Document and site diligence
Summarize, classify, retrieve, and compare key facts from offering memoranda, site plans, leases, zoning notes, studies, and internal checklists.
Real estate & development
AI-assisted real estate analysis for faster, clearer development decisions.
For development and real estate teams, we turn deal documents, site constraints, assumptions, comps, market notes, and scenario changes into workflows that keep facts, assumptions, and judgment visibly separate at every step.
Focus
diligence · scenarios · documents
Risk lens
assumptions · sources · review
Output
repeatable analysis workflows
What deal teams actually need
Real estate decisions depend on scattered material: offering documents, leases, zoning context, site constraints, market notes, comps, cost assumptions, entitlement questions, and meeting memory. The job is to make that material easier to interrogate when the deal moves.
A model isn't there to make the investment call. It's there to move you faster through diligence while facts, assumptions, scenario changes, and human judgment stay visibly separate.
Services that fit deal and development work
AI strategy and roadmapPrioritize AI workflows across acquisitions, diligence, development, reporting, and internal knowledge.LLM, RAG, and evaluation systemsCreate retrieval and evaluation around documents, assumptions, source quality, and real deal questions.AI agents and automationDesign workflows for document intake, research packets, scenario updates, and review-ready summaries.
Use cases
Places diligence gets easier to review.
Scenario and assumption tracking
Make changes to assumptions visible across scenarios so teams can understand what changed and why the conclusion moved.
Market and comparable research
Prepare research packets that separate sources, notes, assumptions, and analyst judgment.
Decision memos and reporting
Turn diligence findings into consistent summaries, open-question lists, risk notes, and review-ready materials for internal stakeholders.
Where analysis loses credibility
The system gets risky when it blends facts with assumptions, hides source uncertainty, or makes a scenario look more precise than the underlying data deserves. Sources, assumptions, and human judgment have to stay visibly separate, every time.
That is why evaluation matters. A useful workflow should be tested against real deal questions, known edge cases, and internal review expectations before it becomes part of acquisition or development decisions.
Answers
Questions real estate teams usually ask first.
Where does AI fit in diligence?
Organizing diligence, summarizing documents, comparing scenarios, tracking assumptions, researching market context, and preparing review-ready decision materials.
Can AI replace underwriting judgment?
No. AI should support diligence and analysis, not replace professional judgment. Strong systems make assumptions and sources easier to inspect.
What data is useful?
Offering memoranda, zoning notes, leases, site plans, market research, comparable data, cost assumptions, entitlement notes, meeting notes, and internal templates.
What should be in hand at the end?
A diligence workflow, document retrieval plan, analysis templates, assumption tracking, scenario review process, evaluation notes, and handoff guidance.
Next step
Have a development workflow that should be easier to repeat?
Bring the diligence pattern, document set, or decision memo that needs a clearer process.