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The problem

Listings, leases, and client conversations are your moat. Don't hand them to a public AI.

Real-estate firms accumulate an enormous amount of high-value private data: comps, off-market opportunities, owner relationships, lease history, NDAs. Putting any of that through a public LLM API turns proprietary information into someone else's training signal — and creates exposure you didn't agree to when you signed the listing agreement.

Listing leakage

Pre-list comps and off-market opportunities going through public AI APIs is a quiet but real risk.

Lease confidentiality

Lease terms and tenant data are subject to NDAs that public LLM TOS rarely match.

Owner trust

Sophisticated property owners increasingly ask whether their data goes through AI. You want to be able to answer "yes — and only AI we control."

Use cases

Three places we typically start.

Every engagement begins with a conversation about your specific bottleneck — but these are the patterns we see most often in real estate firms. Each is a fixed-scope, fixed-fee engagement, typically 4-8 weeks.

Use case 1

Market trend analysis

Private AI that synthesizes comps, market signals, and listing pipeline into deal-specific insight. Closed deals ~30% faster in our reference engagement; increased gross revenue ~15%.

Use case 2

Lease processing automation

AI agent that reads incoming lease documents, surfaces non-standard terms, drafts redlines against your firm's standard form. Saves ~12 hours/week and reduced terms-review errors ~30%.

Use case 3

Client inquiry automation

Inbound buyer / tenant inquiries auto-triaged, qualified, and routed to the right agent with context attached. Improved response time ~40% — meaningful in a market where speed wins listings.

How it works

From first call to deployed system in 4-8 weeks.

Step 1

Bottleneck conversation

30-minute call to understand the specific workflow you want to automate. We tell you whether AI is the right answer — sometimes it isn't, and we say so.

Step 2

Fixed-scope engagement letter

Engagement letter with fixed scope, fixed fee, fixed timeline. No hourly billing, no scope creep, no surprises. Typical range $15K–$35K depending on complexity.

Step 3

Deploy in your environment

System runs in your infrastructure, on your data, behind your access controls. We hand off documentation, training, and a runbook for your team to maintain it.

Curious whether your bottleneck fits?

30-minute call, no pitch. We'll tell you honestly whether what you're describing is a good fit for a fixed-scope AI engagement — or whether you're better off with a different solution entirely.