Seeq Reviews

We don't directly use Seeq. If users face issues, like not being able to see data, we help them and provide access. We do those types of support activities.

Since it was onboarded recently, I don't have much knowledge, but I've done basic things like viewing data using the workbench analysis. 

Also, I've worked on adding new data sources, new AF connections, and PI connections. I've also worked on enabling the data sources and their databases.  

It's an easy tool. A beginner can easily learn to use Seeq for the first time. They can complete the training, and once they complete the training, they'll have an idea of how to use Seeq.

Improvement-wise, I think it's okay. Sometimes we face a performance issue in Seeq, like the server load getting increased. That is one of the major issues we've observed recently. 

We work with the Seeq support team to find the cause. We create a performance dashboard to identify why the Seeq cloud load is increasing. We try to work on the cause.

I have nearly one year of experience with Seeq. We onboarded this application recently, about a year ago.

It's used all over the region. Approximately a thousand-plus users use it. Not just a thousand, it will be more. More than a thousand.  

I have experience in PI and AtDoIt. Including that, I've been supporting Seeq for nearly a year.

So, I currently support three applications, one of which is Seeq. 

The initial setup is very easy. I've done installations and upgrades of Seeq in the remote agent service. We have nearly ten remote agent servers based on the business unit. 

Based on the region, we have different, like, nearly ten remote agent servers. I have installed and upgraded Seeq. This activity is very easy. We have an EXE file, and we can run it accordingly. It's the easiest way to install Seeq.

If we need to add new data sources, like if we try to add a new connection to Seeq, then we need to go with the step-by-step process. First, we need to enable the firewall, then establish the connection, then edit the link. There's a step-by-step process we do.

Every three months, we do a Seeq key change activity. This is one of the activities we are performing every three months - the Seeq agent key change.

And since the password should be set to a three-month expiry period in our organization, we do that activity as well. Apart from that, these are the things I currently take care of.

I have knowledge in adding data sources and monitoring the admin page. I check for disconnections and if any occur, I investigate what's wrong with the server.

It's deployed on a private cloud.

It's the easiest way [tool] to view the data. The things that are in PI will be displayed over Seeq. If something's not working in Seeq, first of all, we need to check whether there's anything wrong in PI. 

Most of the issues we face in Seeq, like if the data is not updating or it throws some error, we first need to check the value of the tag that is updating in PI. 

Most of the time, there might be an issue at the PI end. So, based on that, we troubleshoot the issues accordingly.

Overall, I would rate it an eight out of ten. I feel we do have different tools. I don't know specifically what's unique to Seeq, but we have other tools like PI and AtDoIt where we can see the data. We can switch back, extend the dates, and view historical data in other applications as well.

Apart from that, it's the easiest way. We can just pull the tags and go to whichever date we need to view the data. It is a user-friendly tool. Seeq is a good application where we can easily access it.

I've been an administrator for about a year and a half, working on proof of concept reports in pharmaceutical environments. We use the solution for notifications, reviewing information, and alarm details for troubleshooting. I've built reports that help us manage notifications and statuses for equipment. Being able to tie in databases to that information is really beneficial. We can pull in data from our maintenance management system and use the location status for equipment that gets moved around, along with whether they're connected.

I love how easy Seeq is to use and how quickly you can build an analysis. I've worked in the manufacturing industry for over 30 years, setting up data collection systems to record historical data. Usually, we were trending that data, which isn't very valuable. Being able actually to find value in historical data with Seeq has been great. It's quick and easy to set up monitoring and eliminate nuisance alarms. For example, process alarms typically go off mid-batch when adding materials, causing things to go out of spec. This used to create hundreds of nuisance alarms, but the tool reduces it to just the important ones.

Having some prior experience with manufacturing data is helpful, but I think the average user can get up to speed with a quick 25-minute tutorial and start doing useful things in Seeq in less than an hour. I've worked with a lot of software that tries to do similar things, and it's often taken weeks of training. Those tools were hard, and only advanced engineers or data scientists could use them.

I have used the AI capabilities. It's pretty cool and has helped me on several occasions when building reports.

I have been using the product for a year and a half. 

We have encountered minor bugs. 

The solution is SaaS-based, and it scales well. I rate it a ten out of ten. 

I've worked closely with support, who's very responsive to feedback. If we identify things we'd like it to do or something isn't working as expected, they're quick to address it. They often add requested features in future releases. They add new features and improvements about four times a year. They've incorporated several of our requests as new features. They're probably one of the most attentive and responsive companies I've ever worked with regarding software.

The solution is worth its cost. 

The solution's pricing is comparable to other products. 

The tool offers a fast way to understand what's happening and see your data in a way that will bring value to your company. I rate it a nine out of ten. 

I generally use it for time series data analysis. Seeq is famous for doing time series analysis, like statistical process control, quality control, and different types of analyses like regression analysis or correlation relationships. All these different kinds of analysis can be done in Seeq, which is very efficient.

It's an analytical tool, so it supports all the analytical problems. That is the reason we chose Seeq. It generally supports whatever you need, and that is it. We didn't face any challenges while integrating it. 

There are multiple valuable features, and similar things can be done with different tools. But we found Seeq to be very useful because it can be done easily and with less time. 

For example, we can do SPC with Power BI or Excel, but with Seeq, it can be done more easily. Most importantly, we can get real-time value, which is important.

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 been using it for two years. 

I haven't found a lot of bugs, but sometimes it crashes/lags. Very rarely, though. It might be an issue with your internet or CPU load. I don't have that much experience with bugs in Seeq.

The usage depends on different projects and plans. There are more than 10 or 20 people are using it.

The customer service and support are good. They reply within 24 hours. 

We can raise a ticket and ask for help. They will help you. I'm happy with the support. 

Positive

The initial setup and installation of Seeq are very easy because they also help you with the installation. 

I have done a couple of installations and upgrades, and it's not that hard. It's very easy and not time-consuming. 

The first thing is to figure out where your data is coming from, whether it's Snowflake or another source. Then, the integration is completely easy.

My advice/recommendation depends on the kind of problem the user wants to solve. If the problem is to find a reporting tool, there are a lot of tools on the market. It completely depends on the problem the user is going to solve. 

I cannot simply suggest if you should use Seeq or not. First, you have to know what you are using it for and why you are using it.

I would recommend it as an advanced analytics tool for processing different manufacturing data. It's easy to learn to use Seeq, but you need to have some knowledge of analytics or process engineering. Otherwise, with anything you learn, you have to give some time to the software.

Overall, I would rate the solution a seven out of ten. It's a great platform, a very powerful platform to work with. We can add a lot of machine learning stuff and customize the data in Seeq. 

But they need to improve in a few areas, like the reporting part and customizing the dashboard. Seeq can improve those in future upgrades. Currently, there are a lot of powerful tools on the market similar to Seeq.

A use case for Seeq is performance analysis of assets like fans, turbines, and blowers. I have used Seeq for analyzing the performance of turbines or blowers by using the performance indicators and creating those from raw data using Seeq formulas. I then created a dashboard so that we could track asset performance and used it as a dashboard for asset performance management.

The best feature Seeq offers is the ability to compare multiple things together on the same frame, in the same plane of analysis, and in the same view. It provides very good control on the capsules, which are patches representing the anomaly or representing the points of interest, and it has very good control for them. It has very good scalability, meaning if I am making a template for one asset and an industry has multiple fans, multiple blowers, or rotary equipment of the same nature, we can create a dashboard and swap assets, so scaling up Seeq and scaling of analysis is perfect. It provides the feature engineering concept as well through formulas, allowing us to get a lot of things very quickly in Seeq.

Seeq has provided visibility to the key performance indicators and visualization of those critical pointers in our dashboards. It is very good at filtering and sorting the times of interest because it mostly deals with time series analysis, which I found is not present in other data visualization packages available in the market, including Tableau and Power BI. Seeq is very good in industrial data evaluation.

Seeq has provided on-time visualization or real-time monitoring of the anomalies or the deviation, process deviation, and quality deviation, which has definitely initiated timely action to take proactive measures for avoiding the breakdowns and also keeping the quality within the acceptable range within the limiters.

I could see a lot of things can be added, particularly the ease of working in other packages and other process visualization packages like Power BI or Tableau. That ease is not present here in Seeq. I would like to suggest that the data flow within Seeq is actually a bit slower than compared to Tableau Live or other packages, and I think this is an area where Seeq has to get improved.

The ease of working is an issue, as the user interface of Seeq looks a little bit more professional with an industrial look, and it can be made a bit more user-friendly if we compare it to the reliability of other packages like Tableau. I have worked with Tableau for data analysis, and it is also a very good data analysis package, but as a new person, the tools are visible and available when I just want to visualize something. That is not the case with Seeq; Seeq is purely industrial. Being an engineer, I know what to use and how to add things, but if other visualizations or features can be made available in Seeq, it could handle other demographic data or transactional data along with the time series data, which I have not used so far, and I think it is not available with ease compared to other visualization tools in the market.

Seeq is mostly designed with the background of thinking that it is being used by high professional process engineers, statisticians, and others, and the training is not so easy from the user perspective. The formula part is a bit confusing, and sometimes even I face some problems. I am very proficient in Microsoft Excel and using the formula packages in Power BI and other tools, but in Seeq, I find that the things are not exactly working all the time. Sometimes it is a reliability issue, or sometimes it is a bit over-complex, which can be improved in terms of applying and using the formulas so that it supports feature engineering.

Seeq can better be used for identification of anomalies or monitoring the process deviation or quality deviation in real time, and it can also be used as a very good professional data-driven dashboard for creating data-driven dashboards and doing in-depth analysis using extensions such as Python. I have not used the Python or Pandas integrated with Seeq, but I have used Seeq Workbench, which is useful in dashboarding.

Adding users in Seeq administration settings was not difficult or hard, although I have not worked as an administrator. As a user, the usage of Seeq for process analysis is straightforward and is something people are expecting. Seeq provides very good process analysis by separating the tools like the identification tool, quantification tool, filtration tool, and cleaning tool. I think it is good and easy for understanding if a person has a mathematical, analytical, or statistical mindset.

I would advise anyone to give Seeq a try because it has a yearly licensing structure, and its ownership cost is not so high. The only thing which makes any analytical tool, including Seeq, less productive in industry is the context of analysis missing in a number of industries. Even at this time, skepticism and a lot of things make it difficult. I would recommend Seeq for any manufacturing industry to have it for real-time analysis inside their plant.

Regarding Seeq, I definitely caught a very good point that is missing: it should have a training version so that people who are not aware of Seeq can get familiar with it. If it does not win much market share, I think a version for new process engineers or new process analysts is needed. If there is a version which may be available, I am not aware of it, but as far as I know, it is not available in the public domain for trial purposes. If that can be added, I think it will create better familiarity with people, and that familiarity can create market share. My overall rating of Seeq is seven out of ten.

I'm a process engineer in the oil and gas field. I use the solution for daily monitoring, surveillance, and time series analysis, where I can build prediction models and root-cause failure models. We're building a model with Seeq.

Seeq has a lot of beneficial features for process engineers like us. The solution's most valuable feature is the prediction model. We can see the picture only for a particular time if we highlight certain conditions, a certain timeline, or some boundary or threshold.

Suppose you want to do a failure analysis to see what went wrong. We'll give a threshold to parameters, highlighting my parameters, what went wrong, and how it went wrong. I can build a relatively small model or deep analysis to show the parameters or contributors for a failure analysis.

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.

I have been using Seeq for five years.

The solution does not break down, but there will be a delay in buffering or caching if you are caching data for more than ten years. That usually happens due to the size and capacity.

I rate the solution’s stability an eight out of ten.

I'll create a model for one piece of equipment and scale it up to hundreds of pieces of equipment.

I rate the solution a nine out of ten for scalability.

The solution's technical support is very good. Customers have a weekly support call with Seeq. You can also contact Seeq support engineers, who will help you with whatever you need. Also, you can write your doubts on the Seeq forum. Experts or anyone well-versed in Seeq will answer your doubts.

Positive

The solution's initial setup is very simple. You'll have a virtual server either in the cloud or on-premise, and the installation takes just half an hour because it's a web-based application.

Seeq is a tool that does not store any of your data. It will only cache the data and show it on display. Whether it is an on-premise or cloud version, you cannot hamper any data on Seeq security-wise. Just like Google searches for information from the website, Seeq will buffer the information from the historian and display trends or values. The solution does not have much of a data breach or safety issue.

Seeq is not a tool that requires a programming background. It's just a point-and-click tool that is for everyone. The idea behind Seeq is democratizing data analytics for everyone. You don't need to have any rigorous programming knowledge. Instead, basic knowledge of how the tools work is fine.

There is something called Data Lab in Seeq, where an advanced Python algorithm is used to deploy AI and ML models. It has already been developed, but not on a very large scale. We don't know its potential yet. It has the capacity, but no one has explored its maximum potential because we are limited in our use cases. We are exploring it, and it can be deployed for a big-scale project for advanced predictions.

I would recommend the solution to other users. If you want a feature, you can discuss it with the developer team. If it is a useful feature, it will be applied to everyone. They will develop this as a feature, which will be included in the subsequent releases of Seeq. Seeq is evolving by hearing a lot from the audience.

Overall, I rate the solution a nine out of ten.

I am a data architect focused on serial times data, specifically the extract to data of OT to IT. The main use case for Seeq is to evaluate many technologies such as Seeq, Databricks, and SAS Viya. The project and use case were about energy optimization in Peru related to a company called COES, focusing on maximum demand and saving energy for the company.

I proposed to use Seeq because it is easily connected to the AVEVA PI System due to its time series data, making it easier and more flexible to see the data workflow. I have another case where I analyze thermographical images of some energy devices. However, I am unsure if Seeq is the perfect software for image processing, so I tried using YOLO, and then the results are input to Seeq.

The best features of Seeq in my experience include the model that allows you to see the analytics results in real-time, which is the best feature of Seeq for me.

My work with SCADA and PLC in companies requires analyzing the data model quickly. For that reason, I use an API to return the results, and the real-time capability helps make decision-making faster and more accurate.

Another feature of Seeq is that it not only uses time series data but also can work with relational databases and even offline data. Seeq positively impacted my organization by showing the future of many real-time variables of the plant, allowing us to prevent any issues, which is perfect for me since I work in maintenance.

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 have worked for approximately eight years, especially using the AVEVA PI System.

Seeq is stable in my experience.

I am unfamiliar with Seeq's customer support because I only tried to test the software and did not use the support. I cannot rate customer support on a scale of one to ten as I have not used the technical support.

I previously tested AVEVA Analytics for predictive analytics before trying Seeq. I evaluated SAS Viya on-premise alongside other options before choosing Seeq.

The return on investment is complicated to measure, particularly in creating the use case. However, using Seeq makes the effort much easier, and in my opinion, the return on investment is not so far off.

Regarding pricing, I would like to start using Seeq with flexible costs since when you work in analytics, you never fully utilize the maximum potential, and it is possible to gradually increase costs.

When I evaluated the technology, Seeq was my first option.

I chose a rating of ten because I evaluated many characteristics, including its ability to integrate various data structures. The code flexibility impressed me because you can use it more easily within Seeq. I actually use Seeq on-premise, but I know that it does not currently offer on-premise solutions, and I would like to use it in production.

I do not remember how much money I have saved, but I actually use the AVEVA PI System. In that software, I use around one hundred devices, such as motors, and applying Seeq makes integration perfect since I can use just a template to analyze one hundred devices. I recommend Seeq to others looking into using it because it is perfect. Seeq is perfect for me.

My overall review rating for Seeq is ten out of ten.