Zeitro: 1st AI-native Mortgage Brokerage End-to-end Solutions

Zeitro, 1st all-in-1 platform powered by AI, reduces manual work, automates applications and safeguards private data throughout mortgage brokerage process.

NY, UNITED STATES, March 17, 2025 /EINPresswire.com/ -- The mortgage brokerage industry stands as a critical pillar of the US economy, especially since 2008, when brokers were found selling home loans to high-risk borrowers for personal gain, accelerating the financial crisis. With recent advancements in big data and Large Language Model (LLM), AI now serves as an unbiased intermediary that reduces information asymmetry and safeguards private data, re-boosting the industry growth. Currently valued at over $102 billion in 2024, the market is projected to reach nearly $152 billion by 2028. The integration of AI in risk assessment and cybersecurity largely revolutionizes the financial system. Zeitro emerged as the 1st AI-native platform, streamlining the entire mortgage origination process for borrowers, brokers, and underwriters.

We interviewed Ying Chen, who leads Zeitro's AI Business Strategy, after coming across her article "How AI Would Reshape the Future Mortgage Brokerage Industry" and her speech at leading industry conferences. She explained that Zeitro was created to leverage AI in addressing inefficiency, non-transparency, and inaccuracy throughout the mortgage lending process: their marketplace connects consumers with loan officers; their auto calculator interprets and analyzes user data; GuidelineGPT provides real-time guidelines and answers questions; their AI document processor prepares files for approval; and their CRM system helps to track sales and leads. Unlike traditional companies that typically focus on specific services due to the high operational costs of manual processing, Zeitro stands as the first and only provider of comprehensive end-to-end AI solutions that reduce costs and enhance efficiency in a single platform.

The company also provides extensive free training and educational resources for novice brokers, along with accessible APIs designed specifically for SMBs. "Since implementing Zeitro's solutions, we've cut $1.2M in annual technical expenses, shortened training time by 90%, and processed applications 30 times faster than human processing. This enabled us to expand rapidly from 250 to 600 loan officers within 6 months and achieve immediate improvements in conversion rates and revenue," reported the manager of GMCC, a leading mortgage lender in the Bay Area.

Currently, mortgage borrowers can only get estimated rate quotes from a third party and then contact individual brokers outside the platform, also, personal information cannot be securely stored and synchronized across different brokers, applications must be submitted multiple times. So Zeitro recently launched a new marketplace at https://www.my-mortgage-rates.com/home that directly connects borrowers with brokers online, allowing people even in remote areas to access accurate, personalized, competitive rate offerings without location or time constraints, thanks to 24/7/365 AI-powered assistance and seamless real-time quoting systems driven by machine learning.

In closing, Ying emphasized, "We firmly believe that AI isn't here to replace mortgage brokers—it's here to empower them. With AI handling automated data collection and processing, brokers can reach more consumers, deliver personalized services, secure sensitive information, and complete applications faster with fewer error risks. AI will only replace those brokers who refuse to embrace technology, while those who adapt will secure a significant competitive edge." Established players in the mortgage industry such as LendingTree (valued at $650M, listed on Nasdaq) and ICE Mortgage Technology are generating substantial values and supporting over 1 million loan officers nationwide, whereas Zeitro, positioned to become the next breakthrough success in the AI era, aim to revitalize the whole industry through advanced technology to serve a larger audience with greater efficiency.

Shunxin Pang
HashMatrix
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