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Built on Blackbox

Atlas turns machine data into maintenance decisions.

Atlas reads machine signals, spots anomalies, scores failure risk and recommends the fix — and explains why. It’s the first application built on Blackbox.

Predictive maintenanceAnomaly detectionFailure riskExplainable
What Atlas does

From signal to decision, in plain language.

  1. Reads your machines

    Vibration, temperature, pressure, current, states, alarms and maintenance history.

  2. Spots what’s changing

    Blackbox condenses the stream; Atlas detects anomalies and emerging failure patterns.

  3. Scores the risk

    Each machine gets a failure risk, combined with production and maintenance context.

  4. Recommends and explains

    A suggested action, the best window to do it, and the evidence behind it.

See Atlas at work

Three machines. Three early warnings.

Run each machine’s data through Blackbox and see the recommendation Atlas produces.

RAW INPUT

      
BLACKBOX
characters sent to AI
  • Repeats removed✓
  • Structure kept✓
  • Signal kept✓
WHAT AI RECEIVES
Press “Run through Blackbox” to see what the model gets.

Illustrative example data. Character counts are measured on the text shown here.

Features

Built for maintenance and reliability teams.

Continuous monitoring

Watches every connected machine, not just the critical few.

Anomaly detection

Flags behaviour that differs from how the machine normally runs.

Failure risk scoring

Ranks machines by risk so crews go where they’re needed first.

Maintenance windows

Suggests when to act, using your production and maintenance schedule.

Explainable recommendations

Every recommendation shows the signals and history behind it.

People approve

Atlas advises. Your engineers decide and act.

Who it’s for

Everyone responsible for keeping the line running.

MAINTENANCE TEAMS

Fix it before it fails

A prioritised list of what needs attention, with the reason and the best time to do it.

RELIABILITY ENGINEERS

Understand the pattern

See how failures develop across machines and which signals warn earliest.

PLANT HEADS

Protect output

Fewer surprise stoppages and maintenance planned around production, not against it.

Why Blackbox matters here

Watching every machine is only worth it if it’s affordable.

Continuous AI monitoring means sending machine data to a model all day, every day. Blackbox cuts what each request carries, which is what makes monitoring the whole plant practical.

MEASURED RESULT
71%

Fewer tokens in our current test workflow, with the same output. Results vary by data, model and task.

How Blackbox works →
Questions

Questions teams ask first.

Does Atlas control our machines?

No. Atlas reads data and recommends actions. It doesn’t write to PLCs or control systems, and your team approves every action.

What data does Atlas need?

Machine signals from your PLCs, SCADA or historians, plus maintenance history if you have it. We start with what you already collect.

Do we need new sensors?

Usually not for a pilot. If a critical machine has no useful signals, we’ll tell you what would help.

How does a pilot work?

We pick one line or machine group, connect read-only, run Atlas alongside your team and review what it caught together.

Put Atlas on your most critical line.

Tell us about your machines and where downtime hurts most. We’ll suggest a pilot scope.