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About Us

Real estate AI needs
a foundation in fact.

Quoin exists to bring the records behind a property into the tools people use to understand it.

The people behind Quoin

Meet the team.

Kavin Sakthivel

Kavin Sakthivel

Kavin’s background spans commercial real estate underwriting, capital markets, and civil engineering. He has worked on real estate financing at NewPoint Real Estate Capital and Treme-Parker, alongside research into property data, digital infrastructure, and machine learning.

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Jonathan Morris

Jonathan Morris

Jonathan has nearly three decades of experience in public REITs and private real estate, with more than $4 billion in transactions. His leadership roles include VP and Mid-Atlantic Director of Acquisitions at Boston Properties, SVP at Charles E. Smith, and EVP and COO of a Brown Brothers Harriman–owned private REIT.

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Cynthia Mendoza

Cynthia Mendoza

Cynthia has more than 30 years of experience leading technology organizations across government and industry. Her work spans geospatial intelligence, cybersecurity, and enterprise architecture, including senior technology roles at the U.S. Department of State and the National Geospatial-Intelligence Agency.

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A property is one place.
Its records are everywhere.

Understanding a property means piecing together ownership, sales, taxes, permits, and zoning. Those records sit across different public systems, with different formats and different update cycles. Finding the evidence can take more work than asking the question.

AI makes it easier to ask. It does not remove the need for reliable source material. A useful answer still needs a record you can inspect, context for what it establishes, and a clear view of what remains unknown.

That is why we are building Quoin: a grounding layer that connects real estate research to original-source property data. Our aim is to help people spend less time assembling records and more time understanding what they mean.

Our approach

Evidence first. Judgment always.

01 / Traceability

Start with the source.

Property research should lead back to the underlying record. We keep source evidence separate from interpretation so people can examine the basis of an answer.

02 / Clarity

Make the gaps visible.

Public records can lag, disagree, or leave questions open. Coverage, source dates, and missing information matter as much as the data itself.

03 / Practicality

Fit the way people work.

Bring records into an AI assistant or application through our products, or work with us to build a company brain and AI agents around how your team works.

Read our research approach

Build with us

Bring your next
property question.

Property data is live in Washington, D.C. Available records vary by property. Talk with us about your market, research, or workflow.