Building with geospatial data can be easy!

Iggy is a toolkit that makes it easy to build data products with rich geospatial data.

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A diagram illustrating how data flows from the Iggy Data Cloud, is merged with customer data to produce custom Iggy Features, which can then be enriched with location data to produce visualizations and models

Test hypotheses and build data products, fast

A diagram showing how Iggy ingests raw data sources, is cleaned up using various analysis methods and benchmarking before being used to produce and store as pre-computed features.
INGESTION & QUALITY CONTROL

Spend less time cleaning data

Geographic data comes in all shapes, sizes, formats, and quality. We source, clean, normalize, transform, and QC hundreds of public and private datasets to create new, reliable datasets from them so you don't have to.

Learn more about data ingestion and quality control at Iggy →
A diagram showing how Iggy Features is generated using boundary data and other types of location data that can come from the Iggy Data Cloud as well as other data sources
COMPUTATION & AGGREGATION

High fidelity, custom datasets

Iggy’s compute engine aggregates various data features into boundaries (from zip codes, census tracks, to in-house walking and driving catchments, or even custom viewsheds that you define) to produce highly granular, custom datasets that represent places in entirely novel and powerful ways.

Learn more about custom isochrone boundaries →
A diagram showing how data visualizations and models can be created from customers’ data warehouses using Iggy Enrich and custom Iggy Features
MODELING & VISUALIZATION

Use Iggy on top of your data warehouse

Use Iggy within your own data warehouse, with your own location data. Our tools, like the IggyEnrich Python module, and tutorials make it simple to enrich your in-house data.

Explore enriched datasets using any off-the-shelf map visualization library, like kepler.gl, or feed your enriched dataframe into any modeling library.

Learn more about the IggyEnrich Python module →

Get Started

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