The setup process could definitely be better. In terms of features, I'm happy with where I am at the moment. They bring in their own updates, and I'm happy with the updates that they are bringing. Their updates used to be bad, but they had a recent update, and after the update, it is really good.
Head of RPA COE at a transportation company with 10,001+ employees
Real User
Feb 18, 2021
They are still new in the market. Or, at least, they are still a small player. They require a lot of improvement in terms of learning material as well as the community developers. If you compare Jiffy.ai to an established solution, like UiPath, you can go to YouTube and find a lot of learning material posted by UiPath, partners, and other people in the community. However, for Jiffy.ai, you won't find that available in the market. Because of this it is very hard for us to find talent in the market. Most of the developers in the market are used to the bigger players. For Jiffy.ai, if you search a resume because you are trying to find someone who has used Jiffy.ai, you won't be able to find it. So, when we onboard a new person, we want them to learn this new system, but it is a bit hard for them to pick up because there are no external learning materials on the Internet. For training, they provide the foundation and advanced training. If you have other issues, they have a support portal, which shows a brief summary of the features. It's not very extensive, like Google Cloud Platform. Sometimes there are things that may not be available in the portal. While other products will also not have available the information in their portal, other people know it. So, you don't have in the community discussions about solutions to a problem that would not be available in the portal.
Managing Director, Business Transformation at a transportation company with 10,001+ employees
Real User
Jan 26, 2021
It has gotten better over time, but some of the training and product documentation could be better. I believe this is also being addressed, but a lot of the platform work, as we were putting in new versions or making some updates, was, ironically, very manual. It's improved greatly, but I would imagine that's an area that they're probably still working on, on the backend, to help when it comes to what we need to do for platform support.
Digital Project Manager at a aerospace/defense firm with 501-1,000 employees
Real User
Jan 26, 2021
The UI or the UX has room for improvement. The approach for designing the workflow is not that straightforward. It's quite difficult. Also, when it comes to a Knowledge Base or training, there aren't many resources online that developers can refer to, unlike the competitors. There's no forum and there aren't too many YouTube videos or that sort of thing. There is also no free trial.
National Professional Officer at a international affairs institute with 5,001-10,000 employees
Real User
Jan 14, 2021
They are doing part of the automation process, but it is not entirely end-to-end. They are filling in the gaps for us, and from an end-to-end perspective, they fulfill part of it. They breakup about 25 percent, then 75 percent is actually work done by the staff. However, for the 25 percent that is required, this is actually very time-consuming, especially now during the pandemic. Forwarding documents from home is a pain, as it depends on individual staff and their Internet connection as well as the performance of their ISP. So, we have to take that into account. I have a background in IT and I have an understanding of how the RPA system works. If I am programming this, I know it will be a hassle. It is mostly graphical, then something that you just need to type. As long as you know where to press and what to do as well as have some basic programming skills, it is quite easy. The solution has just not closed the gap of being accessible to non-IT users. If you are a non-IT person, then this all looks like gobbledygook. Maybe that is something that can be improved upon.
Initially, in version 3, Jiffy.ai did not have support for containerization. In our environment, we are heavy users of containers and container illustrators. So, the initial deployment option was running based on individual hosts that we deployed in the cloud. That created a singularity in the way that we deployed services in our system. However, in the latest version release (4), they have full support for containerization. This has been a great improvement and one of the driving factors for switching from version 3 to version 4 very soon. The containerization capability will make a huge difference in our deployment process, because it doesn't create exceptions in the way we would deploy services. All the rest of the system is containers, so if you now have a product from a vendor that doesn't support containerization that means you must have a different process of deploying services, then accompany it with corresponding policies, because we have policies on how systems need to be configured to be reliable, secure, etc. Also, there are the BCDR aspects of it: the disaster recovery and business continuity. So, if you're introducing a new way of deploying services, now you need to have a BCDR plan dedicated to that as well, as opposed to deploying everything using a single model of deployment (mainly containers). Therefore, this will simplify a lot of things, in terms of DevOps.
Founded with the mission to radically change how enterprises automate complex business processes, JIFFY.ai puts the power of real-time innovation in business users’ hands. JIFFY.ai delivers an app-based, cognitive automation platform that includes capabilities ranging from intelligent document processing, natural language processing capabilities, RPA and Low Code/No Code development.
The solution's support services need improvement.
The setup process could definitely be better. In terms of features, I'm happy with where I am at the moment. They bring in their own updates, and I'm happy with the updates that they are bringing. Their updates used to be bad, but they had a recent update, and after the update, it is really good.
They are still new in the market. Or, at least, they are still a small player. They require a lot of improvement in terms of learning material as well as the community developers. If you compare Jiffy.ai to an established solution, like UiPath, you can go to YouTube and find a lot of learning material posted by UiPath, partners, and other people in the community. However, for Jiffy.ai, you won't find that available in the market. Because of this it is very hard for us to find talent in the market. Most of the developers in the market are used to the bigger players. For Jiffy.ai, if you search a resume because you are trying to find someone who has used Jiffy.ai, you won't be able to find it. So, when we onboard a new person, we want them to learn this new system, but it is a bit hard for them to pick up because there are no external learning materials on the Internet. For training, they provide the foundation and advanced training. If you have other issues, they have a support portal, which shows a brief summary of the features. It's not very extensive, like Google Cloud Platform. Sometimes there are things that may not be available in the portal. While other products will also not have available the information in their portal, other people know it. So, you don't have in the community discussions about solutions to a problem that would not be available in the portal.
In Jiffy.ai, they should add more customization, depending on the plugins available in the system.
It has gotten better over time, but some of the training and product documentation could be better. I believe this is also being addressed, but a lot of the platform work, as we were putting in new versions or making some updates, was, ironically, very manual. It's improved greatly, but I would imagine that's an area that they're probably still working on, on the backend, to help when it comes to what we need to do for platform support.
The UI or the UX has room for improvement. The approach for designing the workflow is not that straightforward. It's quite difficult. Also, when it comes to a Knowledge Base or training, there aren't many resources online that developers can refer to, unlike the competitors. There's no forum and there aren't too many YouTube videos or that sort of thing. There is also no free trial.
They are doing part of the automation process, but it is not entirely end-to-end. They are filling in the gaps for us, and from an end-to-end perspective, they fulfill part of it. They breakup about 25 percent, then 75 percent is actually work done by the staff. However, for the 25 percent that is required, this is actually very time-consuming, especially now during the pandemic. Forwarding documents from home is a pain, as it depends on individual staff and their Internet connection as well as the performance of their ISP. So, we have to take that into account. I have a background in IT and I have an understanding of how the RPA system works. If I am programming this, I know it will be a hassle. It is mostly graphical, then something that you just need to type. As long as you know where to press and what to do as well as have some basic programming skills, it is quite easy. The solution has just not closed the gap of being accessible to non-IT users. If you are a non-IT person, then this all looks like gobbledygook. Maybe that is something that can be improved upon.
Initially, in version 3, Jiffy.ai did not have support for containerization. In our environment, we are heavy users of containers and container illustrators. So, the initial deployment option was running based on individual hosts that we deployed in the cloud. That created a singularity in the way that we deployed services in our system. However, in the latest version release (4), they have full support for containerization. This has been a great improvement and one of the driving factors for switching from version 3 to version 4 very soon. The containerization capability will make a huge difference in our deployment process, because it doesn't create exceptions in the way we would deploy services. All the rest of the system is containers, so if you now have a product from a vendor that doesn't support containerization that means you must have a different process of deploying services, then accompany it with corresponding policies, because we have policies on how systems need to be configured to be reliable, secure, etc. Also, there are the BCDR aspects of it: the disaster recovery and business continuity. So, if you're introducing a new way of deploying services, now you need to have a BCDR plan dedicated to that as well, as opposed to deploying everything using a single model of deployment (mainly containers). Therefore, this will simplify a lot of things, in terms of DevOps.