Perspectives on AI, technology, and compliance transformation to help you move faster, smarter, and with more clarity.
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By Tela Mathias, Chief Mad Scientist at PhoenixTeam
We’ve been in the lab for the past few weeks tackling the agent problem and today it really started to connect. I’ll start with a reminder about what an agent is. The foundation of agentic AI is its ability to reason. An AI agent is characterized by the ability to perceive and understand context, reason about a problem, plan and take action, and use tools.
The agent problem, of course, is understanding and rapidly deploying… agents. Why does this matter? This matters because it is a huge unlock in time to value. When we master agents, we eliminate (or at the very least drastically reduce) reliance on coding for solution delivery. And that means we can move at a blistering pace.
We believe that in the AI future, both the front end and the backend of solution delivery are commoditized. There is no moat in foundation models (the “backend”), and anything we can image, we can build (the “frontend”). So what, then, are the differentiators? Original thinking and vertical industry expertise. We believe that in the future (which is happening now, by the way), there is a new formula for differentiation.
Differentiation = Original Thinking + Domain Expertise + Fast Scale
Considering this, we’ve been in the lab working on going “concept to cash” (idea to production value realization), in five days. Imagine if you could have an idea on Monday, and see it through to production by Friday? Wouldn’t that be amazing? I know this is possible. I can’t say we’ve got it quite down to five days, but we are not that far off. What if we could pick an agentic use case from a menu, and have that use case up and running within a week? For that matter, what if it was two weeks? Certainly, way better than how long it takes to get stuff into production in a more classic approach.
I still love classic, don’t get me wrong. We have plenty of customers where we work with AI accelerators to deliver software using traditional agile scrum, with continuous discovery and continuous delivery. That is very much still a thing. But there is another way too, and a way that will become a massive differentiator for those clients boldly willing to go where no one has gone before.
So you are thinking – “yes, let’s go!”. Well, hold on a minute. The tooling isn’t there yet. Where it is there, it doesn’t scale. The accelerators are nascent, and connecting the front end to the back end is still a long way off from “push button get software”. But it’s coming, and it’s coming fast. Things like model context protocol (MCP) will ultimately make building agents like building with Legos. The pieces are all there and you just snap them together. Voice agents will create the ability to do customer discovery at scale in, like, a morning. Coding agents are already accelerating development.
The human side of this is interesting and has to be cared for. There is a lot of fear. Jobs are changing. The things we have to know how to do come with a really steep learning curve and not all of us are ready. I talk often now about what this means to my kids. This generation will be the last that was born before ChatGPT. They are also the unique set of children that had a critical time in their lives and learning utterly disrupted by covid. They will engage with the world and learn in fundamentally different ways. The education systems are not changing fast enough, which puts the burden on parents. We are the ones that have to help our children adapt. And we don’t even know what that means so it’s a bit of the blind leading the blind.
The agents are here, and they are coming for our kids.
I have to just acknowledge how scary that is. I do worry. I worry about my oldest at 22, and my youngest at seven (and everyone in between, my nine and eleven year olds). But we really don’t have a choice. The future is coming and the only way out is through.
For existing professionals, it is also scary out there. Will I be replaced? They way I mastered my craft is not the way anymore. Is my craft even still relevant? The reason I know anything about subservicing is because I spent three years photocopying checks in the second subbasement of HUD in conjunction with litigation support for a federal case against a Ginnie Mae master subservicer whose assets were seized by FDIC. That was 1998 and even then it was old (they were raided by the FBI in the early 1980s).
As much as I came to hate this job, gosh did I learn a lot. Precision. Attention to detail. Escrow account commingling. 11710A monthly reporting. A goldmine really, still useful today. This is simply not a job anyone will do in the AI future. Agents will sift through massive quantities of structured and unstructured and structured data, decide what needs to be done, and do it. How will new professionals learn these things? Does it even matter? What do they have to learn?
I had a fascinating conversation with a senior executive talking about interns last week. They have their interns learning to do things “the classic way”. Stare and compare. Good old fashion math and analysis. This is a valid approach, but it is not the one we are taking. We have our interns living in the AI future. We are paying them to learn, explore, try, and fail fast – all using “the now way”. I have no idea if this is “right” but it’s the path we chose. For now?
I choose to see the sunny side of this, and really I try to see the sunny side of all things. The alternative is depression and despair, and I don’t want to live like that. We all survived the internet, and we will survive this. Those of us who are out in front will pave the way for everyone else. It’s bumpy and painful but it’s better than being bored.
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We’re proud to announce the launch of our PhoenixTeam new website. PhoenixTeam has always been about more than just delivering technology solutions. We exist to drive meaningful transformation in the industries that matter most: mortgage, financial services, and federal modernization. Our new digital home reflects exactly who we are today and where we’re taking our clients tomorrow.
Technology is evolving faster than ever. We don’t just adapt, we lead. Our new site highlights how we help organizations harness the power of AI to transform operations, decision-making, and customer outcomes. From AI strategy to hands-on implementation, we’re helping clients unlock faster, smarter, and more resilient ways of working.
We have deep roots in both federal and commercial sectors, especially in mortgage, financial services, and complex technology product delivery. The new website makes it easy to see how our experience spans mission-critical programs and innovation-driven growth initiatives and why we’re the trusted partner when the stakes are high.
We organize our expertise around the critical areas where transformation is happening fastest. Through specialized hubs, we deliver practical, AI-native solutions across industries: Our hubs include GenAI Services, Technology Delivery and Transformation, Technology Product Management, Mortgage Data Services, and Federal and Commercial Go-To-Market Support each built to accelerate results where they matter most. In partnership with the Mortgage Bankers Association, we also offer hands-on AI education programs to help teams lead with confidence in an AI-driven world.
On our new site, you’ll see how Phoenix Burst is changing what’s possible for business process fulfillment. Phoenix Burst is our genAI technology product designed to fulfill business processes, not just track them. Unlike traditional workflow tools, Burst delivers real outputs for human validation, accelerating operations across compliance, software development, and compliance decision-making.
Technology is just the start. The new PhoenixTeam website isn’t just about showcasing our services, it’s about reflecting the culture that drives everything we do. We’re a team of strategists, AI technologists, and builders who move fast, lead with purpose, and put people at the center of every transformation. We invest in growth, innovation, and solving the problems that move industries forward.
The industries we serve are changing...FAST. PhoenixTeam is here to help you move faster, smarter, and with more clarity. Whether you’re navigating AI disruption, federal mandates, mortgage modernization, or simply building the next phase of your tech strategy, we’re ready.
Connect with us to start building what’s next.
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Phoenix Burst, the industry’s first genAI-native mortgage business process fulfillment platform, has been named a winner of the MortgagePoint Tech Excellence Award, recognizing the most innovative technology providers transforming the mortgage and real estate industries.
For decades, efforts to modernize the mortgage industry have been stalled by the heavy burden of regulatory compliance. Phoenix Burst changes that. By making compliance seamless, the platform clears the way for real innovation. What once took months of legal, compliance, and operations coordination, Phoenix Burst now delivers in hours, turning complex regulatory updates into clear, actionable requirements, user stories, and test cases with a single click.
The MortgagePoint Tech Excellence Award honors companies that are not only pushing the boundaries of what’s possible through technology, but also meaningfully improving operational efficiency and the mortgage experience. Winners are selected based on nominations from industry professionals and judged on their impact, innovation, and ability to drive lasting change.
See the full list of award recipients: https://themortgagepoint.com/2025/03/31/mortgagepoint-announces-2025-tech-excellence-award-recipients/
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I’ve talked before about how managing regulatory change in mortgage is kind of like trolling the internet. Mortgage compliance requirements are primarily published in formats suitable for human readers, not machines. The requirements span hundreds of entities, including federal bodies, state attorneys general, investors, federal and local housing agencies, and the government sponsored enterprises (GSEs), with each providing requirements in diverse formats through multiple, inconsistent distribution channels. According to the National Mortgage News, this has created more than 1,000,000 pages of requirements overt time. Yikes.
We envision compliance as a wheel, with change at the center and evidence of process compliance as the enveloping outer ring. The change kicks off a cascading process that can take anywhere from 45 days to 18 months, depending on the size and complexity of the change.
There is never time to test everything, and compliance and line of business operators ship around copies of an excel spreadsheet to analyze and communicate the requirements. Engineering teams create Jira and ServiceNow tickets to track the development work, and a testing team somewhere might test a subset of the change before production. Mortgage companies then rely on first, second, and third line of defense to actually provide evidence of process compliance at the enterprise and loan levels. There is an alternative to this insanity.
Definition: AI-ready data is structured, consistent, high-quality information that has been cleaned, properly formatted, and labeled to be immediately usable for training or analysis by artificial intelligence systems without requiring significant preprocessing or transformation.
The emergence of generative AI (GenAI) in the mortgage industry present previously unattainable opportunities for automating compliance, risk assessments, and underwriting processes. However, AI systems require structured, standardized data to operate effectively. Current unstructured formats severely limit AI’s accuracy and usability. Our tests for Phoenix Burst have shown that structured regulatory data dramatically improves AI accuracy. We can achieve up to 79% accuracy using image-based formats contrasted with nearly 100% accuracy with structured inputs.
The people who make the requirements have both the authority and motivation to lead the shift to AI-ready data. Standardized, open data directly aligns with the missions of affordable homeownership, clarity, transparency, and effective oversight. It facilitates real-time compliance monitoring, improved market surveillance, and reduces reliance on costly third-party interpretations.
For the mortgage industry, structured data reduces costs, enhances compliance accuracy, and accelerates adoption of regulatory changes. Lenders can integrate real-time regulatory updates directly into automated systems, significantly cutting manual compliance efforts and improving overall lending efficiency.
It is an interesting thought experiment to consider who might host such a centralized data service. It is this author’s opinion that the information should quite obviously be democratized, so the cost of access should be negligible (the Federal Register application programming interface for example costs nothing to access). Yet there is a cost to create and manage such a service. There is a responsibility to be impartial and independent. Who should create and host this service?
Existing compliance data providers might resist open data, fearing revenue loss. However, AI-ready standards open new monetization avenues, such as advanced analytics, lower cost compliance validation services, and AI-driven tools built on top of structured data. Rather than competing on raw regulatory data, these companies can compete on sophisticated value-added offerings, growing their markets while improving industry compliance. Once the data is unlocked, an entirely new set of revenue opportunities will emerge.
States traditionally maintain independent mortgage regulations, posing a challenge to standardize. However, AI-ready data promises significant cost savings, streamlined compliance oversight, and improved accuracy in state-level enforcement. Demonstrating clear economic and operational benefits through pilot projects and leveraging existing cooperative models like the Nationwide Multistate Licensing System (NMLS) can effectively encourage state participation without compromising their regulatory autonomy.
If you make or use mortgage compliance requirements, we really want to here from you. Please engage and tell us what you think. Transitioning mortgage policy data to an AI-ready standard is so much more than a technical problem, it’s a strategic solution that unlocks previously infeasible efficiencies.
