Solutions
Manufacturing problems. AI-native solutions.
Every solution is backed by real ML models trained on real industrial data. No demos. No simulations. Production-grade intelligence running in autonomous loops.
Know what will break. Fix it before it does.
Unplanned downtime costs manufacturers an estimated $50B per year. Digitillis Remaining Useful Life (RUL) agents monitor equipment continuously, predicting failures days or weeks in advance, giving your maintenance teams the window they need to act.
What this means in practice
RUL prediction trained on NASA C-MAPSS turbofan data (26K engine cycles)
Anomaly detection with SECOM-trained ensemble models (5 algorithms)
Root cause analysis triggered automatically when anomalies exceed thresholds
Automated work order generation with priority scoring based on health index
SHAP-based explainability showing which sensor readings drive each prediction
From reactive inspection to proactive prevention.
Quality issues caught at the customer are 10x more expensive than those caught in-line. Digitillis combines statistical process control, defect classification, and root cause analysis into a closed-loop quality system that catches deviations before they become defects.
What this means in practice
Steel fault classification trained on Severstal production data
Statistical process control with real-time control chart monitoring
Automated root cause analysis correlating quality events with process parameters
Compliance monitoring across OSHA, ISO 9001, ISO 14001, ISO 45001, and EPA frameworks
Prescriptive recommendations with what-if analysis and multi-objective optimization
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.
What this means in practice
Energy consumption models trained on Steel Industry (35K rows) and Mining datasets
Carbon ESG models using Steel Energy + OWID CO2 + EPA GHGRP data
Sustainability initiative tracking with measurable progress indicators
ESG compliance dashboards for regulatory reporting
Energy optimization recommendations with ROI projections
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.
What this means in practice
Delivery risk models trained on DataCo Supply Chain (180K rows) + E-Commerce Shipping
Order promising predictions from Olist Brazilian E-Commerce (100K orders)
Spare parts demand forecasting with seasonal and trend decomposition
Supply chain risk scoring with 600-second autonomous monitoring
Bottleneck detection trained on Bosch Production Line (1.18M rows)
More output. Same equipment. Less waste.
Getting more from your existing capacity is the highest-ROI investment in manufacturing. Digitillis combines OEE analytics, throughput optimization, and bottleneck detection to find and unlock hidden capacity, without capital expenditure.
What this means in practice
Throughput optimization trained on Bosch Production Line + FJCS scheduling data
Bottleneck detection with RandomForest on 1.18M production records
OEE analytics with continuous monitoring of availability, performance, and quality
Digital twin models for equipment state simulation and what-if scenarios
Cost avoidance analysis quantifying the financial impact of prevented failures
Industries
Purpose-built for industrial operations
Discrete Manufacturing
Automotive, aerospace, electronics, machinery
Equipment-intensive production lines with complex maintenance scheduling and quality requirements.
Process Manufacturing
Chemicals, pharmaceuticals, food & beverage
Continuous processes where energy optimization, quality consistency, and compliance are critical.
Metals & Mining
Steel, aluminum, copper, rare earth minerals
High-energy operations where sustainability tracking and predictive maintenance drive significant value.
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