Case study

Using semantic-based AI to reduce the editorial board’s workload at The Finnish Population Register Centre (VRK)

Many organisations, like the public sector agency, The Finnish Population Register Centre (VRK), handle tens of thousands of documents in a free text format coming from thousands of different channels. Extracting, summarising and classifying information from natural text is a critical topic for many organisations that can help save workload and improve service quality.

In this case study, you will learn:

  • How AI has helped VRK to organise and classify service description documents
  • How a semantic-based AI solution can automatically pick out contextually similar documents from  service descriptions
  • How AI-developed template can help improve the quality of the content.
case-vrk-c
VRK case study download

Fill in your details to download the case study

By submitting this form you agree that we may contact you in a manner as describribed in our privacy policy.

Digital Workforce In the news:

inthenews1
IDG Connect

CIO Spotlight: Jukka Virkunnen, Digital Workforce

banking-harri
Global Banking & Finance

Banking and automation: how catastrophe led to innovation?

automation-inthenews
IT Pro Portal

How automation can provide a foundation for digital transformation