answers
Every new use case rebuilds the same integrations
Leaders depend on analysts to get answers

Manufacturing Intelligence with DataOS

Equipment failure signals surface hours in advance
Assets are monitored continuously, not at shift end
Teams ask a question and get an answer in seconds
One data product, reused across every use case
Answers available instantly without analyst involvement

See How Lenovo Did It

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Manufacturing Intelligence on DataOS continuously connects detection, action, and learning

See how quickly DataOS can transform your device or operational data step by step

Ask your operations anything Detect what is changing Prioritize what matters Direct the next action Track execution and results

Ask your operations anything

A natural language interface over your production data. Engineers type a question and get an answer in seconds from live operational data. No SQL. No dashboard ticket. No waiting.

Detect what is changing

DataOS does not just store your data. It activates it, connecting signals across MES, SCADA, ERP, and IoT into an intelligence layer your AI models and teams can actually use.

Prioritize what matters

Surface assets with the highest failure probability or quality risk. Engineers see which machines need attention this shift, not next week.

Direct the next action

Recommend what to do next for each asset -- which bearing to replace, which work order to pause, whether parts are in stock. Prescriptive, not just predictive.

Track execution and results

Monitor uptime improvements, quality outcomes, and response times in real time. Every action feeds back into the system, improving accuracy over time.

Build once. Deliver value everywhere.

Reduce engineering effort, accelerate innovation, and bring
new manufacturing initiatives to market faster.

Most tools report on operations. This system changes how they are managed.

Most platforms surface data. DataOS changes what happens next by directing actions based on
real-time signals across every asset in your plant.

Not reporting, execution

DataOS directs what to do next, not just what happened. When a sensor detects a failure pattern, the system recommends an action -- pause a work order, schedule maintenance, confirm parts availability -- not just a dashboard update.

Asset-level intelligence

Focuses where operational decisions are actually made -- at the machine, the line, the shift. Not aggregate plant-level reporting, but specific guidance for the specific asset that needs attention right now.

Unified intelligence layer

Combines predictive maintenance, natural language querying, and 360 asset data products in a single governed layer. Built once, reused across every use case. No rebuilding integrations every time a new question emerges.

Continuous system

Improves with every action taken. As engineers respond to recommendations and outcomes are recorded, the system refines its predictions and priorities. Accuracy increases over time without manual tuning.

One shared view

Leaders gain visibility while teams gain direction. A plant manager and a maintenance engineer see the same data, the same priorities, and the same recommended actions -- without going through an analyst.

Get one trusted view of every plant.

See what one view of every plant looks like on the systems you already run.

Frequently Asked
Questions

Does DataOS work with our existing AI and analytics tools?

Yes. DataOS does not replace your AI or analytics layer. It sits beneath it, providing the clean, unified, governed data those tools need to run. Whether you are using Snowflake, Databricks, or your own models, DataOS makes the data underneath them consistent, fast, and ready to use.

How is this different from a standard IoT dashboard or MES?

IoT dashboards capture data. MES systems record activity. DataOS changes what happens next by connecting those signals into a governed data product layer that predicts failures and directs actions, not just displays readings.

How does the system identify equipment failure risk?

It monitors changes in sensor readings - vibration, temperature, pressure - and correlates them with maintenance history, production schedules, and tool inventory to detect early indicators of failure before they cause downtime.

What does natural language querying mean in practice?

An engineer types a question like "why did failure rates spike last week?" or "which machines are running above normal vibration right now?" and gets an answer in seconds from live production data. No SQL required, no dashboard ticket, no waiting for a data team response.

Does this require replacing our existing systems?

No. DataOS connects to your existing MES, ERP, QMS, and IoT platforms without copying or duplicating data. Your systems stay where they are. DataOS sits on top as a unified intelligence layer.

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How quickly can we see impact?

Impact begins as soon as signals are unified. Based on live deployments, organizations see working use cases within two weeks of connection. Early wins include identifying at-risk equipment and improving response times.

Can leaders get answers without going through an analyst?

Yes. The natural language interface gives every team member -- from plant floor engineer to VP of Operations -- direct access to production data. Questions are answered instantly without analyst involvement.

Ready to Transform  Your Data Strategy?

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DataOS for ManufacturingImprove operational performance. Accelerate AI with the data you have.

​See what’s possible in 30 minutes.

Manufacturing Data Is Everywhere. ​Operational Understanding Is Not.