Revvity Signals Notebook

We have been using Revvity Signals Notebook for developing the scientific templates, different ADTs, then automating workflows using Signals with Trovivo. We have also used Inventa, and Signals Inventa for Data Factory. On top of that, we have developed our own frameworks using Python, which will be using Signals API for integration and through different third-party applications. Suppose you have DLC or any other third-party integration applications, which we can leverage using Signals APIs, and then we have done the integration. We have created some of our own frameworks, such as MetCona. MetCon is a Python-based framework we have developed, and we have done the automation, which cannot be done with VitroVivo.

Regarding the functionality part of Revvity Signals Notebook, they have all the functionality. For sample management, the functionality is now available. The only thing is that if a client has their own sample management tool, can it be seamlessly integrated? Those kinds of connectors or integrators are not available as an out-of-the-box feature. For that, you have to utilize a custom-built script with the help of APIs or an external list. Otherwise, we don't have any direct way of integrating them.

For functionality in Revvity Signals Notebook, obviously, one valuable feature is the API support they have. They have good, extensive API support. If you want to custom build any application, meaning an integration application or you want to create a data pipeline using those APIs, you can leverage and integrate that. That is one good thing they have. Another thing is the speed because clients go for Revvity Signals for that reason. With the speed of loading your templates, configuring your scientific parameters in different ADTs, the user interface is quite good. It loads quickly and doesn't show any lag in terms of loading the applications. They are adding a lot of new features in ADTs. Earlier, we had only the concept of admin-defined tables, which is ADT, but now they have added variant tables and hierarchy tables. They have added the concept of pulling materials from the material table into these ADTs, the hierarchical table, or variant tables. You can do all those things, and they are adding new functions within these different types of tables. Small calculations, which we used to go for VitroVivo for, can now be done at the ADT level as well. They have made a lot of changes at their ChemDraw side as well. The way you will be trying to search your compounds and molecules can be done quite easily from previous releases. They are still progressing. They have done a lot of fixes from the plate map side. Now, based on CSV, you can upload your plate map data. Earlier, only download was there. Now you can upload it as well. That is going to add a lot of value because I had given this idea a long time back, almost two years back, and now they have added that as a feature.

They have good API support, and that API gives flexibility to integrate with any tools. If you have any application integration tool or data integration tool, you can leverage your API and do the integration with that application or data pipelines.

The collaborative feature of Revvity Signals Notebook was always good. Because of that, people prefer this tool. The ease with which you can do the collaboration means that you have different user groups defined, and one user can share their experiment with another user in a very easy manner. If you can define that a scientist will be doing an experiment, then he wants to do a review, and then he can send it for review. Or if somebody has to do a sign-off, meaning signing and closing of the experiment, that can also be done. You can define different roles and accordingly set what are the different layers of the approval life cycle. You can share an experiment from one group to another group or within the group. You can define roles as well. It depends on how well you are planning from the system admin side, where you are setting up your policies, such as how your experiment will flow. If some experiment should be a GXP experiment that should not be exposed, you have to define a policy according to that. You have to define your experiment properties and based on the properties, set your policies. That is how it works. It is a matter of how well you are planning, and that will make your system more collaborative with all security and compliance aspects in consideration.

Regarding security in Revvity Signals Notebook, it is there. Everything is secured based on the policy, the way we are defining it at the admin level. That is one thing. And another thing is obviously the authentication and authorization, how you are doing that, and how you are defining your system user groups. Security-wise, it is there. All the necessary features are there.

In the product, they have started taking the right direction with Revvity Signals Notebook. They have added in-vitro analysis. That is, within Signals Notebook, you can define your experimental workflow steps. However, that is not very customizable. They have started adding those automation steps within in-vitro analysis. If you have a simple workflow, you can automate that within Signals Notebook itself using in-vitro analysis objects. You don't have to go to VitroVivo; you don't have to depend on Spotfire skill because VitroVivo requires your Spotfire skills. They can mature it because they have now started adding different plottings, such as P3 and P4 kind of plotting and curve fitting plotting. However, it is still at a very early stage. They can work on that area to mature their in-vitro analysis, to showcase all kinds of visualization and make their different steps more customizable. They have been adding more and more features in ADT. They can continue doing that with more and more functionality. For other functionality, they can also do things such as how they can combine multiple ADTs together. If we have to do a joining of two ADTs' data and putting it into other ADTs, or if we have to do a union of ADTs, if they can do it at the Signals Notebook level itself, then it will be quite flexible. Many tasks can be taken care of at the notebook level. You don't have to utilize the Signals Notebook API and then integrate it in your Python-based scripting or any other data pipeline scripting for doing this kind of task. Many things can be done at the notebook level. There are improvement areas in Signals Notebook itself, in the area of ADTs, combining data, and joining data. They can add the filtration as well. Currently, the limit in the ADT is 2,000 rows, so they can increase that limit to 10,000 and more than that. If somebody is joining one ADT to another ADT and then the result is getting saved into an ADT, then this row limitation should not come as a hurdle.

For the stability of Revvity Signals Notebook itself, the rating is 9 out of 10. However, the only demerit of one feature of Signals Notebook is their deployment product. If you have multiple tenants, for example, one for the development area, another is for the QA area, another is for UAT, or then the production area, if you have multiple environments configured, and you want to deploy your experiments templates from one environment to another environment, that is a big pain. They have called it CTT functionality, and that is a very unstable functionality they have. It is one of the worst functionalities in Signals Notebook, that CTT tool they have. However, after getting complaints from the client side, they have started working, but the approach is still not that great. They don't have a seamless deployment application available from one tenant to another tenant. If I have to rate it, for deployment from one environment to another, I would be giving 2 or 3 out of 10.

I have worked more than three years with Revvity Signals Notebook.

For the stability of Revvity Signals Notebook itself, the rating is 9 out of 10. However, the only demerit of one feature of Signals Notebook is their deployment product. If you have multiple tenants, for example, one for the development area, another is for the QA area, another is for UAT, or then the production area, if you have multiple environments configured, and you want to deploy your experiments templates from one environment to another environment, that is a big pain. They have called it CTT functionality, and that is a very unstable functionality they have. It is one of the worst functionalities in Signals Notebook, that CTT tool they have. However, after getting complaints from the client side, they have started working, but the approach is still not that great. They don't have a seamless deployment application available from one tenant to another tenant. If I have to rate it, for deployment from one environment to another, I would be giving 2 or 3 out of 10.

For scalability in Revvity Signals Notebook, it also comes up because you are defining your experiment templates, table templates, and all those things. If you want to maintain the versioning of these templates, currently, Signals Notebook doesn't have a default versioning concept. You cannot maintain the versioning, and you have to come up with your own versioning planning. If you are doing that, you end up adding more numbers of tables, more numbers of experiment templates, and that creates a scalability issue. When it comes to the deployment from one environment to another, their tools miserably fail because it can't handle that many versioned tables and templates together. They have put a lot of limits on areas, such as the number of rows in the ADT; they have defined a limit of 2,000. You cannot add more than 2,000 in one ADT. That scalability side, they have intentionally restricted so that the speed of the application could be very fast. They have to work on that because when a big pharma company is adopting their tool, they need a number of scientists, they will be doing a lot of experimentations, and they will be generating too much data. There should not be a limit by number of rows, a number of tables, or a number of experiment templates. They have to think about how they can make it scalable in an easier way, and the client should not be limited by something.

For technical support, such as vendor support, they have good, quite good support, but sometimes, for things such as deployment tools, or if we were raising any issues or ideas, getting that implemented was taking too much time. For example, the idea which I gave got implemented after two years. Their own development team is on the slower side, and that is why the service or support on critical areas takes time. It is not that they will be supporting you very fast. Initially, they will be collaborating very well. However, when things start, and clients start using it too heavily, and they start identifying some critical issues, getting support in a very timely manner will be a little difficult. It happens that you have to wait for six months or years to get something fixed.

The initial setup for Revvity Signals Notebook is quite simple because it is a SaaS application. Everything is web-based. Earlier, we were supposed to install Spotfire on your local machine, but now they have pretty much sorted that out. Their tenants, since this Revvity Signals research suite has been launched, your VitroVivo configuration can be done through the web only, and the web is quite mature now. Setup-wise, you don't have to do much in your local environment, actually.

The main competitor in the market for Revvity Signals Notebook, a very close competitor is Benchling. Benchling is also quite good. The only thing is that the UI, the ease of use—Benchling is a little on the complex side because you have to do a little more configuration from their end. There also, the visualization, curve fitting plotting, those things are not available in Benchling, and that is why we have gone for the Signals research suite. Benchling is the closest one.

The main benefits I receive from working with Revvity Signals Notebook are based on which tool you are moving to this tool from. That will create a benefit. My client was using legacy-based ELN bios. There, the tool was a desktop application which was taking too much time to load your experiment data. If you were making any small changes, the latency of making those changes would be quite high. Scientists would be spending a lot of time just configuring those experiments, and they wouldn't be doing any useful work, such as their scientific activity. This tool makes things faster, and that is what I said. All the clients are liking this tool because of the speed with which you can configure anything, the simplicity of the UI, as well as the speed with which it saves your data. If you have to collaborate, you can collaborate on your experiments with speed. That speed is the only thing making an X factor to this tool compared to the other tools.

The advanced search functionalities in Revvity Signals Notebook have helped to improve or make efficiency better in locating and managing diverse data formats. For search functionality, they have been adding new components, and they have even added AI-based search capabilities as well. However, we have not exposed the AI-based search capability. We have done the testing but not exposed it. You can do OCR-based search as well. If you have scientific images in your experiment and that has OCR text, and if you enable AI-based search functionality, then a user can put in natural language text and that will be able to pull out those experiments which have that OCR text as well. Those things they have added, and they are adding many of these things, AI-based functionality as well. However, that is still in a very early phase. I will not say that it is very mature as of now, but they are improving in the right direction. My overall rating of the Revvity Signals Notebook is 7 out of 10.

Revvity Signals Notebook  is not applicable to my main use case, as I typically do not use it for any specific purpose in my daily work.

I rate Revvity Signals Notebook  as nine out of ten because it is easy to use, which is why I deduct that one point. My company has a business relationship with this vendor as a distributor and reseller beyond being just a customer.

I have been using Revvity Signals Notebook for around five years.

I do not have any advice to give to others looking into using Revvity Signals Notebook. I do not have any additional thoughts about Revvity Signals Notebook.

My main use case for Revvity Signals Notebook  is as an admin for the company and also as a simple user for the process development of my company, which focuses on chemical process development.

A specific example of how I use Revvity Signals Notebook  in my chemical process development work is that we use it to study the optimization of chemical reactions, and we use the lab notebook to take notes and compile all the data.

I would add that we are now starting to implement artificial intelligence, so we use the lab notebook to compile all the data to feed this artificial intelligence in our company.

The best features Revvity Signals Notebook offers include the significant difference between it and paper notebooks. Now we can get all the data in one single computer from several users. We changed our mindset, and now we can compile all the data from several projects.

This feature has helped my team and made our work easier because we can work in a more efficient manner, and we also save a lot of time because we can use templates for experiment creation, allowing us to avoid repetitive tasks.

Revvity Signals Notebook has positively impacted my organization by allowing us to work together across several sites. My company has two sites in different cities, so now we can work together and compile all the data in one place. We can work on one experiment across different sites of the company.

I am unable to share specific metrics or examples, but I can say that this cross-site collaboration is very useful for us.

If I could suggest improvements for Revvity Signals Notebook, I would implement a technology inside Signals to extract data more easily. I know they have Signals Connect, and they can manage all the data with this platform, but I would like to extract the data to combine these numbers with our database.

I think that covers what I want to add about needed improvements regarding integration with other tools or user interface.

I have been using Revvity Signals Notebook since 2023, and since this year, I am the admin of this platform.

I do not have any complaints about Signals, so I think it is very stable.

I think Revvity Signals Notebook has very good scalability since we will double our license.

The customer support is excellent, as they answer very quickly, so I do not have any complaints about them.

This is the first time I have used this kind of technology. I come from paper notebooks, so for us, it is a very significant step forward.

I think we evaluated different options before choosing Revvity Signals Notebook, but I do not have them in mind.

I am not able to share relevant metrics with us regarding return on investment, such as money saved, time saved, or fewer employees needed.

My experience with pricing, setup cost, and licensing is that they have a very competitive budget.

I trust the Signals support team regarding collaboration and data security, although I am not entirely certain about the security of Revvity.

My advice for others looking into using Revvity Signals Notebook is to clarify how they introduce the data into the notebook, as this is very important.

For now, we are very happy with Revvity Signals Notebook. I give this product a rating of eight out of ten.

Revvity Signals Notebook is dedicated to the pharmaceutical industry, particularly for scientific support, drug discovery, and chemical-related experiments. It allows users to create templates for various experimental purposes and supports enterprise features like policy rules for different user types. As a system configuration engineer, I make these templates for different experimentation purposes for different sets of users. While we primarily use Signals Notebook, there are other products like VitroViewer for workflow execution with experimental data and Inventory for creating Lakehouse solutions. Our group usually uses Signals Notebook, though different teams might use Inventory or other products from the suite.

From my experience over the last fifteen months, the most valuable feature of the Revvity Signals Notebook is its ease of use. Customers appreciate that updating templates is straightforward and everything is automatically saved. The UI is simple, making, creating, sharing, and searching experiments easy. Different scientists can reference each other's experiments seamlessly. It is also swift compared to other vendor-built software, where you have to customize templates and write a lot of code. Revvity Signals Notebook excels in this aspect, making it smooth and efficient.

Revvity Signals Notebook supports compliance within the pharma industry. It meets GXP requirements and security policies, depending on how meticulously you design your environment. Signals Notebook provides audit trails and features for making changes and giving audit details.

The workflow implementation is a pain point for customers because it relies on Spotfire with added plugins, which are not natively integrated. This makes execution slow and less effective in meeting all scientific workflow needs. Additionally, the support service is slow to respond and resolve issues. Even known problems take time due to a lack of a Sstrong developer support team, making it a significant product drawback. They also need to work on other products like Workflow, which still need to achieve these compliance requirements. While Signals Notebook is good enough to meet all the necessary needs, other products like BitLocker still need improvements to become fully compliant enterprise products.

I have been using Revvity Signals Notebook for the past year and a half.

Revvity Signals Notebook is very stable because it was developed from scratch. Many users, almost a hundred thousand in our client environment, use this product, which is stable.

However, other products that are not natively designed and developed by Revvity are unstable. For example, implementing workflows requires a lot of effort from developers to solve minor issues because the product tends to crash. These non-native products are volatile compared to Signals Notebook.

It is a very scalable product.

If you want to use Revvity Signals Notebook for the first time, my advice depends on your purpose. If you need to create templates for scientists to conduct and share experiments and reference others' work, you can definitely use this product. However, if you require complex workflows, data transformations, or integration with your data systems for advanced analytics, Revvity doesn't offer a fully stable product for these needs yet. For such cases, you would need your developers to use Revvity's REST API to expose data to your data lake, which can be costly and resource-intensive. You'll need to evaluate the additional costs and resources required beyond Revvity's product. If you're a small user group needing basic experimentation features, Revvity Signals Notebook is suitable. However, consider the additional value and cost before proceeding for comprehensive use with complex workflows and data integration.

From an end user's perspective, Revvity Signals Notebook is easy to learn. It's tricky for a configuration engineer but not overly complicated. With skilled resources, the learning curve is around three to six months. Overall, it's not more challenging than other SaaS products, making it reasonably easy to use.

I would rate the solution a six out of ten. The reason is that their focus seems to be on just one set of products, neglecting other products. Even though big pharma clients have been consistently pushing and giving them ideas on improving, they don't seem to have enough capacity to address those ideas. Clients are eager for improvements, but Revvity needs to take their feedback seriously and address the issues quickly. They are on a good path but need to put in more effort. Our client has been using their products for more than two years, and if the environment isn't stabilized within that time, they need to rethink their approach. They need to be more dedicated to addressing client needs.