Global Product Manager at a pharma/biotech company with 501-1,000 employees
Real User
Top 20
May 4, 2026
Seeq can improve by incorporating more advanced data pipelines. While they have a strong training program and academy, additional hands-on training would be beneficial. The product essentially functions as a supercar that you can drive as fast as needed, so improvements depend on how much users want to get from the tool. Seeq is already distilling something very complicated into something that is relatively easy to use. The à la carte approach allows users to employ just the time series visualization functionality, some calculations, the worksheets, Data Lab, and other features as needed. One challenge was the limited capability to have custom input or script input within the web user interface. More advanced flows required using the Data Lab API or other deprecated APIs. Seeq's core strength is tapping into SQL databases from a process historian. If you are not using that primary use case, workarounds are available, but you need automation engineering support. I chose a rating of eight because Seeq is definitely above average compared to other offerings. The company ethos, customer support, and ability to listen to the market to drive product improvements are positive factors. The feature set is quite comprehensive and unique, though not perfect. The user interface could be simplified, and the non-conventional ways of loading data via the user interface could be improved.
Within the organization structure and sometimes when trying to replicate existing worksheets and organizer topics from one Seeq system to another, there is no import or export feature of those tools. I understand that because of the way the data sources may identify the individual tags, it makes that difficult between one Seeq environment and another, but having the ability to map those at some level to be able to migrate effectively would be a very essential tool for going from a development environment using Seeq Analytics Workbench into a production environment that might not have the same underlying mapping. Some way to import and export and then change from one environment to another would be a good feature to have. I choose a nine because all tools have room for improvement, but this one covers a very large breadth of the analytic need and connects to the majority of data sources that are needed for data analytics, whether it be SQL data sources or historian data sources, and it integrates well within the cloud data space. It definitely fits that niche very well. However, some graphing and tabular functions are still being worked on and are yet to be included fully.
Machinery Engineer Intern at a university with 10,001+ employees
Real User
Top 10
May 4, 2026
Sometimes the software would be a bit slow to respond, and that may be because there were too many users at once. I am not sure exactly what the reason for that could be, but if that was on the end of Seeq and not on the internet connection, which seemed to be quite reliable, then that would be my only complaint.
ENGINEER at a computer software company with 201-500 employees
Real User
Top 10
Apr 30, 2026
I would like to test the software for free for a longer time. I believe Seeq should offer an on-premise server option. I prefer on-premise deployment because for many companies, data is a valuable asset.
I think Seeq could improve by including a section that has SQL-type visualizations to visualize tables of data and not reference them to the timestamp, as that has caused us some problems at times. The features I feel are missing for the platform to be perfect include being able to use tags or variables recorded in the same time span.
I have a couple of suggestions for the organization, and I've told them as well. Nowadays, time-series analysis for manufacturing units is a primary need. What they're looking for is the incorporation of artificial intelligence and machine learning into these tools and then getting some insights out of it, which is closed-loop. Till now, we have been facing open-loop solutions. But how to apply these insights or inferences into my manufacturing unit, which is running 24/7? Being an engineer and a person who comes from the industry, I would rather believe in first principles than a data science model. To break the ice, they need to come up with more of the predictive part of it using machine learning techniques, which can be closed-loop solutions, which can help operators and automation engineers to apply these insights into the units rather than keeping it open-loop.
Regarding AI, I wish Seeq had AI capabilities. For instance, if Seeq could analyze graphs and offer recommendations, it would be advantageous. Currently, there is no AI feature in Seeq. In terms of improvements, it would be great if Seeq could enhance its data export features and possibly integrate more functionalities to reduce the need for multiple software tools. I would like a specific feature related to predictive analysis, which Seeq currently lacks.
As for improvements, I felt there should be a more efficient way to address repetitive customer questions, perhaps using chatbot technology to streamline responses. In terms of functionality, I noticed that certain machine learning methodologies, like Principal Component Analysis (PCA), were missing from the Workbench. While it was possible to perform these analyses in DataLab, adding such features to Workbench would enhance user experience and allow for more complex calculations without needing to switch environments.
Seeq is evolving. We only included time series analysis in the first version. Going forward, we introduced many complex Seeq tables. You give the temperature and pressure, and the solution will give you the enthalpy of steam. It would be wonderful if a time series model could be built with the thermodynamic package. We have Aspen Hysys for thermodynamic package dissimulation. When we interpret both, it will be magical.
They have many features addressing various issues. For example, something I developed plots the gains in a prediction model, which could be a built-in capability in Seeq. Artificial intelligence support exists for the Datalab environment. The advanced functionality requires some training.
Seeq Organizer, which is used for dashboarding, has some limitations. In Seeq Organizer, we've realized that process engineers want dashboards with more drag-and-drop features, like Power BI. Seeq has limitations in terms of the variety of widgets and visualizations you can use. You're limited to a few types like line charts, bar charts, and pie charts (which was introduced recently). Power BI offers a wider range of dashboarding options. It's not that Seeq is solely a dashboarding tool; it can connect to Power BI and Tableau. But customers who purchase Seeq and expect its dashboarding feature to be competitive with Power BI and Grafana might be disappointed. So, dashboarding is where I see a lot of room for improvement in Seeq.
Supply Chain Analyst at a manufacturing company with 10,001+ employees
Real User
Top 20
May 21, 2024
The analytical part is fine. We can do our analysis. But the dashboard, where we approve the dashboard, is not ideal for someone who uses Seeq only as a tool to see data in a report format. Seeq Workbench, Seeq Organizer, and Seeq Data Lab are great platforms where we do our analysis, but if they could add features to Seeq Organizer for publishing reports, that would be helpful. Currently, there are many tools on the market that provide aesthetic dashboards, like Power BI or Tableau. These tools make it easy to create reports that are understandable even for those who don't know anything about the data. So, Seeq could work on the reporting format, but the analytical tool is excellent.
I have noticed that Seeq sometimes struggles with connectivity issues, leading to data gaps. This is an area that needs improvement. While connecting to data, sometimes, due to connection loss or issues with the tool itself, the tags may not display any trends, resulting in missing information.
Seeq is a powerful platform designed to enhance the connectivity and visualization of industrial data, facilitating seamless workflows and intuitive user interactions. It excels in handling large datasets while enabling predictive models and real-time monitoring without requiring extensive coding skills.Seeq's ease of use and user-friendly features make it a go-to choice for professionals seeking effective time series data analysis. It supports a wide array of industries including oil and gas...
Seeq can improve by incorporating more advanced data pipelines. While they have a strong training program and academy, additional hands-on training would be beneficial. The product essentially functions as a supercar that you can drive as fast as needed, so improvements depend on how much users want to get from the tool. Seeq is already distilling something very complicated into something that is relatively easy to use. The à la carte approach allows users to employ just the time series visualization functionality, some calculations, the worksheets, Data Lab, and other features as needed. One challenge was the limited capability to have custom input or script input within the web user interface. More advanced flows required using the Data Lab API or other deprecated APIs. Seeq's core strength is tapping into SQL databases from a process historian. If you are not using that primary use case, workarounds are available, but you need automation engineering support. I chose a rating of eight because Seeq is definitely above average compared to other offerings. The company ethos, customer support, and ability to listen to the market to drive product improvements are positive factors. The feature set is quite comprehensive and unique, though not perfect. The user interface could be simplified, and the non-conventional ways of loading data via the user interface could be improved.
Within the organization structure and sometimes when trying to replicate existing worksheets and organizer topics from one Seeq system to another, there is no import or export feature of those tools. I understand that because of the way the data sources may identify the individual tags, it makes that difficult between one Seeq environment and another, but having the ability to map those at some level to be able to migrate effectively would be a very essential tool for going from a development environment using Seeq Analytics Workbench into a production environment that might not have the same underlying mapping. Some way to import and export and then change from one environment to another would be a good feature to have. I choose a nine because all tools have room for improvement, but this one covers a very large breadth of the analytic need and connects to the majority of data sources that are needed for data analytics, whether it be SQL data sources or historian data sources, and it integrates well within the cloud data space. It definitely fits that niche very well. However, some graphing and tabular functions are still being worked on and are yet to be included fully.
Sometimes the software would be a bit slow to respond, and that may be because there were too many users at once. I am not sure exactly what the reason for that could be, but if that was on the end of Seeq and not on the internet connection, which seemed to be quite reliable, then that would be my only complaint.
I would like to test the software for free for a longer time. I believe Seeq should offer an on-premise server option. I prefer on-premise deployment because for many companies, data is a valuable asset.
I think Seeq could improve by including a section that has SQL-type visualizations to visualize tables of data and not reference them to the timestamp, as that has caused us some problems at times. The features I feel are missing for the platform to be perfect include being able to use tags or variables recorded in the same time span.
I have a couple of suggestions for the organization, and I've told them as well. Nowadays, time-series analysis for manufacturing units is a primary need. What they're looking for is the incorporation of artificial intelligence and machine learning into these tools and then getting some insights out of it, which is closed-loop. Till now, we have been facing open-loop solutions. But how to apply these insights or inferences into my manufacturing unit, which is running 24/7? Being an engineer and a person who comes from the industry, I would rather believe in first principles than a data science model. To break the ice, they need to come up with more of the predictive part of it using machine learning techniques, which can be closed-loop solutions, which can help operators and automation engineers to apply these insights into the units rather than keeping it open-loop.
We face a bit of an issue if there are any server issues or upgrades from Seeq.
The technical support services need improvement.
Regarding AI, I wish Seeq had AI capabilities. For instance, if Seeq could analyze graphs and offer recommendations, it would be advantageous. Currently, there is no AI feature in Seeq. In terms of improvements, it would be great if Seeq could enhance its data export features and possibly integrate more functionalities to reduce the need for multiple software tools. I would like a specific feature related to predictive analysis, which Seeq currently lacks.
As for improvements, I felt there should be a more efficient way to address repetitive customer questions, perhaps using chatbot technology to streamline responses. In terms of functionality, I noticed that certain machine learning methodologies, like Principal Component Analysis (PCA), were missing from the Workbench. While it was possible to perform these analyses in DataLab, adding such features to Workbench would enhance user experience and allow for more complex calculations without needing to switch environments.
Seeq is evolving. We only included time series analysis in the first version. Going forward, we introduced many complex Seeq tables. You give the temperature and pressure, and the solution will give you the enthalpy of steam. It would be wonderful if a time series model could be built with the thermodynamic package. We have Aspen Hysys for thermodynamic package dissimulation. When we interpret both, it will be magical.
They have many features addressing various issues. For example, something I developed plots the gains in a prediction model, which could be a built-in capability in Seeq. Artificial intelligence support exists for the Datalab environment. The advanced functionality requires some training.
Seeq Organizer, which is used for dashboarding, has some limitations. In Seeq Organizer, we've realized that process engineers want dashboards with more drag-and-drop features, like Power BI. Seeq has limitations in terms of the variety of widgets and visualizations you can use. You're limited to a few types like line charts, bar charts, and pie charts (which was introduced recently). Power BI offers a wider range of dashboarding options. It's not that Seeq is solely a dashboarding tool; it can connect to Power BI and Tableau. But customers who purchase Seeq and expect its dashboarding feature to be competitive with Power BI and Grafana might be disappointed. So, dashboarding is where I see a lot of room for improvement in Seeq.
The analytical part is fine. We can do our analysis. But the dashboard, where we approve the dashboard, is not ideal for someone who uses Seeq only as a tool to see data in a report format. Seeq Workbench, Seeq Organizer, and Seeq Data Lab are great platforms where we do our analysis, but if they could add features to Seeq Organizer for publishing reports, that would be helpful. Currently, there are many tools on the market that provide aesthetic dashboards, like Power BI or Tableau. These tools make it easy to create reports that are understandable even for those who don't know anything about the data. So, Seeq could work on the reporting format, but the analytical tool is excellent.
I have noticed that Seeq sometimes struggles with connectivity issues, leading to data gaps. This is an area that needs improvement. While connecting to data, sometimes, due to connection loss or issues with the tool itself, the tags may not display any trends, resulting in missing information.