Tavant Launches Mortgage Data Foundry to Slash Loan Origination Costs by 25%

Tavant has launched Mortgage Data Foundry, an AI-ready data integration solution designed to centralize fragmented mortgage data. For fintech professionals, this addresses the critical bottleneck of "data readiness," enabling lenders to lower origination costs and accelerate the deployment of AI agents by unifying disparate systems like CRM, LOS, and servicing into a single source of truth.

What was announced

Tavant Mortgage Data Foundry is a purpose-built solution for the mortgage industry, designed to consolidate data that is typically scattered across CRM, POS, pricing, LOS, underwriting, secondary marketing, servicing, and accounting systems. By integrating these disparate sources into a single, governed foundation anchored to MISMO standards, the platform provides lenders with real-time loan-level insights into compliance, risk, and operational health.

The solution is built to run on a lender’s existing cloud infrastructure, supporting platforms such as Microsoft Fabric, Snowflake, or Databricks across AWS, Azure, and GCP. It functions through four primary components: configuration-driven connectors to source systems, a canonical mortgage data model that settles "source of truth" conflicts, a mortgage ontology layer defining entity relationships, and governed access via dashboards and MCP-compliant endpoints.

Crucially, the system does not replace or write to existing origination and servicing systems, nor does it replicate underwriting rules. Instead, it aims to help lenders reduce the cost of manufacturing each loan by 15 to 25 percent, increase the share of locked loans, and retain 10 to 20 percent more of their existing borrowers during refinancing or new purchases. Tavant claims the use of AI-assisted accelerators from its Tavant Platform™ can compress implementation timelines from several quarters down to a few weeks, allowing lenders to scale from a single use case to an enterprise-wide rollout.

The companies involved

Tavant is a platform-powered AI transformation specialist that has operated in the lending space for two decades. The company focuses on providing AI-driven solutions and automation for the fintech sector, specifically targeting the complexities of the mortgage lifecycle. Under the leadership of Hassan Rashid, President of Fintech, and Pratip Sengupta, Head of Fintech Delivery and GTM, the firm has positioned itself as a bridge between legacy financial systems and modern AI engineering.

The company’s core offering includes the Tavant Platform™, which serves as a foundation for enterprise AI automation and agentic engineering. By focusing on "data readiness," Tavant addresses a significant market gap where lenders have invested in technology but remain unable to leverage their data due to fragmentation across disconnected systems. The firm’s approach emphasizes integration over replacement, allowing financial institutions to maintain their existing investments in Loan Origination Systems (LOS) and servicing platforms while gaining the analytical capabilities of modern cloud data platforms. This strategy places Tavant as a specialized player in the mortgage technology stack, leveraging its long-standing expertise to offer domain-specific data models that generic AI tools often lack.

What FF News has reported before

Tavant has a history of developing automation tools for the mortgage sector, previously focusing on the automation of the underwriting process itself. FF News reported on Tavant Integrates TOUCHLESS AI with Dark Matter’s Empower LOS to Automate Mortgage Underwriting, which detailed how the company used its "Touchless AI" to streamline workflows within Dark Matter’s Empower LOS. That earlier development signaled Tavant’s direction toward reducing manual intervention in the loan manufacturing process. While the previous reporting focused on a specific integration with a third-party LOS, the current announcement of the Mortgage Data Foundry represents a broader infrastructure play, moving from specific task automation to the underlying data governance required for enterprise-wide AI deployment.

What this means

This announcement highlights a shift in the fintech sector from general AI implementation to the specific practicalities of data plumbing. While many vendors offer AI interfaces, Tavant is targeting the "data readiness" gap that prevents these tools from being effective in highly regulated environments. By choosing not to replace the LOS but to sit alongside it, Tavant is putting pressure on traditional core providers who have historically kept data siloed. The move raises a significant question for the industry: can standardized models like MISMO truly harmonize the messy, custom data structures of legacy lenders? If successful, this approach could commoditize the data layer, making the choice of AI agent more important than the choice of database.