Cherre is a real estate data integration and analytics platform that connects, normalizes, and delivers high-quality property data to help companies make smarter, faster investment decisions. Built specifically for the real estate industry, Cherre enables institutional investors, asset managers, brokerages, and lenders to centralize fragmented datasets into one secure and scalable platform.
Founded in New York City, Cherre’s mission is to unlock the full potential of real estate data. The platform integrates internal and external data sources—including property, financial, tenant, market, and geospatial data—and applies identity resolution and normalization to deliver a unified data layer. This empowers teams to eliminate silos, reduce data prep time, and focus on high-value analytics and decision-making.
Official website: https://cherre.com
Features
Data Integration: Connects internal systems (e.g., Yardi, MRI, VTS) and external data providers (e.g., CompStak, CoreLogic, Moody’s) into a single, normalized platform.
Entity Resolution Engine: Automatically matches and deduplicates records across data sources, resolving inconsistencies in property IDs, addresses, and ownership structures.
Data Normalization: Transforms disparate datasets into standardized formats using Cherre’s real estate-specific data model.
Custom Data Lake: Create a centralized, query-ready data lake tailored to your business rules, analytics needs, and governance standards.
Real Estate Knowledge Graph: A proprietary system that links entities (properties, tenants, owners) and their relationships across time and geography.
Flexible APIs: Access normalized data through API endpoints for direct integration with BI tools, dashboards, or machine learning pipelines.
Security & Compliance: Enterprise-grade security with SOC 2 Type II compliance, role-based access controls, and data encryption at rest and in transit.
Visualization Ready: Integrates seamlessly with tools like Tableau, Power BI, or custom dashboards for dynamic reporting and visualization.
Performance Metrics: Track asset performance, leasing trends, and investment KPIs using unified data layers.
Modular Architecture: Choose only the data connections, modules, or services your organization needs.
How It Works
Connect Your Data: Cherre connects to your internal systems (like CRMs, financial tools, or property management software) and third-party data vendors.
Resolve & Normalize: The platform automatically matches, deduplicates, and normalizes data using AI-based entity resolution and a robust real estate schema.
Unify in a Data Lake: All datasets are centralized into a secure, queryable data lake that can be customized to your company’s data architecture.
Access via API or Dashboard: Users can access clean, structured data through APIs or connect to analytics tools to build visualizations, dashboards, and reports.
Enable Advanced Analytics: With unified data, companies can build predictive models, track asset performance, and inform acquisitions or dispositions more effectively.
Cherre acts as the foundational data infrastructure layer for real estate companies that want to unlock cross-functional insights without manual data wrangling.
Use Cases
Institutional Investors: Analyze acquisition opportunities, monitor portfolio risk, and improve return forecasting with unified data.
Asset Managers: Track leasing performance, operational costs, and tenant behavior across portfolios in real-time.
Brokerages: Leverage clean, centralized data to improve deal sourcing, client insights, and competitive positioning.
REITs and Funds: Ensure consistent reporting and compliance across funds, assets, and stakeholders.
Data Scientists & Analysts: Reduce time spent on data preparation and focus on predictive modeling, clustering, or spatial analytics.
Lenders and Underwriters: Evaluate borrower risk, property values, and market trends with trusted, normalized datasets.
Pricing
Cherre does not publish fixed pricing on its website. Pricing is fully customized based on:
Number of data sources and integrations
Volume of data processed and stored
Required features and modules (e.g., knowledge graph, API access, analytics support)
Size of the organization (e.g., single fund vs. enterprise portfolio)
Implementation and onboarding scope
Cherre serves mid-size to large real estate companies, and pricing is structured to reflect enterprise-grade deployment and support. To receive a tailored proposal or demo, visit:
https://cherre.com/contact
Strengths
Real Estate-Specific Platform: Purpose-built for the unique complexity of property data, unlike generic data integration tools.
Automated Entity Resolution: Saves significant time by automating deduplication and matching across sources.
Enterprise-Ready: Offers security, scalability, and compliance features suitable for large financial institutions and public REITs.
Vendor Agnostic: Connects to hundreds of internal and third-party systems, reducing dependency on one ecosystem.
Accelerates Time to Insight: Minimizes manual data prep and enables faster reporting, forecasting, and decision-making.
Custom Data Lake: Offers flexibility to shape data delivery and access methods according to organizational needs.
Strong Support and Implementation: Dedicated onboarding and customer success teams help with initial integration and long-term adoption.
Drawbacks
Not for Small Businesses: Designed for enterprise-scale real estate operations; may be too complex or expensive for small firms or individual investors.
No Public Pricing or Self-Service Model: Requires contacting sales and setting up a demo to begin using the platform.
Implementation Effort: While streamlined compared to legacy systems, onboarding still requires coordination with IT, data teams, and stakeholders.
Analytics Not Built-In: Cherre focuses on delivering clean, connected data—not on native analytics or dashboards (though it integrates with BI tools).
Requires Data Governance Alignment: Organizations need clear internal data ownership and governance structures to fully benefit from Cherre.
Comparison with Other Tools
Cherre vs. Snowflake (for Real Estate)
Snowflake is a powerful cloud data warehouse but not real estate-specific.
Cherre includes pre-built data models, schemas, and connectors designed specifically for property data.
Cherre is more plug-and-play for real estate teams; Snowflake requires more engineering resources.
Cherre vs. Altus Data Solutions
Altus provides valuation and asset data for CRE.
Cherre is broader in scope, connecting financial, tenant, market, and operational data from many sources.
Altus is data-provider first; Cherre is a data integration and analytics infrastructure platform.
Cherre vs. CompStak, CoreLogic, or Reonomy
These tools provide data sets; Cherre connects and integrates them with internal systems.
Cherre doesn’t compete directly—it enhances the utility of these third-party data sources by integrating them into unified workflows.
Customer Reviews and Testimonials
While individual user reviews are not listed publicly on Cherre’s site, the platform has earned endorsements from large real estate firms, investment managers, and proptech thought leaders.
Featured client outcomes include:
Time Savings: “We reduced weeks of manual reporting down to minutes using Cherre.” – Real Estate Investment Analyst
Operational Visibility: “We finally have a single source of truth across assets, markets, and stakeholders.” – Portfolio Manager
Decision-Making Support: “With better data, our acquisitions and dispositions are more strategic and defensible.” – Director of Investments
Cherre also has case studies with top-tier clients in multifamily, commercial, and investment verticals.
To see client stories and industry insights, visit:
https://cherre.com/resources
Conclusion
Cherre is a leading data integration and analytics platform purpose-built for the real estate industry. By unifying internal and external property data into a single, normalized layer, Cherre enables real estate firms to eliminate data silos, reduce risk, and accelerate decision-making across acquisitions, asset management, and investment analysis.
While it is geared toward mid-to-large scale organizations and does not offer public pricing or self-serve onboarding, Cherre delivers tremendous value for firms looking to modernize their data infrastructure and compete with data-driven insights.
