The Paper Crane Geospatial Intelligence Platform
Purpose-built for Geospatial Data Exploration and AI-enabled for Insight Discovery
Why Paper Crane
Empowering You to Make Better Data-Backed Decisions
In an industry such as Insurance, Paper Crane’s software generates highly detailed and proprietary predictive models that will save insurance companies millions annually based on better risk-adjusted policy and pricing decisions.
Additionally, because Paper Crane’s software can amalgamate messy location and geospatial datasets in 1% of the data scientist’s time, it enables data scientists to focus on modeling enhancements and reduces an insurance company’s operating costs.
What Paper Crane Does For You
Better, Faster Decisions
Better risk-adjusted policy and pricing decisions.
Amalgamate messy location and geospatial datasets in 1% of the data scientist’s time.
Lower Operating Costs
Enables data scientists to focus on modeling enhancements and reduces a company’s operating costs.
New models, products and services.
Automated lossless fusion of disparate data
- Seamlessly unify different data formats, types (vector, raster), projections, and spatial resolutions
- Automatic lossless aggregation of attributes using location as the common key
- Integrate geospatial and non-spatial data
Paper Crane in Action
Tom is seeking strategic insights into consumer behavior for a major brand. He has several data sets including spreadsheets with sales data from existing stores, spending data linked to home addresses, regional imagery of population centers, json files with market research data at the zip-code level, and shapefiles containing polygons of high population growth.
These data are bulk ingested into Paper Crane which automatically geocodes address-level data and unifies these data with the zip-code, arbitrary polygon, and imagery data. These data are then merged with Paper Crane layers for school zones and census block group demographic data.
BENEFIT: Data wrangling is reduced to zero. Immediately import, unify, and form a single source of truth for further analysis.
Make any data geospatial-aware using CraneAI
- Exponentially increase the information content of any location data with automated spatial feature engineering
- Extend any type of data with new geospatial linkage, data appends, and extensions
- Create new custom variables using Paper Crane’s intelligent custom Feature Engineering toolkit
Paper Crane in Action
Carolyn is analyzing household exposure to various risks. In Paper Crane, she first unifies proprietary tabular data at the household level, crime data at the zipcode-level, point locations of known environmental perils, and several Paper Crane layers such as slope, elevation, climate, parcel boundaries, and flood zones.
Paper Crane’s automated spatial feature engineering module immediately computes the spatial relationships (adjacency, proximity to nearest, inclusion, density) between all entities adding 500+ new explicit variables. Carolyn then builds additional custom variables using the proximity to nearest highway, maximum slope of property, household income, the number of losses within a 5 km radius, and tree cover percent.
BENEFIT: Spatial feature engineering is a crucial element of a data science, but it can be a specialized and time-consuming task. Paper Crane does this nearly instantaneously.
Customize and refactor spatial data for optimal utility
- Make spatial data tabular and AI-ready at any chosen feature resolution using GeoDataCubes
- Extract unified data in any format at any spatial feature aggregation level with zero data loss.
- Automated imagery/raster incorporation and transformation in real-time
Paper Crane in Action
José is evaluating different commercial real estate sales prediction models. These models require similar inputs, but one model operates at the parcel level resolution, one at the census tract level, and one at the county level. He also has a spreadsheet of addresses with past sale prices for selected properties.
Using Paper Crane, Jose merges his data with the Paper Crane layers necessary for the data-hungry models. With one click, he exports these as tabular data at the property-level, the census-tract level, and the county level for input into his models. All zonal statistics, spatial feature engineering and aggregates of the underlying variables are automatically handled by Paper Crane making cross model analysis simple.
BENEFIT: The lossless geodatacube structure enables the effortless transformation of data into the spatial resolution or feature level appropriate to the task at hand.
Analyze and Model
Explore data relationships and predict outcomes using CraneAI
- Increase the power of your data using the powerful Paper Crane data analytics engine – purpose-built for spatial data exploration and insight discovery
- Find new predictors with automated variable importance analysis
- Discover and visualize hidden data relationships
- Leverage automated machine learning and deep learning pipelines designed specifically for geospatial to build deployable models
Paper Crane in Action
Claudia’s team is designing a new property-level wildfire insurance product. Paper Crane ingests her proprietary insurance claims data and a set of post-event building impact data as training data. She then appends ~800 paper Crane building-level, property-level, proximity and community variables to each address in her training set.
In seconds, Paper Crane performs an automated variable importance analysis across the entire variable space returning a rank-ordered list of the top predictors of fire damage. Claudia runs feature importance and then filters the data to exclude certain types of hardened buildings. With one click, Claudia then executes a genetic algorithm to build the optimal AI machine learning model for wildfire damage.
BENEFIT: Gain a critical edge in predictive modeling by using AI software purpose-built for huge data volumes, large numbers of variables, spatial awareness, and rapid iteration.
The Most Complete Geospatial Platform in the Industry
Proprietarty GeodataSpatial Data ScienceImagery Deep LearningDeveloper Tools & APIs
Location intelligence platformNoNo
Property analytics platformsNoNo
Real Estate data platformsNoNo
Property data servicesNoNo
Paper Crane – Location intelligence for everyone
Converting pixels and polygons to actionable insights in minutes.
- Unparalleled combination of patent-pending GeoDataCube architecture, extreme degree of automation, and specialized AI (machine learning and deep learning) pipelines tuned to the geospatial domain.
- Applicable in insurance, real estate, agriculture, government, retail, digital marketing, and many other industries.
“Your work has been beyond stellar, and you never cease to amaze. Talk about over-delivering, these are great additional features beyond what we discussed! Still blowing expectations out of the water!”
– Data Scientist at a Top 15 Insurance Company