Post Summary: Miami fintech startup Maximum has emerged from stealth with $30 million in seed funding to build what it describes as an AI-native operating system for banks. Led by CRV with backing from Pear VC, Restive, Plug and Play Ventures and Anthemis, the company is targeting legacy banking cores that were designed for batch processing rather than real-time software agents. Maximum's pitch is that banks need to rethink their underlying infrastructure, not simply add AI tools to aging systems. #Fintech #Banking #BankingTechnology #BankingInfrastructure #AIStartups #VentureCapital #StartupFunding #CoreBanking #FinancialServices
Replacing a bank's core system is one of the hardest things in financial technology. Maximum is betting the arrival of AI makes it necessary anyway.
The Miami-based fintech startup has emerged from stealth with $30 million in seed funding and an ambitious plan to build an AI-native operating system for banks.
The round was led by CRV, with participation from Pear VC, Restive, Plug and Play Ventures and Anthemis.
Founded by Randy Fernando, who previously founded Power Finance, Maximum argues that traditional banking cores were designed for a fundamentally different era of software. They record transactions, reconcile data and process information in batches. AI agents, by contrast, need continuous access to current data, the ability to act in real time and comprehensive audit trails.
That's the infrastructure gap Maximum wants to address.
The problem with legacy banking cores
Fernando said he started Maximum to build an intelligent bank operating system designed for a world where software can understand and anticipate rather than simply record information.
The distinction becomes important when AI agents are responsible for tasks such as compliance monitoring.
A compliance agent scanning transactions for sanctions violations or suspicious activity is only as effective as the information available to it. On older banking systems, that information can lag by hours or remain fragmented across different systems.
Deloitte Insights has highlighted a similar problem, pointing to fragmented data architectures and aging technology as barriers to banks deploying real-time, AI-native services.
The broader banking technology market is already moving in this direction. Backbase has introduced an AI-native banking operating system focused on unifying front-office operations, while Zafin founder Al Karim Somji has backed an AI-native core banking initiative through OpenCoreOS.
Maximum is taking the argument further: rather than layering AI onto legacy infrastructure, banks may need to replace the underlying system itself.
Why replacing the core is so difficult
The opportunity is enormous, but so is the execution challenge.
The U.S. banking market remains heavily dependent on a small group of core banking providers. Federal Reserve Bank of Kansas City research shows that Fiserv, Jack Henry and FIS control the majority of U.S. bank core contracts.
That concentration creates a significant barrier for startups trying to replace incumbent systems.
Moving away from a legacy core can take 18 to 24 months, require substantial internal staffing and expose banks to contract penalties and operational risk. For financial institutions, the consequences of a failed migration extend far beyond an ordinary software implementation.
That's why banks have historically preferred incremental upgrades to wholesale infrastructure changes.
Maximum is betting AI changes that calculation.
The AI-native banking argument
Fernando's thesis is that banks cannot get the full benefit of autonomous software agents if those agents are forced to operate on infrastructure that wasn't designed for real-time decision-making.
An AI agent that needs to understand a customer's financial position, check compliance requirements and execute an action needs immediate access to accurate information.
A legacy core built around batch processing creates friction at every stage.
Maximum wants to build the underlying operating environment around those requirements from the beginning, with real-time data access, autonomous software agents and auditability treated as core infrastructure rather than add-on capabilities.
The idea is attracting investors who already know Fernando's work. Several of Maximum's backers also invested in Power Finance, his previous company.
CRV partner Caitlin Bolnick Rellas said the firm believes banking technology has reached a point where incremental upgrades may no longer be enough.
Maximum still has to prove it
For all the size of the funding round, Maximum remains an early-stage bet.
The company has not publicly named customers or put its product into production. The new capital will fund product development, hiring and the first bank migrations, with the company planning to approach institutions one at a time.
That makes execution the central question.
Replacing a banking core is difficult under normal circumstances. Convincing a bank to entrust that infrastructure to a startup building a new AI-native architecture is an even bigger challenge.
But that's also what makes the opportunity potentially significant.
If Maximum is right, banks may eventually discover that the problem with deploying AI isn't the AI itself. It's the decades-old infrastructure underneath it.
What This Means for Miami
Maximum's emergence adds another significant fintech funding story to Miami's growing financial technology ecosystem.
The company's focus is particularly relevant to South Florida, where fintech startups, financial institutions and investors are increasingly exploring how AI can reshape financial services. A $30 million seed round for a company attempting to rebuild core banking infrastructure also demonstrates the scale of capital investors are willing to deploy behind fundamental financial technology.
For Miami's fintech founders, Maximum offers another signal that investors may be looking beyond AI applications toward the infrastructure underneath them.
For banks, the bigger question is whether AI adoption eventually makes replacing legacy systems economically compelling rather than merely technologically attractive.
