Why is it Worth Adopting AI in Documents Processing?
There are several reasons why adopting AI in document processing brings significant benefits:
- Improved efficiency and productivity: AI can automate various repetitive human tasks, such as data extraction, document classification, reviewing documents, significantly reducing errors related to manual data entry.
- Enhanced decision-making processes: AI systems can quickly analyze, extract, and synthesize data from documents, systems, knowledge bases to improve decision-making processes. This helps to answer any questions about the data and improve decision-making.
- Cost savings: Reducing time spent on repetitive tasks that do not require human attention.
- Improved customer experience: Faster processes have a positive impact on the customer perception of a financial institution.
- Scalability: AI-powered solutions are designed to handle large volumes of documents, even if those volumes grow over time.
- Easy integration: AI document processing systems can be seamlessly integrated with data handling solutions like DPA (digital process automation) or BPM (business processes management) systems serving different processes.
Key Features of AI Based Automated Document Processing Systems
Modern automated document processing systems take advantage of LLMs to streamline the handling of different types of documents within an organization. Below you can find some key features of such solutions:
Document classification
Categorization of documents based on their content into predefined categories
Data extraction
Extracting relevant data from a particular type of document, including unstructured documents
Data validation and verification
Automatic validation and verification of the extracted data against a defined list of data required for a particular type of document (validate whether the data are present and then verify their correctness).
Integration with existing systems and workflows
Providing extracted data and integrating with other enterprise systems like workflows, CRM, data platforms, etc.
Scalability
Automated document processing systems should be scalable to handle growing volumes of documents
Serving unstructured documents
Ailleron’s LLM-based document processing systems are capabale to handle unstructured types of documents
Document tagging
Assigning a set of tags or descriptions to documents
Automatic document summary
Preparation of a short summary containing key information for a particular type of viewer
Let’s talk about how we can help your organization make the most of AI Document Processing!
Michał Walerowski
Business Unit Director AI/ML & Data Solutions