Scenario: Typed Insurance claim PDF document is submitted to the system. The intention is to extract the details, validate the data against internal systems and approve or reject the claim based on set criteria and evaluation.
In this scenario, a typical human task will be to extract data, feed the data and either make deciosion or pass it on to the decision making team. Some might have OCR tools for data extraction.
In this case if IQBot is deployed, the bot can extract the data, feed the data into systems, make decisions and communicate to the customer.
Where does intelligence play a role?
When the data extraction happens there could be some nuances that you can teach to the bot. For example, when the OCR engine extracts the date field from the PDF document and you notice there is a space betweeh the delimiters. In this case, a human intervention can come in during the learning instance to remove the space. Once this is done, everytime a space is extracted in the field will be removed automatically. Like this there are many other intelligent features that could ease the work for human teams.
Hope you are able to relate the scenario for IQBot.
Search for a product comparison in Robotic Process Automation (RPA)
Best for: Repetitive, rules-based tasks that rely on structured data
At the core of automation are Task Bots. These bots automate rules-based, repetitive tasks, in areas like document administration - e.g. HR, claims management, procure-to-pay, quote-to-cash, IT services, and more, leading to immediate improvements in productivity, cost-savings, and error reduction.
Metabots
Facilitating scalability with next-generation integration
Best for: Complex, scalable processes
Meta Bots are automation building blocks that help you scale. They are “app resilient,” meaning that any time an application updates or changes, you make minimal edits to the bot itself, and those changes then automatically apply to any process utilizing that bot. Low maintenance and easy to use, Meta Bots help increase RPA adoption, reduce downtime, and ensure control over complex, enterprise-wide automation.
What are IQ bots
Continuously learning and enhancing process automation
Best for: Managing through fuzzy rules and processing unstructured data...
Merging unique cognitive capabilities with RPA, IQ Bots can understand structured or unstructured data with ease, act based on the information and learn in real-time, making it possible to fully automate processes and run them independently.
An IQ Bot relies on supervised learning, meaning that every human interaction makes IQ Bot smarter.
What is RPA? Robotic process automation (RPA) is a software technology that enables enterprises to build, deploy, and manage a virtual workforce made up of software robots (“bots”) that emulate the actions of humans in interactions with software and digital systems.
I would like to add a simple example for IQBot.
Scenario: Typed Insurance claim PDF document is submitted to the system. The intention is to extract the details, validate the data against internal systems and approve or reject the claim based on set criteria and evaluation.
In this scenario, a typical human task will be to extract data, feed the data and either make deciosion or pass it on to the decision making team. Some might have OCR tools for data extraction.
In this case if IQBot is deployed, the bot can extract the data, feed the data into systems, make decisions and communicate to the customer.
Where does intelligence play a role?
When the data extraction happens there could be some nuances that you can teach to the bot. For example, when the OCR engine extracts the date field from the PDF document and you notice there is a space betweeh the delimiters. In this case, a human intervention can come in during the learning instance to remove the space. Once this is done, everytime a space is extracted in the field will be removed automatically. Like this there are many other intelligent features that could ease the work for human teams.
Hope you are able to relate the scenario for IQBot.
Hi @Evgeny Belenky ,
The basic difference is mentioned below.
TaskBots
Front-end automation
Best for: Repetitive, rules-based tasks that rely on structured data
At the core of automation are Task Bots. These bots automate rules-based, repetitive tasks, in areas like document administration - e.g. HR, claims management, procure-to-pay, quote-to-cash, IT services, and more, leading to immediate improvements in productivity, cost-savings, and error reduction.
Metabots
Facilitating scalability with next-generation integration
Best for: Complex, scalable processes
Meta Bots are automation building blocks that help you scale. They are “app resilient,” meaning that any time an application updates or changes, you make minimal edits to the bot itself, and those changes then automatically apply to any process utilizing that bot. Low maintenance and easy to use, Meta Bots help increase RPA adoption, reduce downtime, and ensure control over complex, enterprise-wide automation.
What are IQ bots
Continuously learning and enhancing process automation
Best for: Managing through fuzzy rules and processing unstructured data...
Merging unique cognitive capabilities with RPA, IQ Bots can understand structured or unstructured data with ease, act based on the information and learn in real-time, making it possible to fully automate processes and run them independently.
An IQ Bot relies on supervised learning, meaning that every human interaction makes IQ Bot smarter.
@Celestine, @Biswajit Mohanty and @Okay Akdeniz, can you please assist and share your knowledge?
Thanks for the help!