Case Study 01
Portfolio build — a complete, working system built and measured by Altus Initiatives to demonstrate this capability. Performance metrics below are measured from the build; agency-impact figures are projected for a representative brokerage.
For any agency that depends on inbound leads, the window between a lead arriving and a response going out is where deals are won or lost. Most brokerages handle this manually — someone reads the inquiry, figures out what the person wants, decides how urgent it is, routes it to the right place, and drafts a reply. Done carefully, that process takes 5–10 minutes per lead. Done under pressure, things get missed.
At 20–30 leads per week, that's hours of repetitive work — performed inconsistently depending on who's available, what time it is, and how stretched the team already is. A high-intent buyer who submits an inquiry at 5pm Friday gets the same treatment as a general question that arrives Monday morning: delayed, manual, and variable.
The deeper problem is prioritization. Without a system, every lead looks identical until someone reads it. Urgent, high-intent prospects sit in the same inbox as routine inquiries — and the team has no mechanism to know which to act on first.
Every inbound lead is now classified, routed, and responded to in under 3 seconds — automatically, consistently, and without anyone on the team having to manage the process.
When a lead submits an inquiry, the system activates immediately and completes the following sequence:
3 seconds
from inquiry submission to full classification, routing, and draft response — replacing a process that previously required manual reading, triage, and response drafting.
For a brokerage receiving 20–30 leads per week, that recovery represents 2–5 hours of agent time returned to client-facing work every week.
The system follows a linear trigger-classify-route-log pattern, with a parallel urgency check running independently of intent routing:
Inbound Lead Submission
│
▼
AI Classification (Intent + Urgency)
│
├──── Intent Router ───────────────────────────────┐
│ │ │
│ ┌────┴─────┬──────────┬──────────┐ │
│ ▼ ▼ ▼ ▼ │
│ Hot Partners Support General │
│ Leads Queue (logged) │
│ Queue │
│ │
├──── Urgency Check ───────────────────────────────┤
│ │ │
│ High Urgency? ──Yes──► Immediate Notification │
│ │
└──── Master Log (all leads) ◄─────────────────────┘
│
▼
Draft response saved per lead
Full architecture documentation available upon engagement.
| Component | Tool |
|---|---|
| Workflow automation | Make.com |
| AI classification and response drafting | Anthropic Claude Haiku |
| Lead intake | Google Forms |
| Lead routing and logging | Google Sheets |
| Urgency escalation | Slack |
Right-sized AI for the task. Classification does not require a frontier-class model. A faster, leaner model was selected for this workflow — delivering accurate intent and urgency classification at a fraction of the cost, with response times under 3 seconds. Selecting the right model for the job is part of how Altus keeps systems efficient and cost-effective in production.
Human review before client-facing delivery. The system prepares a draft response but keeps a human in the loop before anything is sent. This is intentional. The value is eliminating the blank page and the research step — not removing human judgment from client communication. Especially in real estate, where relationships are the business, that distinction matters.
Intent and urgency evaluated independently. A support request can be high urgency. A buy inquiry can be standard priority. Running the urgency check as a separate dimension from intent routing ensures no high-urgency lead is missed regardless of how it's classified — a design decision that prevents the edge cases that break manually built systems.
This is the same architecture we build for clients. The first step is a 30-minute discovery call — no pitch, no commitment.
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