The Data Trust Layer for Industrial AI

Industrial AI doesn’t fail in the model, it fails in the data. DataWise is the autonomous data quality system that makes historian, sensor, and process data ready for AI models, and decisions that depend on it.

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Just a few of the industrial leaders who trust Aperio to make their data ready for every decision.

12

Tags analyzed daily

15

Data quality engine categories

3

Weeks to deployment

0

Manual rule-setting or thresholds

Why Industrial AI Stalls

Industrial historians hold tens of thousands of channels. Sensors drift, instruments fail, networks drop, pipelines lose samples – and nobody notices until a model makes a wrong call, a report runs on bad numbers, or an operator acts on stale data.

OT data is noisy

AI assumes a stable input stream;
plants don’t deliver one.

OT ownership is fragmented

Historians sit with OT, data lakes with IT, and quality with no one.

AI initiatives dodge the core process

Unreliable data pushes AI to the periphery, and the hard problems stay unsolved.

DataWise positioned between data sources and downstream consumers Sources Trust Layer Consumers Historians PI, AspenTech, etc. Sensors Time-series tags Data Lakes Snowflake, Databricks APERIO DataWise The OT data trust layer Detect Measure Triage Remedy Monitored. Scored. Remediated. Before it reaches any AI model, report, or decision. Analytics AI Models CloudPlatforms Dashboards Decisions Trusted data, every time
Sources
Sensors
Time-series tags
Historians
PI, AspenTech, etc.
Data Lakes
Snowflake, Databricks
Trust Layer
APERIO DataWise
The OT data trust layer
Detect
Measure
Triage
Remedy
Monitored. Scored. Remediated.
Before it reaches any AI model, report, or decision.
Consumers
Analytics
AI Models
Cloud Platforms
Dashboards
Decisions
Trusted data, every time

What Aperio Delivers

Clean data without manual prep

Automatically monitors every historian channel detecting the exact anomalies that corrupt model training: flatlines, bad values, outliers, abrupt changes, and more.

Quantify your data readiness

The Data Quality Index (DQI) gives you a quantified readiness score at the channel, asset, or site level. Validate training data, gate model deployment, and get a measurable answer to "is our data good enough?

Ensure consistency between
on-premise and cloud data

DataWise Consistency Monitor verifies that your Snowflake, Databricks, or Azure data faithfully reflects the historian source - catching pipeline dropout, sampling loss, and latency violations that silently degrade inference quality.

Remediate bad data before it
reaches your models

Defines event types and severity thresholds to trigger imputation, correction, or deletion. The result: a clean, audited export that your models can train on with confidence.

Product Capabilities

Always-on
Anomaly Detection

Self-supervised micro-models analyse every tag across mutlipe dimensions (bad values, flatlines, outliers, abrupt changes, noise distribution, and more) with no manual thresholds, training data, or rule configuration required.

Data Quality
Agent

Albert is your AI data quality expert. Ask plain-language questions about data issues, investigate root causes, and surface the most severe events — without building queries or interpreting dashboards manually.

Data Remediation
Agent

Go beyond just detecting bad data. Configure remediation rules by event type and severity to automatically correct, interpolate, or remove flagged data before it reaches your AI models or reports.

Historian Analyzer

Know the true state of your data source. Surface dead and stale tags, configuration mismatches, orphaned signals, and full-channel statistics to establish a baseline of what’s actually happening inside your historian.

Consistency Monitor

Auto-verify that your Snowflake, Databricks, or Azure data lake faithfully reflects the  source. Catch latency, dropouts, sampling imbalance, and silent pipeline failures before they corrupt downstream analytics or AI inference.

Intelligent Scoring

Our proprietary Data Quality Index (DQI) gives every tag, asset, and site a continuous trust score. Quantify data readiness, gate model deployment, and finally answer the question: is our data good enough?

Integrations

Aperio plugs in seamlessly to the historians, data lakes, and analytics tools you already use.

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"With half a million PI tags, manually checking everything is just not scalable. APERIO gives us the confidence that the sensors feeding our decisions are actually trustworthy."
Rich Guhl
Digitalization Lead, Covestro

Stop guessing. Start trusting your data.

See how DataWise quantifies, monitors, and remediates your industrial data – in a 30-minute demo tailored to your stack.

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