AI-Native Manufacturing Platform

Your factory, thinking ahead.

Digitillis deploys 35+ autonomous AI agents across your manufacturing floor, predicting failures, optimizing throughput, and surfacing insights that turn data into measurable business value.

35+
Autonomous AI Agents
16
Production Prediction Loops
28
Trained ML Models
8
Architecture Layers

Why Digitillis

Manufacturing intelligence that works while you sleep

We built Digitillis because the factory floor deserves better than static dashboards and manual threshold alerts. Real manufacturing intelligence means AI that acts, learns, and explains itself. Autonomously.

1

Not just dashboards. Autonomous intelligence.

Most manufacturing platforms give you dashboards. We give you 35+ AI agents that run autonomously, monitoring, predicting, and recommending in continuous loops, 24/7. You set the thresholds. They do the watching.

2

Models trained on real industrial data.

Every model in the platform is trained on real-world datasets: NASA turbofan engines, SECOM semiconductor lines, Bosch production data, Scania truck systems. No toy demos. No synthetic-only benchmarks.

3

Built for manufacturing. Not adapted from IT.

OPC-UA, MQTT, and Modbus connectivity at Layer 1. ISA-95 equipment hierarchies. Time-series-native storage with TimescaleDB. This is a manufacturing platform built by people who understand the factory floor.

Capabilities

Six pillars of manufacturing intelligence

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

87%
Unplanned downtime reduction

Predictive Maintenance

Predict equipment failures days in advance. Our RUL models trained on NASA C-MAPSS achieve R² > 0.85, giving you the confidence to schedule maintenance before downtime hits.

60s
Detection cycle time

Anomaly Detection

Continuous monitoring across hundreds of sensor channels. Ensemble models detect subtle deviations invisible to human operators, flagging issues at the earliest possible stage.

92%
Defect detection accuracy

Quality Intelligence

Move from reactive inspection to proactive quality control. Statistical process control, defect classification, and root cause analysis work together to drive zero-defect outcomes.

15%
Energy cost reduction

Energy & Sustainability

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

3 days
Average early warning

Supply Chain Visibility

End-to-end supply chain intelligence from delivery risk prediction to spare parts demand forecasting. Stay ahead of disruptions with proactive risk scoring.

12%
Throughput improvement

Production Optimization

Bottleneck detection, throughput optimization, and OEE analytics working in concert. Identify constraints and maximize output without additional capital expenditure.

Architecture

8 layers. 3 pillars. One platform.

From OPC-UA connectivity at the edge to executive ROI dashboards, every layer of the Digitillis stack is purpose-built for manufacturing. No bolted-on IT tools. No one-size-fits-all analytics.

Intelligence Pillar: AI/ML models, knowledge graphs, autonomous agents
Experience Pillar: ARIA copilot, executive briefings, real-time dashboards
Operations Pillar: Edge connectivity, time-series data, Kafka streaming
Deep dive into the architecture
L8
Business Value
ROI tracking, value narratives, executive dashboards
L7
Experience
Web UI, ARIA copilot, reports and briefings
L6
Agentic
35+ autonomous AI agents, multi-agent orchestration
L5
Cognitive Semantic
Knowledge graph, learning engine, context retrieval
L4
Intelligence
ML models, predictions, model registry
L3
Integration
Kafka streaming, REST APIs, enterprise connectors
L2
Data
TimescaleDB, PostgreSQL, Neo4j, Redis
L1
Connectivity
OPC-UA, MQTT, Modbus, edge gateway
Built-in AI Copilot

Meet ARIA

The Adaptive Real-time Industrial Assistant. Ask questions in natural language, get answers backed by your actual production data. ARIA coordinates across all 35+ agents to deliver contextual, explainable insights.

Why is CNC-003 vibrating above threshold?

CNC-003 shows elevated vibration (4.2mm/s, threshold 3.5mm/s) correlated with bearing wear. RUL estimate: 18 days. Recommend scheduling maintenance within 10 days. Similar pattern preceded failure on CNC-001 last quarter.

Ready to make your factory think ahead?

See how Digitillis transforms your operational data into autonomous intelligence. We will walk you through the platform with your data, your use cases, your KPIs.