From scattered sources to a dataset you can trust.
Every Horiz-in dataset starts with a Framework defining exactly what's being tracked, then it's built, validated, and can even be kept up to date in real time.
We turn messy information into structured, useful data.
Your information is scattered across public sources and internal systems, hidden and hard to use. We turn it into a dataset you can actually work with.
Four steps, every time.
Define your objectives
We help you define your knowledge objectives: what do you wish you could know, say, and do?
Design the framework
We design the data you need to answer your objectives, so you're not getting data you don't need.
Produce and validate the data
We source, structure, and validate the data against your Framework, the same checking engine behind our Validate offering.
Make it usable, and get adoption
You receive the dataset in an app, table, or map. It's built, validated, and can even be kept up to date in real time.
We use AI too. We just don't stop there.
Most people's first instinct is to ask an AI to build them a dataset. We use AI in our own proprietary data workflows to make sure data is consistent, validated, double-checked, and complete. An AI can generate you a table, Horiz-in can build you systematic organisational knowledge.
- No data model built around your actual question
- Not kept up to date over time
- Not rigorously checked or verified in a systematic way
- Limited by how much data it can hold and reason over
- Difficult to create data that helps many people at once
- A Framework designed around your objectives
- Kept current for as long as you need it
- Every fact checked and verified, systematically
- Built to structure and hold data at any scale
- Frameworks designed to satisfy multiple stakeholders at once