Pupil — Digitally mapping the built world

our platform

What Google did for the outside world, Pupil is doing for interior space, with precision, accuracy and reliability

Next generation technology solving the industry’s lack of primary, verified data

Capture-as-a-service

Industry defining Digital Surveyors capture real estate spaces with unprecedented speed, ensuring a complete data chain of custody.

Verified data library

The world’s first verified spatial data library, with tens of millions of square feet captured. A primary dataset of multi-modal 3D data.

Pupil's first verified spatial data library

Pupil state of the art cloud infrastructure

Proprietary tech stack

Our state of the art cloud infrastructure supports seamless API integrations. Powered by our constantly evolving AI engine.

World leading ai

Pupil is pioneering computer vision for interior spaces. Our groundbreaking AI roadmap enables semantic and instance level segmentation.

ESG in Focus

The built environment is a threat to our planet

By taking buildings online, we are creating a more sustainable future

Cities create more than 70% of carbon emissions

Buildings are responsible for 40%

Discover our research

Our products

Our three products, Spec, Stak and Strat, are changing how we interact with and manage real estate globally

Pupil creates accurate digital twins of properties to:

Residential real estate

Commercial real estate

registration service

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Drive efficiency, sustainability and lower emissions in the built environment

Transform planning, operations, marketing and finance for real estate globally

Increase trust and transparency in the world's most valuable industry

We’ve digitised tens of thousands of properties with a value of over $100 billion

Trusted by:

“A game changer for data accuracy, usability and fast output”

James Maddock, Head of Occupier Services, EMEA
Cushman & Wakefield

Digitally mapping the built world from the inside out; the ground source of truth for real estate data

Turning buildings into verified spatial data