Product Overview of Cherre
Cherre is a leading real estate data management and intelligence platform designed to transform the way real estate professionals manage, analyze, and utilize their data. Founded in 2016 and headquartered in New York City, Cherre’s platform is tailored to help clients in the real estate sector, including investors, lenders, asset managers, property developers, and real estate technology firms.
What Cherre Does
Cherre’s primary objective is to consolidate and standardize disparate real estate data sources into a single, unified platform. This allows clients to break down data silos, automate workflows, increase efficiencies, and make smarter, data-driven decisions. By integrating internal, public, and third-party data, Cherre provides a comprehensive view of the real estate market, enabling clients to evaluate opportunities more accurately and quickly.
Key Features and Functionality
Data Integration and Standardization
Cherre’s platform seamlessly ingests, connects, standardizes, and consumes all types of real estate data. It uses extensive application partner networks to connect and ingest data from key internal systems such as ERP solutions, deal management platforms, and leasing platforms. The platform also includes a Submission Portal that streamlines and standardizes data collection from third-party vendors and investment managers.
Scalable and Secure Architecture
Cherre’s architecture is designed to be scalable and secure. It leverages Cloud SQL for PostgreSQL and BigQuery to process and store data, ensuring a single source of truth for clients. The platform is SOC-2 compliant, with strict security and compliance measures, including role-based security architecture, data encryption both at rest and in transit, and protection against unauthorized modifications.
GraphQL API and Data Accessibility
Cherre utilizes GraphQL to provide clients with a flexible and efficient API. This allows clients to access and combine different datasets without the need for extensive coding changes. GraphQL prevents over-fetching and under-fetching of data and seamlessly handles complex joins and relationships between datasets.
Immutable Tables and Disposable Infrastructure
To ensure data integrity and the ability to correct mistakes quickly, Cherre employs the concept of immutable tables. These tables are recomputed from scratch, allowing for quick iteration and the ability to compare different versions of output. This approach, though more costly and time-consuming, ensures that data is always accurate and can be rebuilt if necessary.
Spatial Queries and Custom Functions
Cherre’s platform supports quick and easy spatial queries, enabling clients to pull information from custom-drawn geographical areas. This is facilitated by tools like Hasura, which includes features such as object aliasing and custom functions, making it easier for clients to pull data based on specific use cases without requiring significant changes to their API calls.
Machine Learning and Data Insights
With over 3.3 billion addresses and rigorously tested machine learning algorithms, Cherre connects and aggregates data based on various identifiers or geospatial layers. This enables clients to extract actionable insights, train machine learning models, and visualize data using BI tools like Looker.
Data Fabric and Knowledge Graph
Cherre’s Data Fabric is a vast real estate data knowledge graph that includes property characteristics, recorder and deeds, valuations, tax and assessments, liens and mortgages, boundaries, community and demographics, and points of interest. This comprehensive data model is continuously growing, providing clients with the largest real estate data knowledge graph in the world.
Conclusion
In summary, Cherre’s platform offers a robust solution for real estate data management, providing a unified, secure, and scalable environment for clients to manage their data, automate workflows, and gain valuable insights to drive better decision-making.