Document Classification and Indexing Made Easy

 

In today's information-driven world, the ability to efficiently organize and categorize vast amounts of data is paramount. Whether you're a business aiming to streamline your document management processes or an individual seeking to find relevant information quickly, document classification and indexing have emerged as indispensable tools. In this digital age, where documents span various formats and sources, from text files to images, emails to spreadsheets, the challenge of effectively sorting and retrieving information can be daunting.

 

Harnessing the Power of AI 

Document indexing enables organizations to easily retrieve information by associating or tagging documents with different “search” terms. However, manual data entry can be error-prone and time-consuming.

With Archive One AI, the documents are automatically classified which eliminates manual pre-sorting, then locates and reads the information pertaining to the specific document class. The information from the digital document is then extracted automatically and efficiently with Archive One Capture, tagging the documents with different “search” terms. This enables organizations to easily retrieve and classify information with fewer errors, significantly less time, and minimal input from the user than manual indexing.

Archive One does this all very quickly in the background. It then generates an output the user can easily understand eliminating time spent comprehending the document. The user interface is also designed to be as intuitive as possible, eliminating errors and maximizing productivity.  

 

Automatic Document Classification with Archive One AI

 

Manual Document Classification is time-consuming and can be inconsistent. Some companies have their own records information specialists who classify the data, but oftentimes for most companies, the task is done by people within the organization once a document is introduced. This is when problems arise as proper document classification requires planning and more time in executing it. With higher volumes come the added difficulty in properly classifying the documents.

Archive One AI addresses these difficulties through auto-classification. Auto-classification is an automated process in which the contents of a document are scanned and automatically given a tag or label based on examples, keywords, and a classification scheme that was established.

With Machine Learning technology, Archive One AI improves with regular use as it remembers data from every captured document, enhancing the classification accuracy and speed.  Removing this burden from staff not only improves the capture of business data and records but also enables them to easily retrieve documents whenever the need arises. 

 

 

Automatic Document Indexing with Archive One Capture  

Like Automatic Classification, Automatic Document Indexing information saves time and speeds up the process of assigning 'search' terms in a document since the tedious task of indexing would be performed by a machine. 

Other advantages of Automatic Document Indexing are as follows:

• Predictability
• More sophisticated than manual indexing
• Great for similar material
• Less expensive
• It enables users to find information faster and more thoroughly.
• It can be applied to a great number of texts without any hassle.
• Faster, more reliable, and cost-effective compared to manual indexing.
• Practically it compensates for differences among the terms used in searches and indexing terms.

 

How It Works

The user/AI interaction starts when the user scans a document using the software. The user attempts to check in a document by pressing the “Analyze Document” button. That is when the AI kicks in. It starts by automatically analyzing what document is scanned. It then checks for specific keywords and tags them. Next, it extracts content and any other relevant information from the scanned images. Finally, it prompts the user with a form showing all the information it has gathered along with visual markers, known as bounding boxes, on the scanned document. 

The form outputs semi-populated fields such as the document type, keywords, content, and all other detected text. The user can then choose to edit these fields as they see fit. The user can also copy and paste the texts inside the bounding boxes to indices should they need reporting or thorough indexing. This process can also work on previously scanned documents. The system accepts file types such as Microsoft Word, PowerPoint, and any other office file. These are also supported with bulk uploads to hasten data processing. 

 

Conclusion

With the help of technology, sifting through a ton of data will no longer be a long and dreary-intensive task. Companies can now focus their attention on more important facets of efficient data storage and security, and more effective information-based decision-making. All of these are necessary to stay competitive in the modern business ecosystem.