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Case Studies
Digital Office Company
From minutes to seconds: Transforming document management with AI
Digital Office Company and IBM
Digital Office Company (DOC), a Finland-based provider of information management solutions and services, helps businesses find and manage large swaths of documents at speed and scale by enabling them to identify, classify and extract insights from their documents.
Most often, automated document classification systems provide superficial insight into the nature of documents through generic tags or metadata enrichments. This superficial classification doesn’t fully take into account the contents of the document itself, meaning that the true value of the data cannot be leveraged unless each document is manually evaluated.
The bottom line is that such a process of manual evaluation of documents to identify document types, detect misplaced documents and extract crucial details would be very laborious and time consuming. Moreover, lack of proper metadata handling poses potential GDPR concerns and negatively affects data quality for down-stream tasks. Unresolved, such challenges can threaten the competitive edge and efficiency of DOC’s customers because of these data quality and regulatory compliance issues.
To tackle these hurdles, DOC collaborated with the IBM Ecosystem Engineering Build Lab, IBM Client Engineering and IBM Technology Expert Labs to develop a pilot that leverages a combination of traditional machine learning and generative AI—large language models (LLMs)—with IBM® watsonx.ai™ and IBM Watson® Discovery.
Through a 6-week co-creation pilot, DOC developed an IBM Watson Discovery platform-powered data pipeline solution that uses custom machine learning models alongside Mistral AI’s Mixtral-8x7B LLM to classify documents with custom labels and metadata tags. The focus of the pilot was set on the real estate industry because of the variety of data types and regulatory requirements faced by DOC’s customers in this domain. This industry focus led to the creation of an additional capability that expanded the scope of the solution—using LLMs to extract rich insights such as board decisions from meeting minutes documents.
Enhanced document classification, insights and cost savings
The pilot proved to be highly successful in terms of the increases in speed and quality of document classification and insights of large volumes of documents. In addition, the results of the pilot provide a clear indication of the benefits of a combined approach of traditional machine learning and generative AI, in which the shortcomings of each approach are covered by the strengths of the other. What used to take an individual a few minutes to manually look through a document and classify it can take just 2 seconds per document through an automated process that requires a human evaluation only for documents that are flagged as outliers by the system.
Looking ahead, DOC aims to expand on this pilot by further developing its solution to expand it to other industries and customer segments.
Digital Office Company (DOC) (link resides outside of ibm.com) is a Finland-company founded in 1996 that offers modern information management solutions for organizations of different sizes. Offices are located in Espoo, Hämeenlinna, Lahti and Lappeenranta, Finland.
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