Digital Urban

Using AI to improve design code accessibility and adherence at a major UK county council

Full case study View profile

Details:

Company: Digital Urban
Client: Surrey County Council
Year: 2024
Region: UK-wide

Service areas:

Artificial intelligence (AI) and software solutions
Plan-making, planning application and data management systems
Organisational digital transformation

Introduction

Digital Urban’s Place Co-Pilot is transforming the way urban developers find trusted answers to their questions – saving time and delivering better outcomes for all.

Like the majority of local authorities in the UK, Surrey County Council had a problem with their design codes. But it wasn’t with the documents themselves. These are detailed and carefully curated sources of valuable information for urban developers, and other stakeholders, created with the purpose of ensuring they adhere to the correct local planning standards.

Challenges

The challenge: Making design codes more user-friendly.

The issue was with the accessibility of those codes. The length and necessary detail in each document makes it challenging for developers to locate the answers they need to specific planning questions.

This often results in many hours of work, both for developers and planning staff fielding queries, time which could be spent on higher value tasks. There is also the risk of the codes not being correctly adhered to if answers are difficult to locate – which could lead to legal reviews, challenges from the planning committees, or all manner of other headaches.

Surrey therefore asked us to find a way to make design codes more accessible to developers in a user-friendly way, with answers that could be fully trusted by all stakeholders.

Solutions

Working closely with Surrey we developed Place Co-Pilot , a tool that uses AI to search the relevant design code documentation – and only that documentation – to swiftly find answers to users’ questions. Once those answers are pinpointed, it shows exactly where they are sourced, so the user can have complete trust in their accuracy.

Because the solution is AI-driven, we recognized that users would need to have complete faith in the accuracy of the answers – as mistrust in AI is common. For that reason, we only allow the tool to supply answers drawn from the information in the design codes and other documents we give it – and it always clearly shows where it has sourced that information.

As design codes are specific to a defined geographical area, we included a spatial element to the solution, so that the rules are interpreted correctly for each location.

Results

The outcomes: time saved, adherence boosted, relationships improved.

Time saving is already happening as developers no longer need to wade through pages of documents to find 100% accurate answers to their queries. They no longer need to make enquiries to the council when they can’t find details they need. The council shows a saving of valuable staff time previously taken up with fielding queries.

We are also expecting many secondary benefits, such as increased adherence to design codes and, overall, better designed urban environments.

As the tool is so easy to use, we are confident that it will help to foster good relationships between local authorities and their local developers and community.

The tool assists the local community in supporting authorities with their mission to create high-quality urban environments.

You can definitely see this being very useful, making things much quicker... particularly in Surrey, where borough-wide guidance and local guidance can be confusing... Having a tool that brings both together in one place could be a really powerful thing.

(Study Participant)