Microform are a document management solution provider, who specialize in document retrieval, access, and storage options to boost efficiency, flexibility, and security. They started out in 1956 as a publishing venture serving academic institutions by microfilming of research materials and theses for archiving processes and now serve both professional businesses and heritage organisations across the UK.

The problem:

Microform reached out to us for a Knowledge Transfer Partnership (KTP) as they did not have the necessary technology to extract key information and data from digitized documents.

Having access to this technology would help non-technical users to search their databases with ease, improving productivity and increasing efficiency.

Project Process:

Experts from our Industry and Innovation Research Institute worked with Microform to develop and apply advanced machine learning tools to their systems to improve operations and efficiency.

This was achieved by creating intelligent search functions using computer vision-based image recognition and natural language processing techniques within a historic archive to assist researchers in discovering new material and support the cataloguing of huge volumes of digitized documents.

This led to improvements in the efficiency of the archive curation process (where archives are organized, edited, and key points of interest are highlighted) which now allows Microform to process archives more rapidly – taking them from concept to publication with far less editorial effort.

The results:

This collaboration has strategically aligned with the company's long-term business goals, setting out to innovate its product offerings and improve its competitive position in the market by leveraging advanced technologies such as AI and machine learning.

By working with us, Microform have been able to achieve their strategic goals in many ways including strengthening innovation through the integration of advanced machine learning techniques into the company archival curation processes, promoting innovation, and enhancing the company’s existing product line.

By developing the technical expertise within the Company in areas like AI, computer vision, and NLP, the partnership has supported the company to increase development capability and created an ongoing competitive advantage.

This partnership has developed tools that enhance metadata creation and accelerate the archive curation process, enabling the company to explore new business models, such as full-service archiving and SaaS offerings, aligning with strategic initiatives to diversify and grow revenue streams.

Through the KTP, the partnership has also created customized machine learning and NLP solutions that address specific market needs, allowing to establish a unique selling point within its industry.

As the Company aims to increase its turnover significantly, the KTP is a central strategic element aimed at realising this financial objective by contributing directly to business innovation and expansion.

They say: “KTP has significantly transformed our business, bringing cutting-edge machine learning expertise that has enabled us to differentiate our services and exceed customer expectations in the archival sector. Our KTP experience has been invaluable in promoting a culture of innovation, enhancing our technical competencies, and paving the way for sustained business growth through strategic market expansions and the development of novel AI-driven solutions”. Daniel Le Page, Technical Director, Microform