Self-diagnostic factory

A system capable of self-diagnostics, that doesn't wait for the right questions. Stay one step ahead and act before small issues become costly problems.

Industrial factory landscape with AI-powered maintenance management overlay
Triage1 new finding
MAINT-2847
ALARM

Vibration exceeding threshold on Pump Station C

Agent Activity

Trusted by Norwegian manufacturers

Hoff SANorsk KyllingNordic DoorWonderland

The platform

Everything you need to stay one step ahead

See how customers use Digel

Explore your data

Ask questions in plain language, build dashboards, and see how your process data connects across systems.

Explore your data
Assistant
Y

Show me this week's operations summary

Generated dashboard

Efficiency

87.3%

↑ 2.1% vs last week

Uptime

99.2%

↑ 0.3% vs last week

Weekly output

M
T
W
T
F
S
S

Automated reporting

Get shift reports, production summaries, and status updates delivered automatically.

Automated reporting
AI Agent

Anomaly detection

3 anomalies flagged in Sector B

Pattern recognition

In progress…

Recommendations

  • Schedule maintenance for Pump #4 within 48h
  • Reduce flow rate in Line 2 by 12%
  • Review sensor calibration on Tank A

Root cause analysis

When something goes wrong, Digel helps you trace back through your data to find out why.

Root cause analysis
Assistant
Pump #4 is showing unusual vibration levels
I see elevated readings at 142 Hz. This pattern typically indicates bearing wear. Checking maintenance history…
When was it last serviced?
Last service was 847 operating hours ago. Based on current trend, I recommend scheduling maintenance within 48 hours.
Ask about your operations…

How it works

Human in the loop, AI in the background

Step 1

Continuous monitoring

Digel continously monitor your operations to look for deviations.

Industrial monitoring
Event Stream
CMMSERPTelemetry
10:00:00ERPScrap booking: 2× damaged impellers
10:00:15TelemetryCoolant flow CF-3: 18.4 L/min
10:00:30CMMSPM schedule triggered — Pump C overdueFlagged
10:00:45ERPMRP run completed — 6 planned orders
10:01:00ERPPO-1185 created for seal kit (×8)
10:01:15TelemetryPower consumption: Line 2 — 142 kW
10:01:30ERPGR posted for PO-1179 — gaskets (×50)
10:01:45CMMSRoot cause recorded: misalignment on P-205
10:02:00ERPSpend analysis report exported
10:02:15CMMSWO-4540 pending approval from Maintenance Lead

Monitoring · 2,847 events today · 1 flagged

Step 2

Flagged in Triage

When something deviates, Digel creates a issue in Triage, investigates the problem, looks at related documents and manuals, analyzes telemetry data and compiles in an easy to read format.

Triage investigation
Triage
ALARM

Pump C — PM schedule overdue

Flagged from event stream · 2 min ago

Agent Investigating

Step 3

Human in the loop

You review each finding and decide what action to take. Accept, dismiss, or investigate further, every decision teaches the system what matters.

Human in the loop review
Triage
3 findings to reviewLast scan: 2 min ago

Reviewed: 0/3 · 0 work orders created

Step 4

Act on the insights

When it's time to act, Digel helps build the work order. Pre-filled with diagnostics, part numbers, and maintenance history. You fix machines, AI writes the report.

Act on insights
Work Orders
Backlog3 open
WO-4521Pump C — PM overdue
Open
WO-4530Motor M-112 corrective
Scheduled
WO-4533HX-201 inspection
Open

3 work orders · 2 open · 1 scheduled

The foundation

Powered by your own industrial context graph

Industrial context graph showing connected equipment, sensors, and maintenance data

Interconnected

Every tag, asset, work order, production order, and process data point is connected and modeled, giving Digel the full picture of how you operate.

Custom Ontology

No two companies are alike. Digel lets you model your own production process and connect the data sources you need.

Capture tribal knowledge

Digel helps you capture the hidden knowledge within your team and become more resilient for the future.

Works with what you have

Digel connects to the systems you already use. Easy to configure, easy to scale.

Questions and Answers

Try out the playground or test with your own data