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Sela Raises $21M to Scale AI Mortgage Agents

Sela raised $21M across Seed and Series A rounds led by Costanoa to scale AI agents for consumer lending and mortgage origination.

Sela raises $21M

The big picture: Sela, a San Francisco-based fintech, has raised $21 million across its Seed and Series A financings. The company develops conversational AI agents that assist loan officers in the mortgage origination process, currently supporting over $1 billion in new mortgages monthly.

Why it matters:

  • Proven Impact: Sela’s AI agents have demonstrated measurable improvements in lead-to-lock conversion rates, boosting lender profits by over 40% in some tests.
  • Market Adoption: The company has achieved over $10 million in annualized run-rate revenue and deployed its technology with six of the top 10 independent mortgage banks.
  • Efficiency Gains: By automating parts of the sales process, Sela aims to reduce customer acquisition costs and increase funded loan volumes for financial institutions.

How it works:

  • Conversational AI: Sela’s voice agents handle borrower questions, explain financing options, build customer relationships, and identify when human loan officers should intervene.
  • Outcome-Based Metrics: The technology is measured by outcomes like productive conversations and completed loans, rather than just AI usage, aligning with lender goals.
  • Continuous Optimization: Agents are trained and refined using data from tens of millions of conversations to replicate high-performing sales behaviors at scale.

The catch: The consumer lending and mortgage sectors are highly competitive, with numerous fintechs and established players also investing in AI automation. Sela’s reported performance gains, while significant, are company-reported and reflect specific deployments, requiring independent verification for broader industry confidence. The long-term challenge will be to maintain these performance advantages as other AI solutions mature and to expand beyond mortgages into other complex consumer lending areas without diluting focus.

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