Fast tracking e-Government deployment
through automated Customer Journey development

Complicated rules, multiple contact points, numerous forms and applications and three administrative levels: processes as common as home renovations in Flanders require a lot of manual administrative work. To streamline customer journeys and simplify processes, municipalities and other public organizations would benefit from e-government applications. However, implementing these solutions is challenging, considering the lack of well-structured content and the need to integrate legacy systems. FAST aims to fast-track these challenges by creating an engine to automatically generate customer journeys from existing unstructured content for a full range of administrative tasks.

FAST is an imec.icon research project funded by imec and Agentschap Innoveren & Ondernemen. It started on 01.05.2018 and is set to run until 30.04.2020.

Dynamic form generation using AI

Citizens engaging with government processes encounter many different tools, UI’s, webforms and administrative levels. Customer journeys could be vastly simplified through electronic and automated administrative processes and services. Yet most municipalities find these tools difficult to implement, causing them to score poorly on European benchmarks.

FAST gathers experts in UX, UI, natural language processing and data linking to develop a rapid approach to e-government implementation in municipalities. Together, the consortium optimises existing customer journeys through data linking and public data, and uses them as models for new customer journeys. A flexible library of UI elements allows for the generation of customer journeys and usage monitoring. .


Content scraping

A scraper extracts data from various unstructured data sources such as PDF files and websites from towns and cities. FAST leverages taxonomies and content from other municipalities in order to improve its understanding of the content and context.

From unstructured content to knowledge

FAST uses state of the art natural language technology to extract knowledge about business processes from this unstructured data and uses that knowledge to generate structured processes. These structured, machine-readable processes can be used to further automate the business. A new standard - called OSLO-STEPS - was created for this.

Automatic process optimisation

The generated processes are validated and further optimised: duplicated steps are removed, loops are removed, irrelevant steps are removed,...

Automatic UI generation

A library of generic UI components is used to automatically generate a conversational UI out of the processes that were the output of the previous steps. Both multi-step webforms, chatbots and even voice-based conversational interfaces are supported.

Optimised UI based on users typology

The generated UI will be optimised for each specific user. Both the process itself and the UI are tailored to the user. Based on what we already know from that user, we can skip certain steps to avoid asking the same questions multiple times. The UI itself will be optimized based on the user’s typology in order to show him/her the most user-friendly and easy-to-use UI.

Multivariate testing

FAST automatically generates different UI candidates based on the process definition. A/B testing is then used to evaluate the different UI candidates and select the most optimal version based on actual end-user behaviour and his/her typology.

Feedback loop for continuous improvement

Feedback from users is looped back into the previous steps in order to continuously improve the generated processes. FAST will thus help governments to identify inefficiencies in their customer journeys and allow them to further improve the overall citizen experience in dealing with government administration.

closing event


OSLO-steps and NLP Demonstrator

FAST demonstrator and valorisation




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We are actively looking for additional members of the user group who are interested in running a pilot with our technology, both in government and industry.

Consortium contact
Sander Goossens - Endare