💨 Up to 30% lower compressed air costs

Make compressed air losses visible. Before they eat your budget.

Compressed air is expensive, but the biggest loss drivers often stay invisible. Upload pressure, runtime, and consumption data to spot patterns that point to leaks, poor control logic, or unnecessary base load faster.

See solution
14-day trialRuns in the browserCSV instead of an integration project

Up to

30%

potential savings in compressed air systems when leak indicators, base load, and operating logic are reviewed with data instead of assumptions alone.

Before

  • • Loss drivers stay hidden across shifts and operating states
  • • Compressors run in poor combinations or too long at base load
  • • Consumption and actual demand are not compared cleanly

After

  • • See when consumption and demand drift apart
  • • Find patterns that point to leaks
  • • Review compressor strategy with data

Trial

Start in just a few minutes

Upload your first CSV and work directly in the browser.

Setup

No local installation

Your team can test dAIve without a rollout or IT project.

Input

CSV from your existing tool

Export data from your current stack and get started immediately.

Support

Personal support via email

support@daive.de

Target

Perfect for

Production companies (SMEs)
Mechanical engineers using compressed air
Workshops & production halls
Energy managers
Problem

The Problem

Compressed air is one of the most expensive energy forms on site, yet leakages, base load, and compressor behavior often remain unclear. Without data analysis, waste easily becomes normal.

Loss drivers stay hidden across shifts and operating states
Compressors run in poor combinations or too long at base load
Consumption and actual demand are not compared cleanly
Actions are prioritized from assumptions instead of data
Solution

The Solution

dAIve turns compressed air data into a clearer action list: surface anomalies, compare patterns, and review the biggest levers first.

1

See when consumption and demand drift apart

Compare load profiles across time, shifts, and operating states to spot unnecessary base load earlier.

2

Find patterns that point to leaks

Use pressure, runtime, and consumption data to investigate suspicious phases more deliberately.

3

Review compressor strategy with data

See which combinations stay stable and where control logic or sequencing may be driving cost.

Next step

Losses visible. Actions prioritized faster.

potential savings in compressed air systems when leak indicators, base load, and operating logic are reviewed with data instead of assumptions alone.

Up to

30%

Workflow

How it works

From CSV to first actionable insights in under 20 minutes.

1

2 min

Export data

Export pressure, runtime, consumption from control system.

2

1 min

Upload & analyze

dAIve reveals patterns, drivers, and suspicious load phases.

3

5-15 min

Prioritize levers

See which operating states deserve review first.

4

instant

Verify changes

Compare updated patterns and observe the effect.

FAQ

Use case FAQ

The key questions before you start your trial with your first CSV.

Can I use CSV exports from meters, BMS, or existing energy systems?

Yes. As long as you can export values as CSV, you can load them into dAIve and analyze directly.

How quickly do I see first savings opportunities?

Usually during the trial itself, within minutes after upload, target definition, and model training.

Do I need an integration project for the trial?

No. Start in the browser with a CSV export from your current setup.

Next step

Every hidden compressed air loss keeps running every day.

Start your 14-day trial and use your first CSV to see which losses you should tackle first.

All use cases
14-day trialRuns in the browserCSV instead of an integration project