Staff Augmentation

Consider a financial services firm aiming to automate its mortgage approval process. The internal IT team has some RPA familiarity but lacks expertise in automating intricate document processing. To address this, the firm hires RPA developers with document processing skills. These external developers work closely with the internal team to create an advanced bot. This bot extracts and processes data from mortgage applications, cutting processing time and errors.
                    
            Managed Services

A retail corporation has effectively integrated RPA bots to oversee inventory levels and enhance order processing efficiency. Despite the accomplishment, the company's IT department is facing resource constraints and aims to guarantee uninterrupted bot operations. To address this, they decided to engage a managed services provider that takes a proactive approach to monitoring the bots, addressing any arising issues, and optimizing the automation processes. This strategic move enables the retail company's IT team to concentrate on pivotal initiatives, while the managed services provider ensures the continuous smooth functioning of RPA operations.

                  

                    Time and Material

 

An insurance firm wants to automate claims processing with RPA. Since the project's exact scope and complexity aren't fully clear at the start, they go for a time and material arrangement with an RPA provider. The provider's team works on the project, and the insurance firm pays for hours worked and software licenses used. As the project advances, the firm realizes more document processing features are needed, and they can easily adjust the project's scope and budget within the time and material framework.

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Robotic Process Automation (RPA) is a technology that uses software robots (or "bots") to automate repetitive, rule-based tasks within business processes, allowing organizations to improve efficiency and reduce human intervention. RPA bots mimic human actions on computer systems, performing tasks such as data entry, data extraction, and process orchestration with precision and speed.


Intelligent Document Processing (IDP) is a technology that combines artificial intelligence and automation to extract valuable data and insights from unstructured documents such as invoices, contracts, and forms. IDP systems use machine learning algorithms to comprehend and process documents, enabling organizations to streamline data extraction, improve accuracy, and make more informed decisions.


Process mining and discovery is a data-driven approach to analyze, visualize, and understand how business processes actually operate within an organization. It leverages event logs and algorithms to provide insights into process performance, bottlenecks, and variations, helping organizations optimize their processes for efficiency and effectiveness.