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The Industrial Time Series Tech Stack.
- Visualization: user configurable dashboards, trending and reporting.
- Analytics: 40 built-in calculations & conversions, and low code tools to build more.
- Knowledge Graph: bringing context and meaning to your data.
- Historian: connect to your existing PI, database or leverage Eigen’s augmented InfluxDB
- Data Acquisition: no data migration required with simple APIs to third party sources.
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A breakthrough in data integration, analytics and visualization
Upgrade your legacy industrial systems
Explore how the five layers of the Eigen TechStack could work to solve your industrial data challenges.
1. Visualization:
- Dashboard Visualization & Process Mimics
- Real-time data trending
- Automated reporting
As the top layer of Eigen TechStack, visualisation brings process data to life with dynamic mimics that combine live trends, KPIs, and visual elements for real-time insight into plant performance, supported by built-in tools such as a data editor to easily fix bulk data and optimize managing and maintaining operational data.
Using templated, model-driven displays, dashboards can be rapidly replicated across assets and sites, with the use of tag aliases helping to standardize naming and simplify reuse across different systems while maintaining consistency in design.
Integrated logbooks, event browsing and data-entry tools let operators capture shift notes, manual readings, and operational events directly within the same environment, creating a single, intuitive workspace.
Together with the historian, analytics, and data acquisition layers beneath it, this visualization layer provides engineers with a data-rich workspace where dashboards, analytics, and reporting flow seamlessly to help make the right data-driven decisions.
2. Analytics:
- 40+ built-in calculations and conversions
- Python Library
- Node-RED® workflow orchestration
The analytics layer of the Eigen TechStack gives engineers the tools to transform raw process data into actionable insights. Choose from over 40 built-in virtual calculations including advanced math, totalizers and statistical functions to create virtual KPIs, production totals and ratios.
Condition real time data by calculating aggregates such as moving averages, time-shift and point-in-time. Add filters to remove noise or perform unit conversions. Compare data with thresholds to feed visual indicators, set up custom alerts with the intuitive low-code interface and much more.
For more complex processing, the built-in Node-RED® workflow engine and Python Library allow access to all data sources across the stack, enabling users to build their own automated workflows, scheduled jobs, or custom calculations that can feed dashboards or APIs.
For example, in the image above, a scheduled job queries a public API, uses the data in a calculation, and stores the result directly into the Eigen time-series historian. This shows how analytics can seamlessly integrate with the full stack to produce actionable insights across multiple assets.
3. Knowledge Graph
- Open-source Neo4j integration
Unified context model linking assets, systems and data sources
- Adaptive and incremental
The Knowledge Graph layer is a Neo4j-powered semantic map of operational information that connects assets, systems, documents, tags and their relationships to bring meaningful context to data across an organization. The Knowledge Graph can represent everything from equipment and maintenance plans to drawings and live sensor links, creating a complete and connected picture of how information fits together.
This unified structure enables powerful search, intuitive navigation, model-driven visualization and smarter decision-making. The Knowledge Graph provides the foundation for asset intelligence, built incrementally without disruptive data migration, giving a complete and connected view of the entire operation.
4. Historian:
- Connect to all major historians e.g. PI, AspenTech…
- Or build with Eigen’s own augmented Influxdb®
- Robust foundation for digitalization
The Historian layer of Eigen TechStack provides a powerful foundation for industrial digitalization, storing massive volumes of process and event data with speed, reliability, and full flexibility. Built on open-source Influxdb® and enhanced by Eigen to deliver a powerful, high-performance time-series data platform with no vendor lock-in.
Advanced features such as:
- Data management: Swinging-door compression, Automated backup and recovery.
- High-performance time-series storage with fast access to live and historical data.
- Comprehensive metadata support and configurable tag attributes for complete context.
- Support for configurable tag attributes like .open, .close, .status, and .pv.
Designed for scalability and openness, performance scales with available compute power and network capacity, and a free license is included under the Eigen Support Contract.
5. Data Acquisition:
- Telegraf: OPC UA, ModBus, MQTT for IoT
- Cogent OPC: OPC DA
- Eigen SQL Data Connectors
- Full List of Data Connectors
The Data Acquisition layer of Eigen TechStack forms the foundation for industrial digitalization, capturing process, sensor, and enterprise data from across your operations. Using open, widely supported protocols, it ensures reliable connectivity to ICSS, PLCs, IoT gateways, and other systems.
Data collectors can run either alongside the data source on client infrastructure or within the Eigen deployment, with built-in buffering to prevent data loss during connection outages.
Data from multiple time-series systems is ingested via Telegraf, supporting:
- MQTT
- OPC UA/DA (via Cogent DataHub)
- Modbus, with configurable poll rates or event-driven updates.
Non-timeseries sources such as SQL databases, files, or APIs can be treated as time-series data, or transformed and ingested using Python or Node-RED® scripts through the backend API.
Ingenuity databases natively support both time-series (Influxdb®) and event (PostgreSQL) data for comprehensive, unified storage across the stack.
Typical Data Sources:
Built for Engineers. Proven in the Field.
Eigen TechStack delivers a complete, integrated solution for industrial digitalization, combining high-performance data acquisition, a robust time-series historian, analytics, and visualization. At the top of the stack is the TechStack’s flexible, intuitive dashboards and analytics that adapt to projects of every scale from IoT pilots to enterprise-wide deployments and already delivering results across oil and gas, chemicals, and energy operations.
Ingenuity’s flexible, familiar dashboards make it an excellent replacement for legacy tools like PI Vision, giving engineers the usability they know and trust while providing actionable insights and supporting automated workflows in real-world operations. Explore how these capabilities have been applied in our use cases.
Migrating Live Process data, KIPs and Complex Calculations
From Static Reporting to Live Flight Status Dashboards
Real-time Calculation of Chemical Injection Rates and Inventories
Managed by experts. Supported by experience
Support Includes:
- Ticketing with guaranteed response
- Regular version updates
- Service levels to fit your budget
- Experienced support team
- Optional 24/7 support
Since 2007, Eigen has supported critical industrial systems with dependable engineering expertise. Our managed stack includes continuous monitoring, guaranteed SLAs, and access to the latest Ingenuity updates, giving you modern technologies without the burden of managing them alone.
