Alta Mira Realty
A Southern California real estate investment and development brokerage
How we did it: Knowledge first, then the algorithm ↓Business
Buys, develops, rehabilitates and sells 1 to 4 unit homes, and manages rentals
Based in
Southern California
Founder
David Mirrafati, who established the business in 1995
Our role
AI and technology partner
Where they were
When we started
- An AI outreach system from an earlier vendor produced activity, but not the results the brokerage needed.
- Broad, untargeted outreach to thousands of properties, with AI call minutes spent on unqualified leads.
- Generic algorithms that ignored the brokerage's market and its own way of judging a property.
- No connection to the team's daily workflow, so the system created more work instead of less.
Where they are now
Today
- AI that follows the brokerage's own decision rules.
- The sales team spends its time on high-probability opportunities.
- No AI minutes wasted on unqualified prospects.
- Transparent lead scoring that management and staff both trust.
Measured results will appear here once Alta Mira Realty approves publishing them.
What we did
The work, step by step
- 01
Started with the people, not the software
Deep-dive sessions with the brokerage's most experienced people to capture how they decide which properties are worth pursuing.
- 02
Turned that expertise into an algorithm
A proprietary scoring model that weighs renovation potential, scope, timeline and after-repair value against comparable sales, so only high-probability prospects reach the sales team.
- 03
Connected it to the CRM
One source of truth for lead data, with dashboards where management and staff see the same scores and the reasons behind them.
- 04
Built for the way the brokerage already wins
The system follows the team's workflow and referral network instead of forcing a new one.
How we did it · Knowledge first, then the algorithm
Building AI around how their best people decide
The brokerage had already tried an AI outreach system built by another vendor. It produced activity, not results. We did not start by automating more activity. We started by understanding expertise: sessions with the brokerage's most experienced people to capture how they decide which properties are worth their time, then turning that judgment into a model the whole team can see.
We did not start by automating activity. We started by understanding expertise.
What the model weighs, and where it lives
- 01
Renovation potential
Structural feasibility, cost and market fit for each property.
- 02
Scope and timeline
The scope of work, timeline and contractor availability in the target areas.
- 03
After-repair value
Projected value from comparable sales, market trends and neighborhood data.
- 04
Only strong prospects reach sales
High-probability opportunities go to the team; the rest are filtered out.
- 05
One source of truth
Lead data lives in the CRM, with no silos between tools.
- 06
Transparent dashboards
Management and staff see the same scores and the reasons behind them.
The outcome
From broad automation to knowledge-based AI
AI works when it wraps around the way a business already wins. The brokerage now has a system built from its own expertise, inside the workflow its team already uses.
- Sales time spent on high-probability opportunities
- No AI minutes spent on prospects that do not fit
- Scoring the team understands and trusts
People
Who we work with
David Mirrafati
Founder, Alta Mira Realty
AI and technology partner, Medai Digital
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