About
TrendMiner is a technology platform purpose-built for industrial operations, enabling data-driven decision-making without requiring deep data science expertise. It connects to a wide range of operational data sources — including machine sensors, Manufacturing Execution Systems (MES), Quality Management Systems (QMS), ERP systems, and field data such as shift logs and operator rounds — and transforms raw time-series data into meaningful, contextualized events. The platform's analytics layer covers time-series analytics, event analytics, statistics, machine learning, and visualization, all accessible through a fast and intuitive interface designed for the entire operations team. An AI Analytics Agent provides autonomous monitoring, pattern recognition, and insight generation around the clock. Key capabilities include 24/7 monitoring with instant alerts, a Data Catalog for organizing cross-source data, data contextualization through feature engineering, and collaborative reporting with personalized dashboards. TrendMiner also supports Operations Performance Management (OPM), Asset Performance Management (APM), and Reporting, Compliance & Safety use cases. Trusted by 48% of the top 50 largest chemical manufacturers globally, TrendMiner serves 28 industry segments including chemicals, discrete manufacturing, food & beverages, energy & natural resources, life sciences, and utilities. Customers report over $500K in annual recurring value per site. The platform is rated a Leader in Time Series Analytics and is significantly faster than comparable historian tooling.
Key Features
- Time-Series & Event Analytics: Powerful analytics layer covering time-series data, event detection, statistics, and machine learning — all designed for industrial operations teams.
- AI Analytics Agent: An agentic AI that autonomously monitors plant data, detects patterns, and surfaces insights 24/7 without requiring manual queries.
- Data Contextualization: Transforms raw time-series data into meaningful operational events using feature engineering, enriching the data layer for deeper analysis.
- 24/7 Monitoring & Alerts: Continuous plant and asset monitoring with instant alerts to keep operations running smoothly and prevent unplanned downtime.
- Reporting & Collaboration: Personalized dashboards, shared insights, and collaborative reporting tools that help cross-functional teams stay aligned on performance.
Use Cases
- Monitoring chemical plant performance in real time and detecting process deviations before they cause quality or safety issues.
- Managing asset health and predicting equipment failures to minimize unplanned downtime in manufacturing facilities.
- Generating compliance and safety reports by contextualizing operational time-series data into auditable event records.
- Comparing historical operating conditions to identify best-operating models and replicate top performance across shifts and sites.
- Enabling operations engineers to independently explore and analyze sensor data without relying on centralized data science teams.
Pros
- Accessible to Non-Technical Users: Designed for the entire operations team, not just data scientists — a fast, intuitive interface enables broad adoption across plant floors.
- Deep Industrial Connectivity: Integrates with MES, QMS, ERP, sensors, and field data sources out of the box, covering the full operational data landscape.
- Proven Enterprise Track Record: Trusted by 48% of the top 50 largest chemical manufacturers, with customers reporting over $500K in annual recurring value per site.
- Broad Industry Coverage: Serves 28 industry segments including chemicals, manufacturing, food & beverages, energy, life sciences, and utilities.
Cons
- Enterprise-Only Pricing: TrendMiner is positioned as an enterprise product with no publicly listed pricing, making it inaccessible to smaller organizations without a sales engagement.
- Narrow Industry Focus: The platform is optimized for industrial and manufacturing environments; organizations outside these verticals may find limited relevance.
- Implementation Complexity: Connecting diverse operational data sources and configuring the data contextualization layer may require significant onboarding effort.
Frequently Asked Questions
What industries does TrendMiner serve?
TrendMiner serves 28 industry segments including chemicals, discrete manufacturing, food & beverages, energy & natural resources, life sciences, metals & mining, and utilities & facilities.
What is the TrendMiner Analytics Agent?
The Analytics Agent is an agentic AI feature that autonomously monitors operational data, detects patterns, and generates insights around the clock — reducing the need for manual data exploration.
How does TrendMiner connect to existing data sources?
TrendMiner integrates with machine sensors, MES, QMS, ERP systems, field data rounds, shift logs, and asset hierarchies, providing a unified operational data layer across data types.
Do users need data science expertise to use TrendMiner?
No. TrendMiner is designed to be fast and intuitive for the entire operations team, empowering engineers and operators — not just data scientists — to generate insights and make data-driven decisions.
What value do TrendMiner customers typically achieve?
Global market-leading customers report over $500,000 in annual recurring value per site, driven by improvements in operational efficiency, reduced downtime, and better-informed decision-making.
