t54 Labs is a financial infrastructure company that builds tools allowing autonomous AI agents to securely execute and manage transactions across both fiat and cryptocurrency platforms. Pulse 2.0 interviewed t54 Labs founder Chandler Fang to learn more.
Chandler Fang’s Background
Could you tell me more about your background? Fang said:
“Sure. I started my career at J.P. Morgan after graduating from UC Berkeley, first in equity derivatives trading and quantitative risk management, then in 2019 I moved into JP Morgan’s Onyx/Kinexys group to build AI and blockchain driven financial products. After that I joined Ripple as an early product manager focused on cross-border payments and settlement networks “Ripple Payment”. Along the way, I’ve also been active in the Silicon Valley investing ecosystem as a venture partner and advisor across AI and Fintech projects. Across all of it, the consistent thread has been putting new technology into real financial workflows—and building the risk, controls, and accountability required for it to work in production—so when AI agents started moving from “assist” to “execute,” it felt obvious we’d need a trust framework for an agent economy.”
Formation Of The Company
How did the idea for the company come together? Fang shared:
“Living in Silicon Valley, you tend to see paradigm shifts early, and the breakout of large language models—especially when ChatGPT hit mainstream in late 2022 and GPT-4 raised the bar in 2023—made it clear we were entering a new interface era. By late 2024, the trajectory looked even more concrete: agents were moving beyond copilots into roles that involve real execution—initiating payments, managing treasury workflows, and interacting with financial systems directly. What struck me was that the “trust layer” wasn’t there: no shared way to verify what an agent is, what it’s allowed to do, how risky a given action is, or what happens when something fails. t54 came from that gap—we’re turning that observation into a practical trust layer so agents can operate inside real economic systems without turning every transaction into a blind leap of faith.”
Favorite Memory
What has been your favorite memory working for the company so far? Fang reflected:
“My favorite moment has been watching the narrative flip from skepticism to recognition—and then to real inbound demand. In 2024, when we described an “agent economy,” the common reaction was basically, “Agents touching money sounds unsafe; why would anyone allow that?” Then in 2025, the ecosystem started to crystallize: standards like OpenAI/Stripe’s Agentic Commerce Protocol and Coinbase’s x402 made agentic commerce feel less hypothetical, and more builders started shipping agents that trade, manage treasury, or shop programmatically. The consistent pain point they hit was the same one we saw early: without identity, guardrails, and accountable risk controls, autonomous execution creates fraud and loss risk that teams can’t tolerate. Seeing customers and partners arrive at that conclusion independently—and asking us to help—has been the most satisfying “we’re building the right thing” signal so far.”
t54 also recently partnered with Mastercard on the newly launched Agent Pay for Machines initiative, which is designed to explore priority use cases for agentic commerce, establish common operating frameworks, and accelerate adoption of machine-to-machine payments and AI-driven economic activity across industries. This marked a pivotal moment for us at t54, demonstrating how our vision is being fully recognized by established financial institutions.
Core Products
What are the company’s core products and features? Fang explained:
“Our core offering is a unified trust and execution layer built specifically for AI agents operating in financial systems. At the foundation is an identity and verification layer that covers developer verification, model provenance, human-agent binding, and intent attestation, allowing businesses to delegate authority while preserving compliance and auditability. On top of that sits a real-time risk and fraud engine that evaluates transactions using agent-native signals such as behavior patterns, code audits, mandates, and device context to detect anomalies and manipulation. We also underwrite agent-native credit, extending liquidity based on verified identity, risk scores, real-time signals, and transaction history. All of this is delivered as a single platform that integrates identity, risk controls, credit, and settlement without adding operational overhead.”
Challenges Faced
Have you faced any challenges in your sector recently? Fang acknowledged:
“One of the biggest challenges has been what I would call inherent institutional skepticism, in that many still treat AI agents as experimental, even as adoption accelerates. Security professionals remain cautious, and research from Keyfactor shows 86% believe autonomous agents need unique, dynamic digital identities. Bridging that trust gap required us to focus on practical integrations and risk controls, showing customers we’re not enabling reckless automation, but making it safer.”
Evolution Of The Company’s Technology
How has the company’s technology evolved since launching? Fang noted:
“Our stack has evolved in lockstep with the agent ecosystem. We’ve expanded support for emerging agent and commerce standards (like MCP and A2A, plus payment protocols such as x402 and ACP) so agents can onboard and transact in a more native, automated way, without relying on human-centric accounts, subscriptions, or manual approvals. On the settlement side, we’ve stayed chain-agnostic, supporting rails like XRPL, Solana, and Base, while extending compatibility to fiat workflows where customers need it. Internally, we’re also using our proprietary transaction and behavior data to train risk validator agents, steadily improving our ability to detect and respond to risky agent behavior in real time. The direction has been consistent: reduce integration friction, make identity and risk controls more dynamic, and turn underwriting into a continuous, agent-native loop that gets better as agents transact.”
Significant Milestones
What have been some of the company’s most significant milestones? Fang cited:
“Recently closing our $5 million seed round was a huge milestone. We attracted capital from some of the most reputable investors across the AI and blockchain spheres, such as Anagram, PL Capital, and Franklin Templeton, with strategic participation from Ripple, Virtuals Ventures, and Blockchain Coinvestors.”
Customer Success Stories
Can you share any specific customer success stories? Fang highlighted:
“We previously announced a strategic collaboration with Evernorth, the Ripple-backed digital asset treasury company raising over $1 billion for institutional XRP holdings. Under the collaboration, Evernorth intends to integrate t54’s agentic finance infrastructure and trust layer to power verification, risk assessment, and compliance for autonomous treasury operations on the XRP Ledger.”
Funding/Revenue
Are you able to discuss funding and/or revenue metrics? Fang revealed:
“As mentioned previously, we’ve been fortunate to secure strong backing from investors who understand both financial infrastructure and emerging AI systems. Our $5 million seed round has given us ample financial runway to focus on long-term architecture rather than short-term optimization. Our approach has been to prioritize meaningful enterprise adoption over vanity metrics. As the agent economy matures, we believe infrastructure providers like ourselves will naturally sit at the center of value creation, and our funding strategy reflects that longer-term view.”
Total Addressable Market (TAM)
What total addressable market (TAM) size is the company pursuing? Fang assessed:
“We view our TAM as overlapping payments infrastructure, treasury management, AI tooling, and digital identity, each of which is already measured in the tens or hundreds of billions. As AI agents begin executing economic actions directly, the need for trust, risk, and accountability layers grows alongside every transaction they touch. Given consumer openness to AI-powered commerce (a YouGov study found 42% of U.S. consumers would let an AI agent purchase on their behalf for better pricing), we believe the agent trust market will expand rapidly. Our goal is to become a core layer in that stack, rather than a feature within it.”
Differentiation From The Competition
What differentiates the company from its competition? Fang affirmed:
“t54 is purpose-built for AI agents, not retrofitted from human-centric identity or compliance systems. Many solutions assume a human behind every action, but we assume autonomy by default. Our focus on dynamic identity, continuous risk assessment, and failure accountability reflects how agents actually operate. We’re also infrastructure-first, designed to integrate across payments, treasury, and commerce rather than locking customers into a closed ecosystem.”
Future Company Goals
What are some of the company’s future goals? Fang emphasized:
“Our near-term goal is to deepen adoption among payment providers and financial institutions experimenting with agent-driven execution. Longer term, we want t54 to be the default trust layer for autonomous economic activity, similar to how identity and settlement layers underpin today’s internet economy. As more consumers and businesses rely on AI agents to transact on their behalf, ensuring those agents are verifiable, accountable, and safe becomes non-negotiable. We aim to be the infrastructure that makes that scale responsibly.”
Additional Thoughts
Any other topics you would like to discuss? Fang concluded:
“One area I think deserves more attention is the mismatch between consumer enthusiasm and institutional readiness. People are often more willing to trust AI agents than the systems governing them are prepared for. That gap creates risk, but also opportunity. If we can align consumer demand, enterprise safeguards, and agent autonomy through shared infrastructure, the agent economy can grow without repeating past mistakes.”
