dAIve/Use Cases
⚙️ Up to 20% less idle energy

Make idle time visible. Before it gets expensive.

Are machines drawing energy without delivering productive output? Connect machine status, consumption, and production data to see when idle phases, waiting states, or poor cycling create avoidable cost.

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

Up to

20%

potential energy savings when idle phases, waiting states, and poor cycling become visible in data instead of staying stuck in assumptions.

Before

  • • Idle phases stay invisible in day-to-day line operations
  • • Waiting states and short stops accumulate across shifts
  • • Energy use is not linked to output or machine state

After

  • • Detect idle phases automatically
  • • Link energy use to output
  • • Compare cycle patterns more clearly

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

✓ Manufacturing companies
✓ Medium-sized producers
✓ Mechanical engineers
✓ Production managers
Problem

The Problem

Idle time costs more than electricity alone. It also hides how inefficiently machines are really being used. Without linking energy and production data, it stays unclear when consumption creates output and when it does not.

Idle phases stay invisible in day-to-day line operations
Waiting states and short stops accumulate across shifts
Energy use is not linked to output or machine state
Loss-reduction actions are hard to prioritize
Solution

The Solution

dAIve connects machine status, energy, and output into a clearer picture: expose idle time, compare cycle patterns, and focus on the worst loss phases first.

1

Detect idle phases automatically

Find time windows where machines consume energy while producing little or no useful output.

2

Link energy use to output

Review how consumption, status, and production volumes actually relate to each other.

3

Compare cycle patterns more clearly

See which shifts, jobs, or operating states generate the most loss time.

Next step

Idle visible. Improvements easier to act on.

potential energy savings when idle phases, waiting states, and poor cycling become visible in data instead of staying stuck in assumptions.

Up to

20%

Workflow

How it works

From CSV to first actionable insights in under 20 minutes.

1

2 min

Collect data

Machine status, energy, production numbers.

2

1 min

Start analysis

dAIve reveals patterns, state changes, and anomalies.

3

5-15 min

See loss phases

Identify idle and waiting periods with a high energy share.

4

instant

Compare actions

Review where timing or workflow should be adjusted first.

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 idle phase costs output and energy.

Start your 14-day trial and use your first CSV to see where your line is consuming energy without enough return.

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