WorkFusion Reviews

I started with invoice processing. That uses a lot of different parts of the WorkFusion solution. It uses their built-in OCR package, built-in S3 instance, and built-in databases. Invoice processing is the big use case. 

We use their AutoML tagging machine learning use cases. Then, at the end, we use their true robotic process automation, using the SeleniumLibrary, to enter things into our ERP system.

I have used it for a couple of other projects. I have done this mostly because WorkFusion makes it easy to code out a straightforward business process, put it on a schedule, and hook it up to a database without needing to requisition all new things and servers to launch it. I can host it in one central spot.

Our particular instance is on-prem. It has five or six different Linux servers that all talk to each other as well as a handful of Windows machines that end up talking to the central Linux boxes. In my time here, we have had two different major versions of WorkFusion: 8.5 and 9.2. We are currently on version 9.2.

The workflow automation has definitely been helpful. It gives us an interface to launch code on one site, then have it run in parallel one to ten times on ten different robots. They can do the same process ten times in parallel on a website. 

We have entire workflows predicated off of the document processing engine. Our whole invoice ingestion process runs 50,000 documents a year, give or take, completely predicated on WorkFusion's document workflows.

We receive invoices from 50 to 100 different vendors. They all have different formats. The document processing engine (coupled with their AutoML services, data extraction, and human tagging) is able to translate these 50 different formats into a single output that we can then pass downstream into whatever process needs to receive it. So, this has been a helpful integration.

We have automated a lot of finance workflows using WorkFusion. This definitely helps both our accounts payable and accounts receivable teams.

Currently, we use WorkFusion for its OCR and automation capabilities to extract key pieces of information from legal entity documents submitted during client onboarding. This information, which relates to individuals who have the authority to control, own, or transact on behalf of the client entity, is then compared to the information in our system of record to ensure a match.

We have 75 different processes, and the AI robots are a critical part of the two processes we have deployed them in for the duration of those processes.

AI robots process data extremely quickly. From a precision perspective, they can achieve high accuracy, but we need to continue training their models to improve further.

AI robots increased efficiency in our organization by 15 percent for one process and 40 percent for the other.

AI robots helped us scale our organization through the reduction in annualized manual handling time. WorkFusion has allowed us to continue to grow the business by ten percent without having to add to our headcount.

The document processing engine is able to digest our primary documents and extract needed pieces of information depending on the use case we provide. This is extremely important for the processes that WorkFusion implemented.

We only process unstructured documents, and we have a good success rate with them. WorkFusion's out-of-the-box models for unstructured documents are the reason we chose them over others.

WorkFusion has helped improve our organization. One of our digital workers allows us to actually speed up review times for our analysts. Historically, they reviewed every single legal document that was submitted, page by page, and did that comparison. We've been able to speed up that process, which has resulted in an efficiency gain. Additionally, the digital worker has added a level of control and consistency to the process by ensuring that all analysts follow the same exact procedures and guidelines, regardless of who they are.

It has helped us improve our accuracy and compliance, resulting in reduced manual handling time. Specifically, WorkFusion has allowed the team to review 15 percent more documents daily, equivalent to a year's worth of growth for our business.

WorkFusion's flexibility helps our organization achieve its evolving goals. We've had a great experience working with WorkFusion over the past two years. They've been able to add functionality and features to their product that align with our processes or make common sense. Most of these requests have been added to their product roadmap and deployed.

We use WorkFusion for SPA, Smart Process Automation. SPA combines robotic process automation and machine learning. The heart of it is machine learning. The RPA processes are a few steps that a robot does instead of outsourcing to a human in India. It makes the process more efficient to execute any exceptions on the WorkFusion cloud.

It's a SaaS solution, so everything goes over the cloud. Only the results are delivered locally on-premises. We're using it for machine learning purposes to extract data. However, the process is not entirely straightforward and sometimes we need manual intervention by our third-party ops provider in India and Poland.

We have between 20 to 40 bots that work in our production environment. They do the work in the background, so we don't see what they do, but they handle the workload. We also have approximately 20 employees in India that for whenever a bot has a question or has an issue. Then a human being needs to look after that. This gets done by our colleagues in India based on training. We define the gold data to be specified in each document we want to have extracted. We also have very detailed instructions on what has to be done if something happens that is not as expected.

We work directly with WorkFusion. We also work with a back-office services provider and they do the manual exception handling. Whenever something isn't automatically extracted, it appears in the cloud. An employee of our service provider in India or Poland handles the manual extraction based on the detailed instructions. We get the results and import them into our target systems.

WorkFusion has doubled our efficiency. We replace manual processes with automated ones. We need half as many people to process the same amount of work, or we can process double the amount of work with the same people. It's a mix of both because the volume has increased a lot. 

We would have some issues meeting our obligations to our clients without WorkFusion. We expected the volumes to increase, but they coincidentally spiked as we introduced WorkFusion. That was an immense help because we would've had trouble serving our clients if we didn't have this capacity gain.

The document processing engine is essential because that's where we gain speed. We're processing a massive volume of documents with the document processing engine and automatically extracting around 80 percent of the information, enabling us to honor our clients' SLAs. We can distribute the information 24 hours after having received it. This is an SLA that we have with the clients, and that document processing engine helps us keep those timelines because it's a lot faster than if someone had to look it over manually.

Adopting WorkFusion has improved our accuracy, but not significantly. We have fewer mistakes overall compared to parallel processes that don't go over WorkFusion. It's around 5 percent better. Compliance isn't an issue because we process publicly available information. It depends on how compliance is interpreted. We would also have more security tasks to go over internally before working with an external provider.

When we implemented WorkFusion, it was quite popular within our company. I got to do a lot of demos for different companies. It was good because it showed people what was possible and inspired ideas about new use cases. I'm currently also working with all kinds of different use cases. In terms of creativity and generating ideas, WorkFusion was good. 

We're also able to automate internal processes because WorkFusion also can deliver different outputs that are more flexible for us to work with internally. So we're also able to have more efficient internal processes thanks to WorkFusion.

We use WorkFusion to develop business processes and deploy them as automation solutions. It serves as the orchestrator for these processes. Some processes were initially manual, but we have automated them sequentially using WorkFusion.

I find the capabilities that a normal orchestrator should have to be valuable in WorkFusion. The WorkFusion 10 cloud-based platform is different from the earlier on-prem version, WorkFusion 9. The platform now includes auto machine learning and AI capabilities. We haven't used these extensively, but they are a nice feature they are working on. The platform remains stable with well-designed processes, despite being a complex and technical tool.

Most of our use cases are for internal operations. We have automated use cases related to 10-plus departments. Most of our use cases are using the robotic process automation capabilities of WorkFusion. Only one use case is through the machine learning capability. Then, there are a lot of use cases that have optical character recognition (OCR) in them.

WorkFusion helps us in automating our business processes, so it helps in many ways, including lowering the cost of delivery. It helps us by either avoiding external costs or by reducing the cost of operations by employing fewer people. Secondly, WorkFusion helps by speeding up processes. The process takes time. It has business costs associated because there are people waiting to take the next steps in the process. The end result of waiting, whether it is an internal or external team, is that they are delayed. Therefore, it helps us in speeding up business processes and improving employee morale, as people don't have to do repetitive work anymore. 

Because WorkFusion is consistent, it creates repeatability in our processes. My team is the automation team so we are the ones who assess the processes and deliver them. For our partner teams, whose processes are automated, it helps by giving them back the capacity and a little more peace of mind that things are working.

Within my company, I am responsible for a line of business where we roll out automations for various internal stakeholders, and WorkFusion is the platform of choice within my organization.

Approximately 90% of our use cases are RPA-governed use cases. We have one use case now that is a machine learning (ML) based use case. While we are not adverse to using ML within WorkFusion, we are still in the process of identifying or exploring the right use cases within the organization that are the best fit for ML.

A helpful feature is the analytics capability within WorkFusion. The analytics dashboards, i.e., their Tableau dashboards, are really helpful for building a business activity monitoring layer. These are very visible to senior management and stakeholders, who can see and know what is happening within processes. They can see what benefits are getting delivered as processes, either ;daily, weekly, monthly, or quarterly. It is easy for stakeholders or senior management to understand the value for the money that they are spending.

The solution has ELK Stack with Kibana, which is useful and helpful for monitoring all of WorkFusion's infrastructures. This has been really helpful, even though we have just started using it very recently. Previously, if there was an issue, we would log into each of the servers separately and try to fix it. We were introduced to ELK stack two weeks ago, though it has always existed in the product. It has been really amazing. If there are failures, we immediately get notifications. We have been able to integrate it with our enterprise alerting system that creates tickets automatically, which is amazing. We don't have to spend and dedicate hours just to look into the infrastructure to see if there has been a failure or not. We can be reactive instead. 

WorkFusion definitely has a very strong capability to process any document using OCR and machine learning frameworks, particularly from an extraction perspective. We have just used this, deploying one use case using these capabilities. We have been happy with the results. We are getting almost an 80% automation rate. Based on this success, we have started exploring other opportunities within my organization to see if there are other use cases that best fits this AI paradigm.

It is related to order entry and customs processing. At a high level, it is automatically reading from emails, processing attachments, OCR, and machine learning.

We use it for our important use cases. We are a transportation company. We take orders, then we fulfill those orders. So, if we do not take the orders, then we have nothing to work on.

We also do cross-border freight. We move freight from the US to Canada and Canada to the US. We need government clearance before we can move the freight. For that, WorkFusion is also important.

It is on the cloud utilizing AWS. We are working on changing it to the SaaS model from this year onwards.

It takes care of simple tasks so users can focus more on exceptions than on regular use cases. They only focus on orders where they need to handle an exception, some information was not given, or there is an issue that they had to focus on. The rest of it goes straight through without human touch. We want to see our employees as engineers, wherein they think and solve problems, not necessarily have to do repetitive tasks. I think WorkFusion helps with avoiding repetitive tasks.

We have a retry queue. Therefore, if some information is not correct the first time, then you put it in the retry queue, the users can correct any mistakes. So, it has certainly helped with accuracy. From a capacity and scaling perspective, it has also helped by taking away our repetitive tasks. It is helpful in that sense.

I primarily use WorkFusion for RPA, specifically the ODF framework, mainly using Java, even though it is somewhat deprecated. I automate tasks like transferring data from websites to services. The WorkFusion infrastructure supports my RPA bots. I also use it for machine learning models that recognize invoices.

It is useful that WorkFusion provides the entire infrastructure, which allows me to focus on writing code without worrying about maintenance. Even without DevOps, I can rely on WorkFusion's support for solving issues. They provide an inbuilt Selenium framework and infrastructure that eases my workload, allowing me to write Java code and embed it within Groovy classes.