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What if the most powerful tool in real estate wasn’t a bulldozer or a checkbook—but a clear, fast answer to “What can I really build on this land?”
We sit down with Whitney Blanco, founder and CEO of Acreage AI, to explore how AI turns zoning, policy, comps, infrastructure plans, and even public sentiment into an actionable feasibility playbook. A former civil engineer and global public-health strategist, Whitney calls herself “a humanitarian who does real estate,” and shows how clarity up front prevents costly, infeasible plans down the line.
We dig into building a company the scrappy way—selling useful reports, iterating with customers, and proving value before seeking capital—while confronting the funding gap women (and especially Black women) face. Along the way, we rethink due diligence: fewer blind spots, faster timelines, and better decisions without replacing expert judgment. If you’ve ever wondered what your land can really support—and how to get from maybe to go—this conversation delivers.
Resources:
Connect with Our Hosts
Emerick Peace:
Daniel Dixon:
Julia Lashay:
Bo Menkiti
Produced by NOVA
This podcast is for general informational purposes only. The views, thoughts, and opinions of the guest represent those of the guest and not Keller Williams Realty, LLC and its affiliates, and should not be construed as financial, economic, legal, tax, or other advice. This podcast is provided without any warranty, or guarantee of its accuracy, completeness, timeliness, or results from using the information.
Any text or materials generated by artificial intelligence (AI) should be reviewed for accuracy and reliability as there may be errors, omissions, or inaccuracies. The use of generative AI is subject to limitations, including the availability and quality of the training data used to train the AI model used. Users should exercise caution and independently verify any information or output generated by the AI system utilized and should apply their own judgment and critical thinking when interpreting and utilizing the outputs of generative AI.
4.9
3030 ratings
What if the most powerful tool in real estate wasn’t a bulldozer or a checkbook—but a clear, fast answer to “What can I really build on this land?”
We sit down with Whitney Blanco, founder and CEO of Acreage AI, to explore how AI turns zoning, policy, comps, infrastructure plans, and even public sentiment into an actionable feasibility playbook. A former civil engineer and global public-health strategist, Whitney calls herself “a humanitarian who does real estate,” and shows how clarity up front prevents costly, infeasible plans down the line.
We dig into building a company the scrappy way—selling useful reports, iterating with customers, and proving value before seeking capital—while confronting the funding gap women (and especially Black women) face. Along the way, we rethink due diligence: fewer blind spots, faster timelines, and better decisions without replacing expert judgment. If you’ve ever wondered what your land can really support—and how to get from maybe to go—this conversation delivers.
Resources:
Connect with Our Hosts
Emerick Peace:
Daniel Dixon:
Julia Lashay:
Bo Menkiti
Produced by NOVA
This podcast is for general informational purposes only. The views, thoughts, and opinions of the guest represent those of the guest and not Keller Williams Realty, LLC and its affiliates, and should not be construed as financial, economic, legal, tax, or other advice. This podcast is provided without any warranty, or guarantee of its accuracy, completeness, timeliness, or results from using the information.
Any text or materials generated by artificial intelligence (AI) should be reviewed for accuracy and reliability as there may be errors, omissions, or inaccuracies. The use of generative AI is subject to limitations, including the availability and quality of the training data used to train the AI model used. Users should exercise caution and independently verify any information or output generated by the AI system utilized and should apply their own judgment and critical thinking when interpreting and utilizing the outputs of generative AI.
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