See the failure coming, and where it began.
Mira carries the Datasight platform into operations. It joins the readings from your machines with their maintenance history, the parts register and what your suppliers declare. Sites, networks and fleets then appear as a single operation your teams can follow.
On screen
A drift, and the batch behind it.
Pumps on the same line, read over time. One of them leaves its normal band. Mira flags it with the part batch it shares with earlier failures. The team knows which machines to inspect next.
How it works
From the reading on the machine to the supplier of the part.
Each reading tied to its machine
Vibration, temperature, pressure and run hours arrive with the maintenance log and the ERP. Mira attaches them to the asset they describe, ready to compare.
A normal band for each machine
Mira learns how each machine usually behaves. A reading that wanders away is flagged with a plain explanation of what changed.
Back to batch and supplier
A failed part is followed through the parts register to its batch and its supplier. The other machines fitted from that batch come up with it.
Sites side by side
Each site names its machines in its own way. Mira matches them, so plants and fleets can be compared like for like.
A drift becomes a case
The case opens in Nora with the readings and logs attached. The choice to stop, inspect or withdraw a batch then rests on the facts.
Questions from the floor
Where else is this pump model installed? Anna AI's answer tells maintenance where to look next.
Why it matters
The early signs, in one view.
The signs live in your systems: a vibration creeping up, a part from a batch with a history, a certificate to verify. Mira joins what each team holds. Maintenance then acts at the moment it chooses.
Show us the machine you watch most closely.
Mira works with the sensors and logs your plants have now.