Irvine – October 13, 2026 -- ATTOM has released version 1.0 of Semantic Views for its property data delivered through Snowflake, adding a layer of business context intended to help AI systems interpret and query complex real estate datasets.
ATTOM builds the semantic layer on Snowflake's native technology
The offering uses Snowflake's native Semantic View technology. It defines how ATTOM's property data points connect and should be used, so customers no longer have to build and maintain that knowledge themselves. ATTOM said it drew on decades of experience curating and standardizing property data.
Four customer benefits target AI development speed and accuracy
ATTOM lists four intended outcomes:
- Simpler AI analysis through natural-language questions.
- Shorter development time through ATTOM-defined data relationships and logic.
- Greater accuracy and consistency through trusted data definitions.
- Faster insights through easier access to property data in Snowflake.
Rob Barber, CEO of ATTOM, described the release as another step in the company's AI strategy, extending its data advantage by supplying the context AI needs to interpret the data.
ATTOM commits to ongoing releases that expand coverage and refine relationships
The v1.0 release is the first stage of a continuing program. Future versions are planned to expand coverage, strengthen data relationships and refine the semantic context available to AI and analytics tools. ATTOM will keep evaluating the underlying context as new business questions, use cases and data needs emerge.
Todd Teta, Chief Product and Technology Officer, said "this isn't a one-time development," and added that ATTOM plans to enhance the views continuously as customer needs evolve.
Semantic Views are available across a growing range of ATTOM's property data products delivered through Snowflake. ATTOM said coverage will continue to expand.