Seeq
Seeq is an advanced analytics software platform designed for process manufacturing industries to rapidly investigate and share insights from time-series data stored in historians and cloud data stores.
TrendMiner
TrendMiner is a self-service industrial analytics software providing predictive maintenance and process optimization tools for engineers to analyze, monitor, and predict manufacturing performance using time-series data.
Quick Comparison
| Feature | Seeq | TrendMiner |
|---|---|---|
| Website | seeq.com | trendminer.com |
| Pricing Model | Custom | Custom |
| Starting Price | Custom Pricing | Custom Pricing |
| FREE Trial | ✘ No free trial | ✘ No free trial |
| Free Plan | ✘ No free plan | ✘ No free plan |
| Product Demo | ✓ Request demo here | ✓ Request demo here |
| Deployment | ||
| Integrations | ||
| Target Users | ||
| Target Industries | ||
| Customer Count | 0 | 0 |
| Founded Year | 2013 | 2013 |
| Headquarters | Seattle, USA | Hasselt, Belgium |
Overview
Seeq
Seeq provides you with advanced analytics tools specifically built for process manufacturing data. Instead of spending days manually cleaning data in spreadsheets, you can connect directly to your historians and IoT platforms to visualize trends and identify root causes in minutes. You can easily search through years of data to find specific operation patterns or equipment failures across your entire enterprise.
The platform enables your engineers to collaborate in real-time using shared workbooks and automated reports. You can build predictive models to anticipate maintenance needs and optimize production yield without requiring a background in data science. It is designed for heavy industries like oil and gas, pharmaceuticals, and chemicals where high-frequency time-series data is critical for daily decision-making.
TrendMiner
TrendMiner gives you the power to analyze, monitor, and predict industrial process performance without needing a data science degree. You can plug it directly into your existing data historians to uncover patterns, troubleshoot quality issues, and identify the root causes of production deviations in minutes rather than days.
By using a high-performance search engine and pattern recognition, you can compare current sensor data against historical 'golden runs' to ensure your operations stay on track. It is designed specifically for process engineers in the chemical, oil and gas, and pharmaceutical industries who need to turn massive amounts of time-series data into actionable insights to improve overall equipment effectiveness.
Overview
Seeq Features
- Workbench Analytics Identify trends and calculate KPIs across massive time-series datasets using an intuitive point-and-click interface.
- Organizer Reports Create dynamic documents and dashboards that update automatically as new process data flows into your system.
- Data Lab Access the power of Python libraries to build custom machine learning models and advanced data science workflows.
- Pattern Search Find specific process conditions or equipment behaviors instantly across months of data to replicate best practices.
- Predictive Modeling Build and deploy regression models to forecast future performance and prevent costly unplanned downtime.
- Contextualization Overlay data from different sources like SQL databases and historians to see the full story behind your operations.
TrendMiner Features
- TrendHub Analysis. Search through years of historical process data instantly to find specific events or patterns using a Google-like search interface.
- ContextHub Documentation. Add context to your sensor data by capturing digital logs and shift notes to explain why process changes occurred.
- DashHub Monitoring. Create personalized operational dashboards to monitor your most critical process parameters and key performance indicators in one view.
- Predictive Alerts. Set up automated monitors that notify you the moment your process deviates from established optimal operating windows.
- Pattern Recognition. Identify recurring process behaviors automatically to predict future outcomes and prevent potential equipment failures before they happen.
- Cross-Asset Comparison. Compare the performance of similar assets across different production lines or global sites to standardize your best practices.
Pricing Comparison
Seeq Pricing
TrendMiner Pricing
Pros & Cons
Seeq
Pros
- Rapidly cleans and aligns messy time-series data
- Eliminates the need for manual spreadsheet calculations
- Excellent collaboration features for remote engineering teams
- Direct connection to major industrial data historians
- Intuitive interface for non-data scientists
Cons
- Requires a significant initial time investment
- Pricing is not transparent for small teams
- Advanced Python features require coding knowledge
TrendMiner
Pros
- Fast search capabilities across massive historical datasets
- Empowers engineers to perform analytics without data scientists
- Seamless integration with major industrial data historians
- Intuitive interface mimics familiar web search experiences
Cons
- Requires high-quality historical data for accurate predictions
- Initial configuration of data connectors takes technical effort
- Pricing is not transparent for smaller manufacturing sites