Excuse the subdomainTime is of the essence. I'd rather spend it on your MLS problem than on picking a domain name.
Real estate · Mortgage · Technology
I connect real estate, people, and technology.
Real estate broker and mortgage professional with 13 years of industry experience, a background in building and scaling businesses, and hands-on leadership of AI-assisted technology projects. I turn complex industry needs into practical solutions that protect every stakeholder and help consumers connect with the right home, agent, and financing, faster.
- 13 Years in Real Estate
- Real Estate + Mortgage
- English / Español
- AI & Systems Integration
- Business & Partnerships
Explore the ecosystem
One industry, many hand-offs.
MLS boards, brokerages, agents, lenders, and consumers, joined by data, workflows, and AI. Select a part of the industry to see how it connects.
Executive snapshot
The 20-second version.
Industry fluency, operating experience, and hands-on technology leadership, in one person who can sit on both sides of the table.
- 01
Industry perspective
Brokerage, agents, lenders, and consumers, from the first property search through financing and closing.
- 02
Scale & operations
Built and operated businesses. Led teams, partners, processes, and technology adoption.
- 03
Stakeholder alignment
Brings MLSs, brokers, agents, lenders, and technical teams to the same table, and understands what earns their trust and adoption.
- 04
Bilingual
English and Spanish, with clients, agents, and partners alike.
- 05
Hands-on technology
Directed AI-assisted apps, automations, CRM integrations, servers, databases, and connected tools.
- 06
Technical growth
Continuing formal software and AI engineering education to deepen independent technical skill.
Fluency
I speak multiple languages.
Building a platform for real estate takes more than one vocabulary. Most people are fluent in one or two. Platforms succeed or fail in the translation between them.
These all need to come together to create a solution.
And the two spoken ones: English and Español.
- Bachelor's degreeB.S. Business ManagementWestern Governors University
- Master's degreeM.S. Management & LeadershipWestern Governors University
The graph
Everything is connected.
A living map of my work, in the spirit of an Obsidian vault: 61 notes and 137 links across the industry, my projects, the AI models and harnesses I run, and the systems behind them. Tap any node and follow the links.
Full screen · drag to orbit · pinch to zoom · tap a node
- Freddy
- Experience
- Industry
- MLS concepts
- Projects
- AI models
- Harnesses & runtimes
- Systems & tools
Experience
Built from the inside of the industry.
A career spent where real estate's people, money, and systems meet, and a long-standing interest in how those systems connect.
~13 years
Real estate brokerage
Sales, coaching and training, broker relationships, transactions, operations, and business growth. I know the daily reality of the agents and brokers a platform has to win.
Lending
Mortgage & loan origination
Financing, referral partnerships, the full transaction lifecycle, and the consumer experience between offer and closing.
Ownership
Building & scaling businesses
Founded and operated active businesses; scaled team processes and partner relationships, and led technology adoption across them.
Now
Technology & AI systems leadership
Leading AI-assisted builds at Favor Mortgage, including FavorAI, and connecting CRM, data, automation, and infrastructure into working systems people use.
Education
- Master's degree
M.S. Management & Leadership
Western Governors University
- Bachelor's degree
B.S. Business Management
Western Governors University
Next
Planning to pursue an M.S. in Software Engineering (AI Engineering) at WGU; an introductory Python prerequisite is underway.
Selected work
Systems I’ve conceived, directed, and put to work.
Six case studies from running real businesses. Each one shows the problem, the approach, my exact role, and what it changed. I define the problem and direct the build; AI tools and collaborators write much of the code.
Tech stack
Tools we’ve worked with, honestly labeled.
Grouped by what each tool does for the business, including the AI models we route between and the agent harnesses they run in. The labels show how deep my involvement goes, so nothing implies expertise I haven't earned.
Select a label to highlight it across every group.
AI models we route between
12The right model for each job, chosen by code, not habit
- Claude (Opus, Sonnet)(Designed / Directed)
- OpenAI GPT / Codex(Designed / Directed)
- Google Gemini(Designed / Directed)
- DeepSeek(Designed / Directed)
- GLM(Designed / Directed)
- MiniMax(Designed / Directed)
- Mistral(Worked With)
- Jev classifier(Designed / Directed)
- Qwen (local, private data)(Designed / Directed)
- Whisper speech-to-text(Worked With)
- Embedding models(Worked With)
- Grok (in progress)(Currently Learning)
Agent harnesses & runtimes
11Where agents actually run, review, and hand off work
- Claude Code(Designed / Directed)
- Codex CLI(Designed / Directed)
- Paperclip (multi-agent)(Designed / Directed)
- OpenCode(Designed / Directed)
- Hermes (voice & messaging)(Designed / Directed)
- MCP servers(Designed / Directed)
- CodeRabbit(Worked With)
- Antigravity(Worked With)
- OpenRouter(Worked With)
- Ollama(Worked With)
- MLX · llama.cpp(Worked With)
Apps & languages
05The web products people touch
- Web apps(Designed / Directed)
- Next.js(Worked With)
- TypeScript(Worked With)
- JavaScript(Worked With)
- Python (beginner)(Currently Learning)
Data & integration
04How information moves between systems
- REST APIs(Worked With)
- Webhooks(Worked With)
- PostgreSQL(Worked With)
- Supabase(Worked With)
CRM & automation
05Where agents, lenders, and clients connect
- HighLevel(Designed / Directed)
- Follow Up Boss(Designed / Directed)
- Email & messaging workflows(Designed / Directed)
- n8n(Worked With)
- Twilio(Worked With)
Deployment & infrastructure
09What keeps it running
- Apple Silicon fleet(Designed / Directed)
- GitHub(Worked With)
- GitHub Actions(Worked With)
- Vercel(Worked With)
- Linux VPS(Worked With)
- SSH(Worked With)
- Tailscale(Worked With)
- NAS(Worked With)
- Local AI hosting(Worked With)
Formal study
02Deepening independent technical skill
- Software engineering fundamentals(Currently Learning)
- AI engineering(Currently Learning)
“I define problems, select architectures and tools, direct implementations, and test outcomes; AI tools and collaborators produce much of the underlying code.”
Conceptual perspective · not a shipped system
The opportunity isn't just unified listings. It's unified workflows.
Connecting multiple MLS organizations comes down to one outcome: helping agents and consumers connect with confidence. That depends on data quality and synchronicity across every board, and on protecting the stakeholders whose rules, relationships, and trust make the system work. Here is how I think about it, and the questions I'd bring to the table on day one.
Why it matters
Data quality and synchronicity are the experience.
When every board's data is accurate and in sync, every stakeholder wins, and the consumer feels it first.
Consumers
Listings they can trust: accurate status, current price, clear source. Fewer dead ends and a faster path to a showing and to financing.
Agents
Time spent with clients instead of correcting data or explaining stale listings. One reliable view across every market they serve.
MLSs & boards
A better member experience, while keeping control of their rules, licensing, and stewardship of their data.
Brokers & lenders
Transactions that move faster with fewer surprises, and consumer relationships built on data everyone agrees on.
Stage 01
Multiple MLS sources
Each board publishes on its own schedule, with its own fields, status values, and geographic coverage. The platform has to respect each source as it is.
A question I’d bring on day one
“Which boards anchor the first market, and how often does each one update?”
What makes this hard
- 01A single listing can appear across systems; identity matching and deduplication matter.
- 02Sync frequency and event handling directly shape user trust.
- 03Permissions, display rules, and source attribution vary by board.
- 04Field-level differences, statuses, and coverage areas matter.
- 05Success depends on MLS relationships, stakeholder trust, and adoption, not engineering alone.
“I can help translate between the MLS ecosystem, brokerage operations, mortgage workflows, and the team building the platform, so every stakeholder is protected and every consumer is better served.”Start the conversation
Where I add value
The bridge between the industry and the build.
Stakeholder relationships
MLS, broker, agent, referral partner, lender, and consumer perspectives, built through years of doing the work and protecting those relationships.
Product discovery
Requirements gathered from real practitioners, not assumptions, and translated into priorities builders can act on.
Adoption & scale
Market-entry playbooks, partner development, and the training and support workflows that make rollout stick.
Technical translation
Product requirements, integration mapping, and steady coordination between builders and stakeholders.
Roles I’m interested in
- Strategic Product & Industry Partnerships
- Real Estate Technology Integration
- AI Product Implementation
- Platform Adoption & Ecosystem Development
About
“Technology has always been a passion of mine. My career took me through sales, real estate, mortgage lending, and entrepreneurship. Over time, advances in AI-assisted development gave me powerful ways to combine my industry knowledge with my interest in how systems connect. Today, I'm pursuing the technical depth to complement years of practical business leadership, so I can help design and scale products that solve meaningful industry problems.”
Freddy Baez
What I'm looking for
To be part of something that leaves a legacy: protecting the stakeholders who built this industry, and helping it evolve for the consumers it serves.
Real estate runs on relationships, local rules, and trust that took decades to earn. The next generation of platforms should strengthen that foundation: higher-quality data, in sync across every market, so agents can serve better and consumers can connect faster. I want to help build the platform that does both.
Connect
Let's discuss your vision.
If you're connecting MLS markets to give agents and consumers a better experience, I'd welcome a conversation about where stakeholder relationships, data quality, and adoption can move the platform forward.
Contact details are being finalized.