Cotality Launches AI Data Connector Aimed At Real-Time Property Intelligence
New MCP server and AI-ready datasets target more reliable automation in underwriting, valuation, and risk workflows
Cotality is pushing deeper into the AI infrastructure layer of mortgage and real estate, launching a new data connector designed to link artificial intelligence systems directly to standardized property intelligence.
The company announced the release of its Model Context Protocol (MCP) Server alongside “AI-ready” property datasets, positioning the technology as a way to deliver more reliable, real-time insights for property-related workflows.
At its core, the platform is designed to solve a persistent problem in housing data: fragmentation.
“Property data is historically fragmented, non-standardized, and complex,” said Devi Mateti, president of enterprise digital solutions at Cotality, noting that this has often caused AI systems to produce unreliable outputs.
A Connector Between AI And Property Data
Cotality describes the MCP Server as a “universal connector” that allows AI systems to securely access and retrieve property and location data in real time.
Built on the Model Context Protocol — an emerging standard for connecting AI models to external data systems — the server enables AI tools to plug into a consistent data framework instead of relying on fragmented integrations.
The company said this structure allows AI systems to move beyond static or incomplete datasets and instead operate with “trusted property intelligence” grounded in verified data.
Alongside the connector, Cotality is introducing datasets specifically structured for AI use.
Each dataset includes what the company calls a “semantic companion file,” designed to help AI systems interpret not just raw values, but the meaning behind them in real-world property decisions.
That added layer is intended to support:
- natural language queries
- faster deployment of AI tools
- more consistent outputs across workflows
Focus On Automation And Workflow Execution
Cotality said the combination of standardized data and direct AI connectivity is aimed at enabling “agentic workflows,” or AI systems that can execute tasks with minimal human intervention.
The platform is built to support use cases tied to core property functions, including:
- underwriting
- valuation
- risk analysis
The company said its MCP Server allows AI systems to retrieve specific property details, climate risk data, and market insights through a single, standardized interface.
Cotality framed the launch as part of a broader shift toward making property data usable at scale for AI-driven decision-making.
The system is designed to reduce the need for custom integrations between software platforms, replacing them with a standardized connection layer for data access.
By grounding AI systems in consistent, structured datasets, the company said the goal is to enable “high-fidelity” outputs that can support real-world property and lending decisions.