ATTOM launches three AI agents to interrogate 160 million property records
The Irvine data provider is moving from APIs and files into analysis and report generation, with MCP connecting its records to Claude and ChatGPT.
By Ryan Merket · Published
Primary source: PR Newswire
Why it matters
ATTOM is using proprietary property records to climb from data licensing into analysis and finished reports, while MCP keeps AI access governed, metered and tied to its APIs.

ATTOM CEO Rob Barber on August 18th introduced three specialized AI agents that let customers query property records, analyze housing markets and generate finished reports through natural-language prompts. The release extends ATTOM's data business into the work customers perform after retrieving a record, placing the vendor closer to underwriting, portfolio research and client delivery.
Barber has spent more than three decades in real estate information services. He joined ATTOM's predecessor, RealtyTrac, as CEO in 2015, led the creation of its consolidated data warehouse and oversaw the 2016 rebrand to ATTOM. Before that, he spent a decade running Environmental Data Resources, where ATTOM says he shifted a specialized property database toward workflow and market-intelligence products. The new agents follow the same playbook: use proprietary records as the base, then sell access to the decisions and documents built from them.
The technical work falls under Chief Product and Technology Officer Todd Teta, whose background puts him unusually close to the market ATTOM is trying to reshape. According to ATTOM's leadership biography, Teta co-founded mortgage and real estate analytics provider VisionCore, sold it to CoreLogic and later led research and development groups that built CoreLogic's early mobile and mapping products. He studied computer engineering and computer science at the University of Southern California and joined ATTOM after leading product and technology at Meyers Research.
Three agents, each with a narrower job
The Property & Place Insights Agent handles questions about individual properties, parcels, neighborhoods and geographic areas. ATTOM says a user can ask for property intelligence in natural language rather than selecting an API endpoint, assembling a query or navigating a conventional research interface.
The Data Analyst Agent works across aggregated records. ATTOM positions it for housing-market comparisons, trend analysis, portfolio evaluation and research queries. That distinction matters operationally. A property lookup typically starts with a known address or parcel, while a market query may require selecting geographies, time periods and measures before aggregating many records.
The Report Generation Agent pushes furthest into the application layer. ATTOM says it can assemble property characteristics, automated valuations, comparable sales, maps and neighborhood information into a customer-ready document. For a lender, brokerage, investor or insurance operation, that output could replace several steps between data retrieval and a report delivered to an employee or client.
ATTOM describes the agents as part of a self-service workbench built with the Model Context Protocol, or MCP, and the Agent2Agent protocol. Customers can also connect ATTOM Intelligence to applications that support those standards, including Claude and ChatGPT. ATTOM continues to support direct APIs, bulk licensing and cloud delivery, so the agents add another route into the same data estate rather than replacing ATTOM's established delivery products.
ATTOM says that estate covers 160 million U.S. properties, or 99% of the U.S. population. Its records span property characteristics, ownership, deeds, mortgages, foreclosures, valuations, environmental hazards, school areas, neighborhood information and geographic boundaries. The coverage figure and customer claims are supplied by ATTOM; ATTOM does not publish audited revenue, customer-count or usage figures for the new agents.
The MCP server is the control plane
ATTOM's agents sit on an MCP server that translates model tool calls into requests against ATTOM's existing systems. The server exposes structured tools for property profiles, ownership records, tax history, sales and mortgage history, automated valuation models, comparable sales, foreclosures, building permits, rental estimates and home-equity data.
That design gives developers a standardized interface while preserving the controls expected around licensed property data. ATTOM says access runs through authentication, plan entitlements, permissions, logging and usage monitoring. Its support documentation says the MCP server acts as a real-time broker and does not persist requests or responses. Traditional applications can continue calling ATTOM's APIs directly.
The implementation also carries familiar usage economics under the agent language. Each tool invocation counts as one request, regardless of how much information the tool returns. A workflow that separately calls a property profile, valuation model, comparable-sales tool and permit record therefore consumes four requests under ATTOM's accounting. Rate limits and monthly quotas are tied to customer plans, and ATTOM instructs developers building high-volume workflows to handle 429 Too Many Requests responses with retry logic.
ATTOM uses bearer-token authentication, which keeps the server recognizable to developers already operating API-based products. The abstraction removes some orchestration work, especially for low-code tools and internal assistants, while retaining the underlying mechanics of metered data access. That balance is central to ATTOM's commercial strategy: make the database easier for AI systems to consume without surrendering control over permissions, consumption or licensing.
The specialized agents represent a second layer above that interface. MCP gives a model a governed way to call property tools. ATTOM's agents package those tools around defined jobs, including answering a property question or producing a report. That can shorten deployment time for customers that want an outcome and have little interest in assembling their own prompts, tool sequences and output templates.
A three-step move up the software stack
ATTOM has staged the rollout across 2026. On January 27th, ATTOM introduced the MCP server alongside Databricks delivery. That release established an AI-focused connection to existing property endpoints and gave analytics teams another way to consume licensed datasets inside their cloud environments.
On May 12th, ATTOM grouped its data, delivery systems and analytics under the ATTOM Intelligence name. The framework organized ATTOM's products into three layers: engineered data, AI-native delivery and analytics that produce decision-ready outputs. The August 18th agents give that framework visible applications rather than another taxonomy for the same catalog.
ATTOM also continues its work with Snowflake, where customers can access licensed datasets inside their own Snowflake environments. Cloud delivery and MCP address different integration points. Snowflake brings the records to a customer's data warehouse for internal analysis, while MCP lets an AI application retrieve specific records and analytical outputs at runtime.
The agents give ATTOM a direct role in the final workflow. That creates a useful commercial tension. ATTOM tells customers that it supplies data without competing against the products they build. A report-generation agent moves closer to functions that software vendors, brokerages and research platforms have historically implemented on top of ATTOM records. ATTOM can preserve that positioning if customers treat the agent as infrastructure embedded in their own products. A standalone ATTOM-generated report places the product further into customer-facing software.
Barber's private equity mandate meets the agent cycle
Lovell Minnick Partners acquired ATTOM from Renovo Capital and Rosewood Private Investments in January 2019. Financial terms were undisclosed. Lovell Minnick highlighted ATTOM's recurring license revenue and its opportunity to expand into additional markets, while Barber said at the time that ATTOM planned to build out an end-to-end data platform.
ATTOM has since expanded through acquisitions and additional delivery products. The AI rollout offers another route to growth from the same underlying records. Easier access can increase query volume. Packaged analysis can support higher-value contracts. Finished reports can make ATTOM relevant to employees who would never work directly with an API or a warehouse table.
The risk sits in reliability at the point of action. Property records can feed credit, insurance, appraisal, investment and government workflows where a plausible answer is insufficient. ATTOM's pitch rests on using structured tools and governed records to reduce the model's room to improvise. The report agent raises the bar again because polished output can conceal weak source selection, stale records or an unsuitable valuation as easily as it can save an analyst time.
ATTOM's release does not establish independent accuracy rates for the agents, and its 160 million-property figure measures database coverage rather than answer quality. The product's value will be determined by how clearly each response exposes its underlying records, dates and analytical assumptions. In property intelligence, provenance is part of the result.
Barber called the agents another step in ATTOM's long-term investment in property data and AI. The sharper reading is that ATTOM is defending the economic position of its database as conversational interfaces reduce the value of raw access alone. If customers increasingly begin a property workflow with a prompt, ATTOM wants to supply the records, meter the calls and generate the document that comes out the other end.