AI for Real Estate:
Spend Less Time on Admin, More Time on Deals.
88% of CRE investors and owners are piloting AI — but most lack a structured approach to move from experimentation to results. The ones pulling ahead are the ones who know how to use it. Kiingo delivers AI enablement built for real estate workflows, from principals to analysts.
What Your Team Could Do with AI
Market Research
Pull recent transactions, surface pricing trends, and build a submarket brief your team can actually present — turning hours of data work into a 10-minute workflow.
Rental Analysis
Compare asking vs. achieved rents across property types and markets — and walk into every negotiation knowing exactly where the spread is.
Lease & Contract Review
Extract key terms, flags, renewals, and obligations from PDFs in minutes — not hours of manual review.
Comparable Search
Structure your comp data into a formatted set with rationale and gap analysis — so every number you present has a story behind it.
Data Compiling
Combine data from your research platforms, public records, and internal notes into one clean brief your team can actually use.
Narrative Creation
Turn raw numbers into client-ready talking points, investor memos, and deal summaries — so your team spends time on strategy, not formatting.
How could your team start using AI for this?
CRE AI Prompts You Can Try Today
Want to learn how to set up AI safely, with proper context and configuration? Talk to us about joining a bootcamp.
These prompts are designed to work with AI tools your firm has approved for use with deal documents. Before pasting leases, estoppels, or DD materials into any AI tool:
- Confirm the tool is on your firm's approved technology list
- Check whether your firm's AI policy requires confidential deal data to be redacted before input
- Review the AI tool's data retention and training policies — some tools use your inputs to train their models
- For NDA-covered documents, verify that third-party AI processing is permitted under your confidentiality agreements
Don't have a firm AI policy yet? That's one of the things we help with.
[Paste your commercial lease here — redact as required by your firm's AI usage policy.] Extract these terms: tenant name, premises address, square footage, lease start and expiration dates, base rent and escalation schedule, renewal options, termination clauses, CAM responsibilities, any co-tenancy or exclusivity provisions, and landlord concessions. Flag anything unusual — above-market concessions, one-sided termination or kick-out clauses, or missing estoppel language. Return as: (1) a single-page term sheet with each term on its own line, (2) a "red flags" section listing anything non-standard or potentially unfavorable, and (3) a list of follow-up questions I should raise with the landlord or tenant before signing. Use plain language — this needs to be readable by someone who isn't a real estate attorney.
Turns a lengthy lease review into a quick scan — with a flagged term sheet ready before your next client call.
[Paste your commercial lease and the corresponding tenant estoppel certificate here — redact identifying details as required by your firm's AI and confidentiality policies.] Compare them line by line across these dimensions: current rent amount, lease expiration date, renewal option terms, security deposit held, landlord obligations outstanding, and any tenant claims or offsets. Identify every discrepancy, no matter how small. For each mismatch, specify: (1) the exact clause or section number in each document, (2) what the lease states vs. what the estoppel claims, (3) the potential financial or legal exposure if the discrepancy goes unresolved. Then provide a summary table of all discrepancies ranked by severity (high / medium / low) and a recommended next step for each — whether to request a correction, seek legal review, or flag for the buyer's counsel before closing.
Catches the mismatches that blow up deals at the closing table — before they become your problem to explain.
I'm evaluating a [asset type, e.g., 120-unit multifamily / 45,000 SF retail center / single-tenant NNN industrial] property for [acquisition / refinance / disposition]. The deal structure is [all-cash / leveraged / JV partnership]. Known considerations include: [list any specifics — deferred maintenance, environmental concerns, lease rollover concentration, zoning changes, etc.]. Build a due diligence checklist customized to this deal, organized by category: (1) Financial — rent rolls, operating statements, tax returns, CAM reconciliations, (2) Legal — title, survey, zoning, entitlements, existing litigation, (3) Physical — property condition report, environmental Phase I/II, capital expenditure needs, (4) Tenant — lease abstracts, estoppels, tenant creditworthiness, (5) Insurance — current policies, coverage adequacy, claims history, flood zone and hazard status, (6) Market — submarket comps, vacancy trends, rent growth projections. For each item, indicate priority (critical / important / nice-to-have), the typical source document, and a red flag to watch for. Format as a printable checklist my team can use to track progress.
A deal-specific checklist in 30 seconds — customized to your asset type, structure, and known risks.
All prompts should be used in accordance with your firm's AI usage policies and any applicable confidentiality or NDA provisions. AI outputs are starting points requiring professional review — they do not replace legal counsel, licensed appraisals, or completed due diligence.