Inconsistent formats
Address fields were recorded in inconsistent ways.
Cleaner addresses. More usable data.
AI-assisted standardisation of inconsistent address fields for government-affairs data.

What stood in the way.
Inconsistent address records reduced the usability of LegiStorm's government-affairs data. The same address written in different ways makes records harder to match, search and rely on.
Address fields were recorded in inconsistent ways.
Some address fields contained inaccurate values that needed correcting.
Poor address quality reduced how useful the data was for the people relying on it.
How we answered it.
We built an AI model that learns from training data and standardises inaccurate address fields. Instead of hand-written rules for every variation, the model learns the patterns from examples.
The parts that made the difference.
The model learns from training data how addresses should look.
The model rewrites inaccurate address fields into a consistent form.
Standardised addresses make the wider dataset easier to use.
What changed for the client.
LegiStorm's address records are now more consistent and more useful downstream.
What it was built with.
Part of our AI and machine learning work.
The next big thing starts with a conversation.
An idea, a challenge, a “what if”. Tell us what you have in mind, and we’ll figure out the next step together.
What happens next
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