Solutions

Manufacturing problems.AI-native solutions.

Every solution is backed by real ML models trained on real industrial data. Production-grade intelligence running in autonomous loops, with published accuracy numbers you can verify.

Asset Performance

Know what will break. Fix it before it does.

Unplanned downtime costs $42K–$120K per hour. We prevent it. Most customers avoid 2–3 catastrophic failures per site, per year.

Remaining useful life estimation across rotating equipment, pumps, bearings, and drives

Multi-algorithm anomaly detection that adapts to each equipment's unique signature

Automatic root cause analysis triggered when anomaly scores exceed thresholds

Automated work order generation with priority scoring based on real-time health index

Explainable predictions showing which sensor readings are driving each alert

Digitillis / Predictive Maintenance
RUL
18d
Health
62%
Confidence
87%
Degradation Curve
Today
Top Features
vibration_rms92%
temp_bearing78%
current_draw45%
87%
Reduction in unplanned downtime
40%
Lower maintenance costs
18 days
Average failure prediction window

Illustrative data points

Production Excellence

More output. Same equipment. Less waste.

You already own $20M+ in equipment. We'll show you how to get 12–18% more throughput without buying anything new.

Continuous OEE monitoring decomposing availability, performance, and quality losses

Throughput optimization identifying the process parameters that move the needle

Bottleneck detection pinpointing constrained stations across multi-stage production lines

Intelligent job-shop scheduling balancing makespan, priority, and resource constraints

Digital twin simulation for what-if scenarios before making physical changes

Digitillis / Production Analytics
OEE
91.2%
Throughput
+12%
Bottleneck
Stn 3
Hourly Output vs Target
6a7a8a9a10a11a12p1p
OEE Decomposition
Availability94%
Performance96%
Quality99%
12%
Throughput improvement
98.4%
Throughput model accuracy (R²)
Real-time
Bottleneck identification

Illustrative data points

Workforce & Operations

The right person, the right task, the right time.

Frontline workers are the last mile of manufacturing intelligence. Digitillis closes the loop between AI insights and human action, generating work orders, briefing shift teams, and delivering precise instructions to the technician standing in front of the machine.

AI-driven maintenance scheduling with priority-based work order generation and technician assignment

Automated shift handoff summaries briefing crews on equipment status, active alerts, and pending actions

AI-generated work instructions tailored to equipment type, failure mode, and technician skill level

Technician skill matching that routes the right person to the right task based on certification and availability

Mobile-ready interfaces for frontline workers delivering context at the point of action

Digitillis / Workforce & Operations
Open WOs
12
Technicians
8/10
Shift OEE
91%
Work Order Priority
WO-042CNC-001Critical
WO-043Pump-03High
WO-044Conv-07Medium
Shift Handoff Status
Tasks Completed78%
On Schedule92%
Assigned85%
65%
Faster work order response
40%
Reduction in mean time to repair
Real-time
Shift-level visibility

Illustrative data points

Supply Chain

See disruptions coming. Respond before they arrive.

Supply chain disruptions increased 38% in the last three years. Digitillis provides end-to-end visibility from delivery risk scoring to spare parts demand forecasting, helping you maintain continuity when your supply chain gets tested.

Delivery risk scoring that flags at-risk shipments before they become late

Spare parts demand forecasting with seasonal decomposition and trend detection

Order promising that gives customers reliable delivery dates based on real capacity

Inventory optimization balancing service levels against carrying costs

Autonomous monitoring that continuously reassesses risk as conditions change

Digitillis / Supply Chain
On-Time
94%
At Risk
3
Lead Time
4.2d
Delivery Risk Scores
Bearings Co.Low
Steel SupplyMedium
Motor PartsHigh
Spare Parts Forecast
3 days
Average early warning for disruptions
25%
Reduction in inventory carrying costs
94%
Order promising accuracy

Illustrative data points

Sustainability

Reduce your footprint. Prove it with data.

Manufacturing accounts for 21% of global carbon emissions. Digitillis tracks energy consumption, carbon intensity, and ESG metrics across your operations in real time, identifying optimization opportunities and generating the audit trail your sustainability reporting demands.

Granular energy consumption modeling at the machine, line, and plant level

Carbon footprint tracking with scope 1, 2, and 3 emission breakdowns

Sustainability initiative tracking with measurable progress indicators against targets

ESG compliance dashboards purpose-built for regulatory and investor reporting

Energy optimization recommendations with projected savings and ROI timelines

Digitillis / Sustainability
Energy
342kW
CO₂
-15%
ESG Score
A-
Energy Consumption (7 Day)
Emissions by Source
Manufacturing52%
HVAC28%
Transport20%
15%
Energy cost reduction
99.6%
Energy model accuracy (R²)
Real-time
Carbon emission tracking

Illustrative data points

Business Value

Prove what AI is worth. In dollars, not dashboards.

Most AI platforms show predictions. Digitillis tracks outcomes. Every intervention, every prevented failure, every optimization is measured against what would have happened without the platform. You get counterfactual ROI, cost avoidance tracking, and value narratives your CFO can take to the board.

Counterfactual analysis comparing actual outcomes to what would have happened without intervention

Every alert we raise has a price tag. If we say 'fix this,' we track what you actually saved. 87% of recommendations this quarter prevented real downtime.

Cost avoidance quantification across prevented failures, reduced scrap, and energy savings

Executive value narratives translating operational metrics into financial language

Portfolio-level ROI dashboards showing cumulative platform value over time

Digitillis / Value Realization
Total ROI
$2.4M
Avoided
$890K
Days to Value
47
Value Realized (30 Day)
Value by Domain
Predictive Maint.42%
Production Excel.28%
Energy Optim.18%
$22K–$38K
Typical avoided cost per intervention
< 90 days
Time to first documented ROI
4.2×
Average platform ROI

Illustrative data points

Which problem costs you the most?

Let us show you the solution. With your data, on your equipment, for your KPIs.

Talk to Our Team