AspenTech Inmation™

Centralized data management system that allows for the ingestion, processing, augmentation and storage of diverse data, empowering your team from the plant floor to the executive suite.

Liberate Your Industrial Data

The editors of IoT Evolution World magazine have chosen AspenTech Inmation for a 2023 IoT Evolution Industrial IoT Product of the Year award. This award honors the best, most innovative products and solutions powering the Industrial Internet of Things. Winners represent prominent players in the market who consistently demonstrate the advancement of technologies and are verifiable leaders in the marketplace.

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Easily Manage One System

Manage the distributed system entirely from a central location – configuration, security, monitoring and license management included.

Seamless Connectivity

All major OT and IT interfaces supported: OPC UA, Classic OPC (DA/HDA/A&E), MODBUS, PLC, ODBC, http, MQTT, Kafka and more.

Scale Without Limits

Horizontally scale a single system across the enterprise, increasing data integrity, data driven automation and advanced analytics capabilities.
ARC Executive Panel:  AspenTech’s Acquisition of Data Management Leader, inmation

AspenTech Inmation and Your Industrial Data Strategy

Learn how companies like BASF and Bayer make better, faster business decisions using data-driven information:

  • Aggregating global operational data into a centralized storage repository foundation for business intelligence, AI and analytics
  • Unlocking and reconciling information from legacy systems to enable plant and enterprise-wide operational improvements
  • Realizing a measurable return on digital transformation efforts while achieving top performance
  • Visualizing and sharing industrial data to support sustainability goals and investments

 

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"The addition of Inmation software to the AspenTech portfolio is a huge step forward to help companies unlock more value from an industrial data strategy. The Inmation real-time data platform connects diverse systems and addresses many problems with data cleansing, contextualization and scalability."

— Peter Reynolds, Principal Analyst, ARC Advisory Group.

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