What your team sees

Integrated view of your entire operation from different lenses.

Operations, executive, and financial perspectives, all powered by the same autonomous AI agents and live data.

Digitillis / Operations Hub
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Good morning. Your insights briefing for Saturday, February 14:
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All 8 machines are active with no alarms. Floor is running at full capacity.
Production is running 12% ahead of pace, on track to exceed target by ~94 units.
OEE spread across running machines is 14.2 points (CNC-001 at 96.8% vs Press-02 at 82.6%). Investigate Press-02 for quick-win improvements.
Machines Running
7/8
1 idle
Floor OEE
91.2%
+2.3%
Parts Produced
1,847
Target: 2,400
Active Alarms
2
1 critical
On Shift
12
Day Shift
Machine Status
RunningIdleMaintAlarm
CNC-001running
OEE: 96.8%72%
JOB-4472
CNC-002running
OEE: 94.1%45%
JOB-4468
CNC-003alarm
Requires attention
CNC-004running
OEE: 91.5%88%
JOB-4471
Lathe-01running
OEE: 89.3%62%
JOB-4465
Press-01running
OEE: 87.4%34%
JOB-4470
Press-02idle
Awaiting job
Pump-A1running
OEE: 92.7%51%
JOB-4469
Active Alarms
CNC-003 vibration 4.2mm/s2m
Bearing degradation ~18d5m
Lot M-2847 moisture +8%12m
Shift Progress
Parts Produced1,847 / 2,400
77.0% of target
Quality Rate
99.2%
Scrap Count
14
Hourly Output vs Target
6am7am8am9am10am11am12pm1pm
Energy (kW)
342 kW-4.2% vs avg

Built on industry-standard protocols and technologies

OPC-UAMQTTModbusTime-Series DBKafkaRedisNext.jsFastAPI
AI-powered factory operations

Autonomous AI agents. Each an expert in its domain.

Your operations team sleeps. The platform doesn't. Failures are detected and escalated before your shift starts.

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Agent OrchestratorAll systems active
Cycle: 847ms avg
RUL Prediction
120s loopHigh accuracy
Last: 3s ago
Anomaly Detection
60s loopStrong detection
Last: 12s ago
Equipment Health
120s loopHigh precision
Last: 45s ago
Demand Forecast
300s loopReliable forecasting
Last: 1m ago
Bottleneck Detect
300s loopHigh precision
Last: 22s ago
Carbon ESG
300s loopNear-perfect accuracy
Last: 2m ago
Quality Control
120s loopHigh-confidence detection
Last: 8s ago
Throughput Opt.
300s loopHigh accuracy
Last: 31s ago
Cost Avoidance
300s loopRobust classification
Last: 55s ago
Intelligent AI-Assistant

ARIA: Your Factory's Intelligence Layer.

One conversation to surface any insight, coordinate any workflow, and reason across your entire manufacturing operation. ARIA connects equipment data, AI predictions, maintenance history, and supply chain signals, then answers in plain language, grounded in what is actually happening on the floor. Not a chatbot. An orchestration engine.

"What is driving the OEE drop on Line 3?"
"Show me equipment at risk of failure in the next 30 days."
"Schedule maintenance and notify the shift supervisor."
See ARIA in action
ARIA
Autonomous Reasoning Industrial Assistant
Online
What is driving the OEE drop on Line 3?
Line 3 OEE dropped from 91.2% to 87.4% over the past 6 hours. Analysis of the three OEE components:Availability: 94.1% (stable)Performance: 96.8% → 92.1% (degraded)Quality: 99.2% (stable)The performance drop correlates with CNC-003 cycle time increase (+14%). Root cause: elevated bearing vibration causing micro-stoppages.
Schedule maintenance for CNC-003 and notify the shift supervisor.
Done. Here's what I've set up: Work order WO-1847 created for Thursday planned window Technician Ramirez assigned (bearing specialist) Spare part BK-440 confirmed in stock Shift supervisor Martinez notified via email
Ask anything about your factory...
CNC-003 / Predictive MaintenanceWarning
Updated 3s ago
Remaining Life
18d
±3 days (95% CI)
Health Score
62%
-5% this week
Confidence
87%
Ensemble model
Degradation Curve (90 Day Forecast)
TodayFailure zone
Root Cause
Bearing wear
Vibration: 4.2mm/s (threshold 3.5). Similar to CNC-001 failure pattern (Q3 2025).
Top Features
vibration_rms92%
temp_bearing78%
current_draw45%
spindle_speed23%
Predict. Prevent. Protect.

Know when equipment will fail. 18 days in advance, on average, with a confidence score your team can schedule against.

Remaining Useful Life predictions with explainability for every forecast and uncertainty quantification so you know exactly how confident each prediction is. Schedule maintenance when it matters, not on an arbitrary calendar.

Learn more
Real-time anomaly detection

Spot problems humans cannot see

Ensemble models across hundreds of sensor channels detect subtle deviations that precede equipment failures. High-frequency detection cycles with automatic alert escalation.

Anomaly Detection / Sensor Correlation
1,247 normal23 anomalies
Temperature (°C)Vibration (mm/s)
Sensor Correlation
TempVibPresRPMCurrFlowTempVibPresRPMCurrFlow
-1.0
+1.0

Pillars of manufacturing intelligence

Each powered by real ML models, trained on real industrial datasets, running in autonomous loops with sub-minute cycle times.

Predictive Maintenance

Know when equipment will fail days in advance. Models trained on real-world industrial datasets deliver predictions your team can act on.

Anomaly Detection

Catch the failures that stop your line, 2 to 4 weeks before they happen.

Quality Intelligence

Defect prediction, SPC analytics, and root cause analysis working together. Move from reactive inspection to zero-defect manufacturing.

Energy & Sustainability

Track carbon emissions, energy consumption, and ESG metrics in real time. AI optimization reduces waste while maintaining production targets.

Supply Chain Visibility

Delivery risk prediction, demand forecasting, and spare parts optimization. Stay ahead of disruptions with proactive risk scoring.

Production Optimization

Bottleneck detection, throughput optimization, and OEE analytics in concert. Find constraints and maximize output without additional capex.

From sensor data to boardroom decisions.

Every reading, every alert, every intervention: connected, explained, and measured. See it running on your equipment.