Dark Matter Acquires House Numbers' Agentic AI Platform For Home Lending, Names Jeff Levinsohn Chief AI Officer

(MENAFN- Send2Press Newswire) JACKSONVILLE, Fla., Oct. 30, 2026 (SEND2PRESS NEWSWIRE) - Dark Matter Technologies (Dark Matter), an innovative leader in home lending technology, today announced it has acquired the AI agent platform and related intellectual property of House Numbers, a venture-backed agentic AI company that builds AI agents for home lending workflows. Alongside the technology, Dark Matter has brought on the team that built it, led by House Numbers co-founder and CEO Jeff Levinsohn, who joins Dark Matter as chief AI officer. The acquisition extends Dark Matter's existing AI strategy, deepening both its agentic capabilities and the team that builds them.

Image caption: Dark Matter Technologies logo.

The acquisition accelerates agentic AI across the Empower® loan origination solution (LOS) and its built-in point of sale (POS), helping lenders put autonomous AI agents and AI agent assistants to work to improve borrower experiences, increase loan officer productivity, lower the cost of origination and advance the shift from doing to reviewing.

Levinsohn, together with co-founders Benjamin Hoffman and Arthur Granado, founded House Numbers in 2021 and led development of the platform, bringing AI agents from concept into live production for home lenders. The platform has been in production for two years and has processed loans for more than 100 lenders. As chief AI officer, Levinsohn will lead Dark Matter's AI strategy and development, working with Dark Matter's product and technology teams to enhance existing agentic solutions and bring agentic AI capabilities into Empower, its built-in POS and the broader ecosystem. The engineering and product team that built the platform joins him at Dark Matter, with Arthur Granado as vice president of engineering and Benjamin Hoffman as vice president of AI adoption and enablement.

“We started House Numbers because getting a mortgage should be faster and cheaper than it is, and software should do more of the work,” said Levinsohn.“The hard part of agentic AI is not getting a model to do a task once. It is orchestrating complex agentic work safely inside a regulated process and executing valuable tasks consistently at scale, with people in control of the decisions that matter. That is what we built at House Numbers. Dark Matter already has AI working inside the loan process for some of the largest lenders in the country, and that is exactly why our team wanted to be here. It is the right place to create the magnitude of impact we always hoped for.”

House Numbers developed its platform to run AI agents live in production for lenders, with controls designed for a regulated industry. The platform's autonomous agents constantly monitor for loan changes and respond by working loan conditions, taking necessary actions, driving recommendations and communicating with borrowers and lenders by email, text and voice, with loan operations personnel supervising. The platform pairs a workflow orchestration engine with Model Context Protocol (MCP), so each agent gets only the context and capabilities its task requires. Through the MCP gateway, external AI assistants can work a loan file with the same permissions and controls as a human user. Confidence gating, a code-enforced compliance blocklist and human oversight keep agents within defined limits. A complete audit trail records every action taken by a person or an agent. Per-workflow model tiering, multi-provider failover, extensive evaluations and per-loan cost attribution help the system run efficiently at scale.

The acquisition supports Dark Matter's three AI platform commitments: AI embedded in every workflow, an AI agent assistant for every user and the shift from doing to reviewing across the loan lifecycle.

“We're AI-forward, and we're disciplined about what we build and what we buy,” said Vikas Rao, CEO of Dark Matter Technologies.“House Numbers had already done the incredible work of running AI agents in live production for home lenders. Bringing in that proven technology and the team behind it gets agentic AI into our clients' hands faster than building it from scratch, and lenders will see that in better borrower experiences, more productive loan officers and a lower cost of origination.”

Terms of the transaction were not disclosed.

ABOUT HOUSE NUMBERS

House Numbers was founded in 2021 by Jeff Levinsohn, Benjamin Hoffman and Arthur Granado. From 2024, the company focused on using AI to make mortgage origination faster and less expensive for homeowners and lenders, operating as a licensed third-party mortgage processor and building an agentic AI platform that runs AI agents in live production on real loan files, with the controls a regulated industry requires. House Numbers was backed by Resolute Ventures, Maven Ventures and Uncommon Capital, together with more than a dozen angel investors.

ABOUT DARK MATTER TECHNOLOGIES

Dark Matter Technologies is the trusted innovation partner that empowers home lending. As the home of the Empower loan origination solution with its built-in POS and Aiva® Intelligence, the ElevateSM loan servicing solution and the ExchangeSM partner marketplace, Dark Matter moves enterprise lenders and servicers from doing to reviewing with its unified data model and exception-based processing. For more information, visit .

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News Source: Dark Matter Technologies

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