Episode 27: Kully Koomer - Breaking Down Data Silos with AI Intelligence
In an industry drowning in data but starving for insights, host Kelly Yale sits down with Kully Koomer, founder and CEO of Lamata, to explore a problem that keeps mortgage executives up at night: how do you make sense of information scattered across dozens of disconnected systems? With over 25 years of experience leading technology strategy at giants like Cisco and Salesforce, Kully brings an outsider's perspective to an industry he describes as "bravely taking on." But this isn't another conversation about the promise of technology—it's about why so many of those promises have failed to materialize, and what's actually different this time.
The conversation opens with a candid acknowledgment of an uncomfortable truth: the data industry has been selling the same dream for years. Bring us your data, they say. We'll consolidate it into data lakes and warehouses, and all your answers will magically appear. Except they don't. Kelly and Kully dive into why companies are left with vast repositories of information but still can't answer basic questions like "which mortgage offerings give us the highest margin?" The discussion reveals a fundamental disconnect between the people who build data platforms and the people who understand what the business actually needs—a gap that has cost the industry dearly in missed opportunities and inefficiency.
What makes this episode particularly compelling is Kully's exploration of what an "AI business agent" actually means beyond the buzzword. Rather than offering vague promises about artificial intelligence, he breaks down the practical reality of how automation can eliminate the 90% of manual work that most mortgage professionals spend gathering, analyzing, and organizing data into spreadsheets. But the real intrigue comes when Kelly poses seemingly simple questions—like how many loan officers are licensed in California—and the conversation reveals just how difficult these answers are to obtain in real-time. The implications ripple outward: if you can't answer basic operational questions quickly, how can you possibly make strategic decisions with confidence?
The discussion takes an unexpected turn when exploring the messy reality of mortgage technology stacks. Kelly's frustration is palpable as she describes companies juggling multiple loan origination systems, various CRMs, different point-of-sale platforms, and separate tools for accounting, HR, and compliance. Kully's response introduces a philosophy that challenges conventional wisdom: rather than forcing companies to rip out and replace their existing systems, what if technology could be "additive, not disruptive"? This concept of creating an intelligent data layer that sits across fragmented systems promises something the industry has long sought but rarely achieved. But how does it actually work, and can it deliver on promises where others have failed?
The conversation ventures into territory that should concern every mortgage executive: the dangerous silos that exist between departments. When marketing doesn't understand what technology is implementing, or when tech teams sign multi-year vendor agreements in bubbles disconnected from broader business strategy, companies make expensive mistakes. Kully begins to map out how AI can connect operational data to strategic initiatives, revealing patterns and opportunities that remain invisible when departments operate in isolation. The mention of partnerships with platforms like Workday hints at a level of integration that goes far beyond traditional business intelligence tools like Tableau or Power BI.
As the discussion builds toward its conclusion, listeners are left contemplating a provocative question: what happens when you can finally ask your data anything and get accurate, real-time answers grounded in your specific business context and rules? From C-suite executives forecasting six-month revenue projections to loan officers understanding their pipeline, the promise of unified intelligence across fragmented systems represents a fundamental shift in how mortgage companies could operate. Whether you're skeptical of yet another technology promise or desperate for a solution to data chaos, this conversation offers a candid look at what's actually possible—and what questions you should be asking about your own organization's ability to make data-driven decisions.
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