Real EstateAI implementation case study

Real Estate – Luxury Brokerage (Coastal Markets): Transaction Orchestration AI

AI automation from lead qualification through inspection milestones, title coordination, and closing communications for a luxury brokerage.

This case study documents a real client implementation. Identifying details may be withheld where confidentiality applies.

Key takeaway

PrimeAxiom replaced manual thread-chasing with an AI-orchestrated transaction system spanning people, documents, and calendars.

The engagement

From operational friction to a connected AI system

01 · Context

Business overview

Industry: residential luxury. Size: 140 agents, 4 offices. Complexity: cash deals, 1031, international buyers. Systems: Salesforce, transaction rooms.

02 · Challenge

Core problem

Email silos, manual checklist tracking, no single timeline truth. Bottlenecks at doc collection and title. Revenue risk when deals stalled silently.

03 · Approach

Solution

PrimeAxiom implemented a transaction brain: AI-parsed offer packages, milestone timers, automated stakeholder nudges, and exception escalation to transaction coordinators.

04 · Impact

Results

Missed contingency deadlines −88%; coordinator touches per file −52%; agent NPS +11; time-to-close variance −19%.

System design

The full automation system

The implementation connects triggers, AI decisions, business rules, human approvals, and downstream actions in one controlled workflow.

Canonical transaction object; AI reads contracts and amendments; milestone engine; comms agents with brand voice; dashboard for leadership.

Workflow

How the automation runs

1. Trigger: executed contract upload. 2. AI extracts dates, contingencies. 3. Milestone graph built. 4. Reminders to agents, clients, title. 5. Escalations on SLA breach. 6. Coordinators handle exceptions only. 7. Closed deal analytics improve predictions.

Intelligence layer

AI agents and decision logic

Contract Parse Agent, Milestone Agent, Client Comms Agent, Title Liaison Agent, Risk Alert Agent.

Under the hood

Technical architecture

Node services, Postgres, encrypted doc store, LLM with schema outputs, OAuth to email/calendar.

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