Industrial Intelligence.
Built on over 20 years of codified Industrial Expertise.
- Business-Critical Use Cases
- KPI-Driven Outcomes
- Validated Results within 90 days
- Enterprise-Ready AI Foundation
The missing Intelligence Layer between Industrial Assets and Enterprise AI
We codify industrial expertise into reusable ontology, KPI cascades and outcome-driven methodologies.
Standardized asset information alone doesn’t create business value. Context does.
We connect assets, processes and business outcomes. Creating trusted foundations for industrial AI, optimization and autonomous operations.
Industrial AI starts with Industrial Knowledge.
AI doesn’t create industrial knowledge. It requires it.
SyntelliQ enriches industrial data with context:
- SyntelliQ Solution Framework codifies over 20 years of industrial expertise into reusable ontology, KPI cascades, domain models, semantic models, AI Agents and outcome-driven use cases.
- SyntelliQ Perfect Fuel is the trusted industrial context layer that operationalizes the SyntelliQ Solution Framework. It ensures raw industrial data becomes clean, contextual and connected — connecting assets, processes and business outcomes, ready for Industrial AI.
- SyntelliQ Semantic Layer based on the Asset Administration Shell (AAS) provides the standardized, vendor-independent digital asset model. SyntelliQ consumes and enriches AAS information with industrial context, enabling interoperable and scalable Industrial Intelligence.
Creating trusted Industrial Intelligence that scales across assets, plants and enterprises.
Asset Health, Maintenance & Reliability
- Higher Asset Availability
- Reduced Unplanned Downtime
- Lower Maintenance Cost
- Early Failure Warning & Prediction
- Faster Root Cause Analysis
- Improved Return on Capital Employed (ROCE)
Production, Quality & Process Optimization
- Higher First-Pass Yield
- Lower Scrap Rates
- Fewer Customer Complaints
- Real-Time Production Visibility
- Critical Process Parameter Monitoring
- Improved Capacity Utilization
Operations, Visibility & Control
- Less Blindspots
- Reduced Response Times
- Real-Time Production Visibility
- Faster & Data-Driven Decisions
- Improved Shop Floor Transparency
- Faster Root Cause Analysis
Sustainability, Energy & Resource Optimization
- Reduced Energy Consumption
- Reduced Energy Cost
- Improved Security of Supply
- Greater Production Cost Stability
Industrial Intelligence
Modular. Scalable. Built for your context.
As 70% of industrial companies struggle with digital transformation1, our phased and modular approach supports transformation at every layer of your operation.
Our phased approach is composed of configurable modules. These adapt to your infrastructure, priorities and digital maturity, without lock-ins.
Each module addresses a layer of industrial transformation: from data harmonization to real-time AI enablement, from worker guidance to workflow orchestration.
Built for complexity. Engineered for clarity.
Immediate Outcomes and enterprise-ready AI Foundation
Starting with a clearly defined, high-value industrial use case, every engagement follows our structured methodology:
From operational signals to business outcomes.
Each pilot is designed to deliver validated, measurable results within 90 days.
Creating a proven foundation for enterprise-wide scaling.
- Higher Asset Availability
- Lower Energy Consumption
- Improved Yield & Product Quality
- Reduced Unplanned Downtime
- Faster Root Cause Analysis
- Trusted AI & Autonomous Operations
No technology-driven pilots. No generic AI Initiatives. Every engagement starts with a business-critical use case, measurable KPI targets and a clear commitment to deliver validated business outcomes within 90 days.
Industrial Excellence driven by AI
10% greater profitability
300% return-on-investment
30% greater energy efficiency
Turning raw data into real-time decisions
We don’t just digitize. We deliver.
- Deep expertise in ET, OT & IT
- Seamless integration of third-party systems
- Contextualized, high-quality data as foundation
- Enabling reliable AI performance
- Modular partner solutions for tailored transformation
- Operationalized insights, not just data
- Industrial AI + GenAI deployed in real-world complexity
Built with industrial insights.
Not assumptions.
We don’t just digitize. We design autonomy.
Our approach isn’t plug-and-play — it’s based on deep domain knowledge across manufacturing, energy, utilities, marine, pharma & more.
SyntelliQ understands the friction between legacy systems, production goals & digital tools. Our industry expertise enable us to implement industrial intelligence use cases from shop floor to enterprise-level orchestration.
Get in touchDo you deal with data silos?
Are your systems producing data, but no decisions?
Is your AI initiative delivering results?
Is your AI strategy aligned with your actual workflows?
Are your ET/OT/IT systems aligned?
Can your current setup adapt fast enough?
Recognize your challenges?
FAQ
ET/OT/IT convergence is the integration of engineering technology (ET), operational technology (OT) and information technology (IT). It connects design, operations and business systems to enable smarter, more efficient and data-driven enterprises.
AI in manufacturing helps optimize processes, reduce downtime and improve quality by analyzing large amounts of (production) data.
For example, AI-powered predictive maintenance can detect early signs of machine failure and schedule repairs before breakdowns, saving costs and avoiding production delays.
Data becomes usable for GenAI when it is clean, structured, contextual and accessible. For example, in manufacturing, sensor data labeled with machine type, operating conditions, and timestamps allows AI to not just see numbers but understand which machine is vibrating abnormally under what load, making insights reliable and actionable.
Industrial Intelligence transforms raw industrial data into trusted, contextualized information that can drive business decisions, optimization and autonomous operations. It connects assets, processes and business outcomes, not just data sources.
Industrial Intelligence is the synthesis of two decades of codified engineering expertise and modern, data-driven analytics. Unlike general-purpose AI, which focuses solely on pattern recognition in data, Industrial Intelligence understands the physical constraints,
safety regulations, and operational dynamics of the manufacturing environment. By bridging the gap between engineering (ET), operations (OT), and IT, it translates raw sensor data into reliable, context-aware decisions that optimize production efficiency and
ensure operational stability.
Generative AI can reason over information, but it cannot invent decades of process engineering expertise. Successful Industrial AI requires contextualized industrial knowledge, operational semantics and business logic to produce trustworthy results.
No. SyntelliQ integrates with existing OT, ET and IT systems, protecting previous investments while adding contextual intelligence.
SyntelliQ is vendor independent and integrates with industrial automation systems, historians, MES, ERP, cloud platforms and enterprise applications.
Because most industrial companies already have robust software landscapes in place. SyntelliQ builds the intelligence layer above existing systems instead of replacing them, maximizing the value of existing investments while enabling smarter and more efficient operations.
- Why do most transformations fail? A conversation with Harry Robinson | McKinsey & Company. (2019, July 10) ↩︎
- Empowering advanced industries with agentic AI | McKinsey & Company. (2025, September 8) ↩︎
- Empowering advanced industries with agentic AI | McKinsey & Company. (2025, September 8) ↩︎
- Rewiring maintenance with gen AI | McKinsey & Company. (2025, February 6) ↩︎