I would give the product an overall rating of seven and a half out of 10 because it has a lot of functionality, whatever we use. The extraction process for still and noisy documents and some data is good. The need for manual intervention is minimal. A few things could be improved. Not having to do QA would increase accuracy. We also must create different user data types if a particular data type is missing. We currently have15 people using the product all the time. It can only be a cloud-based program because it requires more GV whenever we install HyperScience pieces of more than around 250. So we have to install the relevant cloud servers and gain access using their URL. If you are a first-time user, you must show what kind of documents you have. You also need to estimate how many documents you will require each month. Next, you must decide whether structured or non-structured documents would better meet your needs. Based on your decision, you create the appropriate document, considering t which fields are required and which are not. You can then estimate the number of manual tasks that might be required. It's a good extraction solution if you're looking for an IQ Bot and ARN documents. So. if it's a typed document, it's fine, but whenever you're looking at something handwritten or a still or noisy document, you have to go to HyperScience.
Head of AI and Automation at a insurance company with 5,001-10,000 employees
Real User
2022-07-14T12:11:00Z
Jul 14, 2022
We are a customer. We're just upgrading to version five. I don't remember the exact version we are on right now. If accuracy and customer satisfaction are your goals, then you should go for this solution. It's really a fantastic product in the market. We have seen other products doing stuff. They weren't good at all. They all claim to be excellent, yet they weren't. I’d rate the solution eight out of ten.
Lead Analyst at a financial services firm with 1,001-5,000 employees
Real User
2022-03-23T16:48:18Z
Mar 23, 2022
Whenever someone is looking forward to using HyperScience or any of the IDP tools, I would recommend them to take a look at what their own use cases are, what kind of forms they have, and what documents extractions that they need. They then can map it with the functionality that HyperScience or similar tools have to offer and see what is best compatible for their use case. HyperScience will be good at a lot of operations, but those operations might not be well-suited for your needs. it is best to look around at the options available on the market. I rate HyperScience an eight out of ten. My rating might be a bit biased because of my lack of experience with the solution. I may not be able to gauge the overall performance and capability that the entire solution has to offer. I may have only been exposed to a limited amount of functions or features.
The biggest lesson I have learned is that we have to configure the maximum number of templates for unstructured documents, and they have given the range that goes from a minimum of ten to a maximum of 400. That makes it a time-consuming job. On a scale from one to ten, I would give HyperScience a seven.
HyperScience is a cloud-based input-to-output platform that automates document-based workflows and extracts data for analysis from both physical and digital documents.
The HyperScience platform simply integrates with your current business systems thanks to an open API, an intuitive UI, and pre-trained models, resulting in a totally automated digital workflow.
The classic scanning paradigm has been reimagined by HyperScience; it has replaced the need for human verification with intelligent...
If it fits your process requirements, you must try it. It would certainly give you a new dimension and better results. I would rate it an 8 out of 10.
I would give the product an overall rating of seven and a half out of 10 because it has a lot of functionality, whatever we use. The extraction process for still and noisy documents and some data is good. The need for manual intervention is minimal. A few things could be improved. Not having to do QA would increase accuracy. We also must create different user data types if a particular data type is missing. We currently have15 people using the product all the time. It can only be a cloud-based program because it requires more GV whenever we install HyperScience pieces of more than around 250. So we have to install the relevant cloud servers and gain access using their URL. If you are a first-time user, you must show what kind of documents you have. You also need to estimate how many documents you will require each month. Next, you must decide whether structured or non-structured documents would better meet your needs. Based on your decision, you create the appropriate document, considering t which fields are required and which are not. You can then estimate the number of manual tasks that might be required. It's a good extraction solution if you're looking for an IQ Bot and ARN documents. So. if it's a typed document, it's fine, but whenever you're looking at something handwritten or a still or noisy document, you have to go to HyperScience.
We are a customer. We're just upgrading to version five. I don't remember the exact version we are on right now. If accuracy and customer satisfaction are your goals, then you should go for this solution. It's really a fantastic product in the market. We have seen other products doing stuff. They weren't good at all. They all claim to be excellent, yet they weren't. I’d rate the solution eight out of ten.
Whenever someone is looking forward to using HyperScience or any of the IDP tools, I would recommend them to take a look at what their own use cases are, what kind of forms they have, and what documents extractions that they need. They then can map it with the functionality that HyperScience or similar tools have to offer and see what is best compatible for their use case. HyperScience will be good at a lot of operations, but those operations might not be well-suited for your needs. it is best to look around at the options available on the market. I rate HyperScience an eight out of ten. My rating might be a bit biased because of my lack of experience with the solution. I may not be able to gauge the overall performance and capability that the entire solution has to offer. I may have only been exposed to a limited amount of functions or features.
The biggest lesson I have learned is that we have to configure the maximum number of templates for unstructured documents, and they have given the range that goes from a minimum of ten to a maximum of 400. That makes it a time-consuming job. On a scale from one to ten, I would give HyperScience a seven.